Review ArticleDEMATEL Technique A Systematic Review of theState-of-the-Art Literature on Methodologies and Applications
Sheng-Li Si1 Xiao-Yue You12 Hu-Chen Liu 3 and Ping Zhang13
1School of Economics and Management Tongji University Shanghai 200092 China2Institute for Manufacturing University of Cambridge Cambridge CB3 0FS UK3School of Management Shanghai University Shanghai 200444 China
Correspondence should be addressed to Hu-Chen Liu huchenliushueducn
Received 8 October 2017 Accepted 14 December 2017 Published 14 January 2018
Academic Editor Marco Pizzarelli
Copyright copy 2018 Sheng-Li Si et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system It deals with evaluating interdependent relationships among factors and findingthe critical ones through a visual structural model Over the recent decade a large number of studies have been done on theapplication of DEMATEL andmany different variants have been put forward in the literatureThe objective of this study is to reviewsystematically the methodologies and applications of the DEMATEL technique We reviewed a total of 346 papers published from2006 to 2016 in the international journals According to the approaches used these publications are grouped into five categoriesclassical DEMATEL fuzzyDEMATEL greyDEMATEL analytical network process- (ANP-)DEMATEL and otherDEMATEL Allpapers with respect to each category are summarized and analyzed pointing out their implementing procedures real applicationsand crucial findingsThis systematic and comprehensive review holds valuable insights for researchers and practitioners into usingthe DEMATEL in terms of indicating current research trends and potential directions for further research
1 Introduction
Decision making trial and evaluation laboratory (DEMA-TEL) technique was first developed by the Geneva ResearchCentre of the Battelle Memorial Institute to visualizethe structure of complicated causal relationships throughmatrixes or digraphs [1] As a kind of structural modelingapproach it is especially useful in analyzing the cause andeffect relationships among components of a system TheDEMATEL can confirm interdependence among factors andaid in the development of a map to reflect relative relation-ships within them and can be used for investigating andsolving complicated and intertwined problems This methodnot only converts the interdependency relationships into acause and effect group via matrixes but also finds the criticalfactors of a complex structure system with the help of animpact relation diagram
Due to its advantages and capabilities the approach ofDEMATEL has received a great deal of attention in the pastdecade and many researchers have applied it for solving
complicated system problems in various areas In additionthe DEMATEL has been extended for better decisionmakingunder different environments since many real-world systemsinclude imprecise and uncertain information However tothe best of our knowledge no systematic review has beenperformed for the DEMATEL technique and its applicationsTherefore in this study we present a comprehensive reviewof the state-of-the-art literature regarding the approaches todecision making based on the DEMATEL As a result ofsearch using the Scopus database and following a method-ological decision analysis a total of 346 papers publishedin scientific journals from 2006 to 2016 were reviewed indetail Based on the selected articles the main objectives ofthis review are as follows (1) to summarize the DEMATELmethods that have been used in the academic literature (2)to reveal the different usage and application areas of theseapproaches (3) to show the current research trends in thisfield of study and (4) to find out the potential researchdirections in the future
HindawiMathematical Problems in EngineeringVolume 2018 Article ID 3696457 33 pageshttpsdoiorg10115520183696457
2 Mathematical Problems in Engineering
The remaining part of this paper is structured as followsIn Section 2 we introduce the research methodology used toidentify and refine the literature in this study In Section 3detailed reviews of each category of the DEMATEL studiesare presented Section 4 describes some general observationsand findings based on statistical analysis results of thereview Finally this paper concludes in Section 5 by sum-marizing the results and discussing opportunities for futureresearch
2 Research Methodology
For the purpose of this literature review we searched forarticles in the Scopus database published between 2006 and2016 The choice of this time period is based on the factthat the majority of papers on this topic were publishedduring this period and there are only five articles recordedin the Scopus prior to 2006 Inspired by the PreferredReporting Items for Systematic Reviews and Meta-Analyses(PRISRMA) method [2 3] the selection of articles in thisstudy is consisted of three stages that is literature searcharticles eligibility and data extraction and summarizingFirst the keyword ldquoDEMATELrdquo was used for searching inldquoabstract title and keywordsrdquo for journal papers and atotal of 509 document results were identified from ScopusNext we chose the articles which had used the DEMATELtechnique or its extensions to solve real-world problemsand 346 academic papers fell under the scope of this reviewafter title abstract and full-text screening Since this studyfocuses on both the DEMATEL and its applications thosestudies which only modify the DEMATEL technique withoutapplying to actual settings have been eliminated (for theinterested readers please refer eg to [4ndash6]) Finally theresulting papers were reviewed thoroughly to identify thefocus method application and combination with othermethods Also articles were summarized based on variouscriteria such as year of publication application areas andcitations
Based on the DEMATEL methods adopted the selectedpublications are roughly grouped into five categories the onesusing classical DEMATEL (105 articles) the ones using fuzzyDEMATEL (63 articles) the ones using grey DEMATEL(12 articles) the ones combining analytical network process(ANP) and DEMATEL (154 articles) and the ones basedon other DEMATEL methods (12 articles) The classificationscheme of the DEMATEL articles is shown in Figure 1Most of the papers on ANP and DEMATEL hybridizationare included in a review paper of DEMATEL approachesfor criteria interaction handling with ANP by Golcuk andBaykasoglu [7] Therefore in the following sections wewill not discuss the studies which apply the DEMATELin conjunction with ANP to deal with interactions amongcriteria
3 Reviews of DEMATEL Methods
31 The Classical DEMATEL As stated earlier the DEMA-TEL technique can convert the interrelations between factors
Classical DEMATEL303
Fuzzy DEMATEL 182
ANP and DEMATEL445
Grey DEMATEL35
Other DEMATEL 35
Figure 1 Classification scheme of the DEMATEL articles
into an intelligible structural model of the system and dividethem into a cause group and an effect group [8] Hence it isan applicable and useful tool to analyze the interdependentrelationships among factors in a complex system and rankthem for long-term strategic decision making and indicatingimprovement scopes The formulating steps of the classicalDEMATEL can be summarized as follows [8ndash10]
Step 1 (generate the group direct-influence matrix 119885) Toassess the relationships between 119899 factors 119865 = 1198651 1198652 119865119899in a system suppose that 119897 experts in a decision group 119864 =1198641 1198642 119864119897 are asked to indicate the direct influence thatfactor 119865119894 has on factor 119865119895 using an integer scale of ldquonoinfluence (0)rdquo ldquolow influence (1)rdquo ldquomedium influence (2)rdquoldquohigh influence (3)rdquo and ldquovery high influence (4)rdquo Then theindividual direct-influence matrix 119885119896 = [119911119896119894119895]119899times119899 provided bythe 119896th expert can be formed where all principal diagonalelements are equal to zero and 119911119896119894119895 represents the judgmentof decision maker 119864119896 on the degree to which factor 119865119894 affectsfactor 119865119895 By aggregating the 119897 expertsrsquo opinions the groupdirect-influence matrix 119885 = [119911119894119895]119899times119899 can be obtained by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 119894 119895 = 1 2 119899 (1)
Step 2 (establish the normalized direct-influence matrix 119883)When the group direct-influence matrix 119885 is acquired thenormalized direct-influence matrix 119883 = [119909119894119895]119899times119899 can beachieved by using
119883 = 119885119904 (2)
119904 = max(max1le119894le119899
119899sum119895=1
119911119894119895max1le119894le119899
119899sum119894=1
119911119894119895) (3)
Mathematical Problems in Engineering 3
All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by
119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)
in which 119868 is denoted as an identity matrix
Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas
119877 = [119903119894]119899times1 = [[119899sum119895=1
119905119894119895]]119899times1
119862 = [119888119895]1times119899 = [119899sum119894=1
119905119894119895]119879
1times119899
(5)
where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors
Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making
311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria
In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach
Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM
If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]
Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840
To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale
119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)
where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is
119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)
Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in
4 Mathematical Problems in Engineering
Table1Va
rious
applications
ofthec
lassicalDEM
ATEL
Papers
Research
purposes
Com
binatio
nsRe
marks
Type
1interrelationships
BEfea
ndOFE
fe[42]
Specify
theinfl
uenced
egrees
ofthep
atient
perceivedvalues
whenapplying
lean
health-care
managem
entinan
emergencydepartment
Thresholdvalue-
average
Malekzadehetal[43]
Investigatethe
causea
ndeffectrelations
forthe
dimensio
nsandcompo
nentso
forganizational
intelligenceinIranianpu
blicun
iversities
Thresholdvalue
Ranjan
etal[44
]Ad
dressthe
interrelationships
betweendifferent
evaluatio
ncriteria
ofIndian
Railw
ayzones
VIKOR
Thresholdvalue-
average
Tzengetal[10]
Addressthe
depend
entrelations
ofevaluatio
ncriteria
andprop
osea
hybrid
MCD
Mmod
elfor
evaluatin
gintertwined
effectsin
e-learning
programs
FAA
HPfuzzy
integral
Threshold
value-experts
Huetal[45]
Establish
thec
ausalrelationshipandextent
ofmutualimpactam
ongqu
ality
features
andpu
tforth
adecision
analysismetho
dology
toremovep
otentia
lproblem
sfrom
thec
onventionalIPA
mod
elBP
NN
Huetal[46
]Analyze
thec
ause-effectrelationshipam
ongdifferent
quality
characteris
ticstomaker
evision
sto
thetraditio
nalIPA
mod
elandfin
dthec
orep
roblem
sinvolvedwith
winning
orders
GAM
RA
Chengetal[47]
Explorethe
conn
ectio
nbetweenserviceq
ualityattributes
andthes
ervice
quality
improvem
ent
priorityof
fine-dining
restaurantsa
nduseitasa
referencefor
serviceq
ualitystr
ategyplanning
andresource
reorganizing
IPGA
Hsie
handYeh[48]
Exam
inec
ause
andeffectrela
tions
offactorsinfl
uencingthe
serviceq
ualityinfastfood
restaurants
Thresholdvalue-
average
Chiu
etal[49]
Analyze
relatio
nships
ofcusto
mer
buying
decisio
nfactorsa
ndprovidea
marketin
gstr
ategy
planning
forfi
rmsintheL
CD-TVmarket
Hoetal[50]
Analyze
thec
ause-effectrelationbetweenqu
ality
characteris
ticsa
ndbu
ildam
etho
dology
ofsupp
lierq
ualityperfo
rmance
assessmenttoim
proves
upplierq
ualitythroug
hop
timizing
order-winnersandqu
alifiers
IPAM
RA
Tsaietal[51]
Determinethe
causalrelationships
ofandinteractiveinfl
uencea
mon
gcriteria
andprop
osea
mixed
mod
elto
evaluatejobsatisfactionin
high
-tech
indu
strie
sIPA
Najmiand
Makui
[52]
Und
ersta
ndther
elationshipbetweencomparis
onmetric
sand
prop
osea
conceptualmod
elfor
measurin
gsupp
lychainperfo
rmance
AHP
Shafiee
etal[53]
Determinethe
relationships
betweenfour
perspectives
ofBS
Candprop
osea
napproach
toevaluatethep
erform
ance
ofsupp
lychain
DEA
BSC
Thresholdvalue-
average
ShaikandAb
dul-K
ader
[16]
Und
ersta
ndtheinterdepend
ence
amon
gperfo
rmance
factorsa
nddevelopar
everse
logistics
enterpris
eperform
ance
measurementm
odel
BSC
Innerd
ependence
matrix
Mathematical Problems in Engineering 5
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
LinandTzeng[11]
Determinethe
relatio
nshipbetweenthee
valuationcriteria
contrib
utingindu
stryclu
stersand
establish
theirv
alue
structuresa
ndbu
ildav
alue-created
syste
mof
science(techno
logy)p
ark
Threshold
value-experts
LinandSun[18]
Exam
inethe
impactso
fand
determ
inethe
relationships
amon
gdifferent
drivingforces
forthe
grow
thof
indu
strialcluste
rs
Threshold
value-expertsinner
depend
ence
matrix
WangandHsueh
[54]
Recogn
izethe
causalrelationships
betweendesig
nattributes
andmarketin
grequ
irementsand
prop
osea
napproach
toincorporatec
ustomer
preference
andperceptio
ninto
prod
uct
developm
ent
AHPKa
nomod
el
WangandSh
ih[55]
Identifytheimpactso
ffun
ctionalattributes
oncusto
mer
requ
irementsandpresenta
fram
ework
toincorporatec
ustomer
preferencesintoprod
uctd
evelo
pment
CA1QFD
TO
PSIS
Koetal[56]
Analyze
directandindirectim
pactsa
mon
gvario
ustechno
logy
areasa
ndpresenta
combined
approach
toconstructtechn
olog
yim
pactnetworks
forR
ampDplanning
usingpatents
SNA
Yoon
etal[57]
Assesstechno
logicalimpactsa
nddegree
ofcauseo
reffectam
ongtechno
logy
areasw
ithin
the
Korean
techno
logy
syste
mandob
servetheirdynamictre
nds
PCCA
Shen
andTzeng[58]
Explorethe
cause-effectrelationships
amon
gthea
ttributes
inthes
trong
decisio
nrulesa
ndprop
osea
mod
elfortacklingthev
alue
stock
selectionprob
lem
DRS
AFCA
Altu
ntas
andDereli
[59]
Establish
causalrelationships
amon
gtechno
logies
andprop
osea
napproach
forp
rioritizing
investmentp
rojectsfrom
theg
overnm
entrsquos
perspective
PCA
Thresholdvalue-
average
Shen
andTzeng[60]
Explorethe
complex
relationshipam
ongfin
ancialindicatorsandim
provefuturefi
nancial
perfo
rmance
oftheITindu
stry
VC-D
RSAFIS
Leea
ndLin[13]
Find
theinterrelationshipof
financialratio
sidentified
bymanagerso
fshipp
ingcompanies
and
financialexpertsa
ndcompare
theirc
ognitio
nmapsb
ycoun
tryandexpertgrou
pTh
resholdvalue-
MMDE
W-K
Tan
andY-J
Tan[61]
Analyze
howdifferent
factorsinteractand
collectively
contrib
utetothes
uccessfultransform
ation
anddiffu
sionof
thes
mart-c
ard-basede-micropaym
entm
ultip
urpo
sescheme
Azadehetal[12]
Evaluatetheimpactdegree
ofleannessfactorsa
ndpresentsac
omprehensiv
eapp
roachfor
evaluatin
gandop
timizingtheleann
essd
egreeo
forganizations
(lean
prod
uctio
n)
DEA
fuzzy
DEA
FCM
AHP
Thresholdvalue-
average
Sara
etal[14]
Assessrelativeimpo
rtance
andmutualinfl
uenceo
fbarrie
rsforc
arbo
ncapturea
ndsto
rage
deployment
AHP
Thresholdvalue-
average
Liaw
etal[62]
Analyze
theind
irectrelations
betweensubsystemsa
ndcompo
nentsa
ndprop
osea
reliability
allocatio
nmetho
dto
solvethe
fund
amentalproblem
sofcon
ventionalreliabilityappo
rtionm
ent
metho
dsME-OWA
Type
2interrelationships
andkeyfactors
AlaeiandAlro
aia[
63]
Identifyandprioritizethe
factorsa
ffectingandaffectedby
thep
erform
ance
ofsm
alland
medium
enterpris
es
Bacudioetal[64
]Analyze
cause-effectrelationships
ofbarriersto
implem
entin
gindu
stria
lsym
biosisnetworks
inan
indu
strialp
ark
Thresholdvalue-
averageinner
depend
ence
matrix
Balkovskayaa
ndFilneva[
65]
Identifycausalrelationships
betweenthek
eyevaluatio
nindicatorsof
bank
ingperfo
rmance
aswell
asdefin
ingthem
oststrategicallyim
portantind
icators
BSC
Threshold
value-second
quartile
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
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2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
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imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
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2no
rmalization
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Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
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res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
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fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
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hybrid
fuzzymod
elforsup
pliersele
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Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
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Defuzzification-
centroid
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Wang[179]
Interrelationships
Criteria
weights
Recogn
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betweenmarketin
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irementsandtechnical
attributes
andprop
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ystems
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A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
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metho
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Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
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uences
ofcriteria
into
each
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ndprop
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Mapproach
foro
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ELEC
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Defuzzification-Yager
rank
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matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
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expertsweights-
fuzzy
ANP
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rocessD
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onM
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Cmultio
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edecision
makingMODMunifiedtheory
ofacceptance
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UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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2 Mathematical Problems in Engineering
The remaining part of this paper is structured as followsIn Section 2 we introduce the research methodology used toidentify and refine the literature in this study In Section 3detailed reviews of each category of the DEMATEL studiesare presented Section 4 describes some general observationsand findings based on statistical analysis results of thereview Finally this paper concludes in Section 5 by sum-marizing the results and discussing opportunities for futureresearch
2 Research Methodology
For the purpose of this literature review we searched forarticles in the Scopus database published between 2006 and2016 The choice of this time period is based on the factthat the majority of papers on this topic were publishedduring this period and there are only five articles recordedin the Scopus prior to 2006 Inspired by the PreferredReporting Items for Systematic Reviews and Meta-Analyses(PRISRMA) method [2 3] the selection of articles in thisstudy is consisted of three stages that is literature searcharticles eligibility and data extraction and summarizingFirst the keyword ldquoDEMATELrdquo was used for searching inldquoabstract title and keywordsrdquo for journal papers and atotal of 509 document results were identified from ScopusNext we chose the articles which had used the DEMATELtechnique or its extensions to solve real-world problemsand 346 academic papers fell under the scope of this reviewafter title abstract and full-text screening Since this studyfocuses on both the DEMATEL and its applications thosestudies which only modify the DEMATEL technique withoutapplying to actual settings have been eliminated (for theinterested readers please refer eg to [4ndash6]) Finally theresulting papers were reviewed thoroughly to identify thefocus method application and combination with othermethods Also articles were summarized based on variouscriteria such as year of publication application areas andcitations
Based on the DEMATEL methods adopted the selectedpublications are roughly grouped into five categories the onesusing classical DEMATEL (105 articles) the ones using fuzzyDEMATEL (63 articles) the ones using grey DEMATEL(12 articles) the ones combining analytical network process(ANP) and DEMATEL (154 articles) and the ones basedon other DEMATEL methods (12 articles) The classificationscheme of the DEMATEL articles is shown in Figure 1Most of the papers on ANP and DEMATEL hybridizationare included in a review paper of DEMATEL approachesfor criteria interaction handling with ANP by Golcuk andBaykasoglu [7] Therefore in the following sections wewill not discuss the studies which apply the DEMATELin conjunction with ANP to deal with interactions amongcriteria
3 Reviews of DEMATEL Methods
31 The Classical DEMATEL As stated earlier the DEMA-TEL technique can convert the interrelations between factors
Classical DEMATEL303
Fuzzy DEMATEL 182
ANP and DEMATEL445
Grey DEMATEL35
Other DEMATEL 35
Figure 1 Classification scheme of the DEMATEL articles
into an intelligible structural model of the system and dividethem into a cause group and an effect group [8] Hence it isan applicable and useful tool to analyze the interdependentrelationships among factors in a complex system and rankthem for long-term strategic decision making and indicatingimprovement scopes The formulating steps of the classicalDEMATEL can be summarized as follows [8ndash10]
Step 1 (generate the group direct-influence matrix 119885) Toassess the relationships between 119899 factors 119865 = 1198651 1198652 119865119899in a system suppose that 119897 experts in a decision group 119864 =1198641 1198642 119864119897 are asked to indicate the direct influence thatfactor 119865119894 has on factor 119865119895 using an integer scale of ldquonoinfluence (0)rdquo ldquolow influence (1)rdquo ldquomedium influence (2)rdquoldquohigh influence (3)rdquo and ldquovery high influence (4)rdquo Then theindividual direct-influence matrix 119885119896 = [119911119896119894119895]119899times119899 provided bythe 119896th expert can be formed where all principal diagonalelements are equal to zero and 119911119896119894119895 represents the judgmentof decision maker 119864119896 on the degree to which factor 119865119894 affectsfactor 119865119895 By aggregating the 119897 expertsrsquo opinions the groupdirect-influence matrix 119885 = [119911119894119895]119899times119899 can be obtained by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 119894 119895 = 1 2 119899 (1)
Step 2 (establish the normalized direct-influence matrix 119883)When the group direct-influence matrix 119885 is acquired thenormalized direct-influence matrix 119883 = [119909119894119895]119899times119899 can beachieved by using
119883 = 119885119904 (2)
119904 = max(max1le119894le119899
119899sum119895=1
119911119894119895max1le119894le119899
119899sum119894=1
119911119894119895) (3)
Mathematical Problems in Engineering 3
All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by
119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)
in which 119868 is denoted as an identity matrix
Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas
119877 = [119903119894]119899times1 = [[119899sum119895=1
119905119894119895]]119899times1
119862 = [119888119895]1times119899 = [119899sum119894=1
119905119894119895]119879
1times119899
(5)
where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors
Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making
311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria
In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach
Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM
If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]
Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840
To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale
119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)
where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is
119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)
Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in
4 Mathematical Problems in Engineering
Table1Va
rious
applications
ofthec
lassicalDEM
ATEL
Papers
Research
purposes
Com
binatio
nsRe
marks
Type
1interrelationships
BEfea
ndOFE
fe[42]
Specify
theinfl
uenced
egrees
ofthep
atient
perceivedvalues
whenapplying
lean
health-care
managem
entinan
emergencydepartment
Thresholdvalue-
average
Malekzadehetal[43]
Investigatethe
causea
ndeffectrelations
forthe
dimensio
nsandcompo
nentso
forganizational
intelligenceinIranianpu
blicun
iversities
Thresholdvalue
Ranjan
etal[44
]Ad
dressthe
interrelationships
betweendifferent
evaluatio
ncriteria
ofIndian
Railw
ayzones
VIKOR
Thresholdvalue-
average
Tzengetal[10]
Addressthe
depend
entrelations
ofevaluatio
ncriteria
andprop
osea
hybrid
MCD
Mmod
elfor
evaluatin
gintertwined
effectsin
e-learning
programs
FAA
HPfuzzy
integral
Threshold
value-experts
Huetal[45]
Establish
thec
ausalrelationshipandextent
ofmutualimpactam
ongqu
ality
features
andpu
tforth
adecision
analysismetho
dology
toremovep
otentia
lproblem
sfrom
thec
onventionalIPA
mod
elBP
NN
Huetal[46
]Analyze
thec
ause-effectrelationshipam
ongdifferent
quality
characteris
ticstomaker
evision
sto
thetraditio
nalIPA
mod
elandfin
dthec
orep
roblem
sinvolvedwith
winning
orders
GAM
RA
Chengetal[47]
Explorethe
conn
ectio
nbetweenserviceq
ualityattributes
andthes
ervice
quality
improvem
ent
priorityof
fine-dining
restaurantsa
nduseitasa
referencefor
serviceq
ualitystr
ategyplanning
andresource
reorganizing
IPGA
Hsie
handYeh[48]
Exam
inec
ause
andeffectrela
tions
offactorsinfl
uencingthe
serviceq
ualityinfastfood
restaurants
Thresholdvalue-
average
Chiu
etal[49]
Analyze
relatio
nships
ofcusto
mer
buying
decisio
nfactorsa
ndprovidea
marketin
gstr
ategy
planning
forfi
rmsintheL
CD-TVmarket
Hoetal[50]
Analyze
thec
ause-effectrelationbetweenqu
ality
characteris
ticsa
ndbu
ildam
etho
dology
ofsupp
lierq
ualityperfo
rmance
assessmenttoim
proves
upplierq
ualitythroug
hop
timizing
order-winnersandqu
alifiers
IPAM
RA
Tsaietal[51]
Determinethe
causalrelationships
ofandinteractiveinfl
uencea
mon
gcriteria
andprop
osea
mixed
mod
elto
evaluatejobsatisfactionin
high
-tech
indu
strie
sIPA
Najmiand
Makui
[52]
Und
ersta
ndther
elationshipbetweencomparis
onmetric
sand
prop
osea
conceptualmod
elfor
measurin
gsupp
lychainperfo
rmance
AHP
Shafiee
etal[53]
Determinethe
relationships
betweenfour
perspectives
ofBS
Candprop
osea
napproach
toevaluatethep
erform
ance
ofsupp
lychain
DEA
BSC
Thresholdvalue-
average
ShaikandAb
dul-K
ader
[16]
Und
ersta
ndtheinterdepend
ence
amon
gperfo
rmance
factorsa
nddevelopar
everse
logistics
enterpris
eperform
ance
measurementm
odel
BSC
Innerd
ependence
matrix
Mathematical Problems in Engineering 5
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
LinandTzeng[11]
Determinethe
relatio
nshipbetweenthee
valuationcriteria
contrib
utingindu
stryclu
stersand
establish
theirv
alue
structuresa
ndbu
ildav
alue-created
syste
mof
science(techno
logy)p
ark
Threshold
value-experts
LinandSun[18]
Exam
inethe
impactso
fand
determ
inethe
relationships
amon
gdifferent
drivingforces
forthe
grow
thof
indu
strialcluste
rs
Threshold
value-expertsinner
depend
ence
matrix
WangandHsueh
[54]
Recogn
izethe
causalrelationships
betweendesig
nattributes
andmarketin
grequ
irementsand
prop
osea
napproach
toincorporatec
ustomer
preference
andperceptio
ninto
prod
uct
developm
ent
AHPKa
nomod
el
WangandSh
ih[55]
Identifytheimpactso
ffun
ctionalattributes
oncusto
mer
requ
irementsandpresenta
fram
ework
toincorporatec
ustomer
preferencesintoprod
uctd
evelo
pment
CA1QFD
TO
PSIS
Koetal[56]
Analyze
directandindirectim
pactsa
mon
gvario
ustechno
logy
areasa
ndpresenta
combined
approach
toconstructtechn
olog
yim
pactnetworks
forR
ampDplanning
usingpatents
SNA
Yoon
etal[57]
Assesstechno
logicalimpactsa
nddegree
ofcauseo
reffectam
ongtechno
logy
areasw
ithin
the
Korean
techno
logy
syste
mandob
servetheirdynamictre
nds
PCCA
Shen
andTzeng[58]
Explorethe
cause-effectrelationships
amon
gthea
ttributes
inthes
trong
decisio
nrulesa
ndprop
osea
mod
elfortacklingthev
alue
stock
selectionprob
lem
DRS
AFCA
Altu
ntas
andDereli
[59]
Establish
causalrelationships
amon
gtechno
logies
andprop
osea
napproach
forp
rioritizing
investmentp
rojectsfrom
theg
overnm
entrsquos
perspective
PCA
Thresholdvalue-
average
Shen
andTzeng[60]
Explorethe
complex
relationshipam
ongfin
ancialindicatorsandim
provefuturefi
nancial
perfo
rmance
oftheITindu
stry
VC-D
RSAFIS
Leea
ndLin[13]
Find
theinterrelationshipof
financialratio
sidentified
bymanagerso
fshipp
ingcompanies
and
financialexpertsa
ndcompare
theirc
ognitio
nmapsb
ycoun
tryandexpertgrou
pTh
resholdvalue-
MMDE
W-K
Tan
andY-J
Tan[61]
Analyze
howdifferent
factorsinteractand
collectively
contrib
utetothes
uccessfultransform
ation
anddiffu
sionof
thes
mart-c
ard-basede-micropaym
entm
ultip
urpo
sescheme
Azadehetal[12]
Evaluatetheimpactdegree
ofleannessfactorsa
ndpresentsac
omprehensiv
eapp
roachfor
evaluatin
gandop
timizingtheleann
essd
egreeo
forganizations
(lean
prod
uctio
n)
DEA
fuzzy
DEA
FCM
AHP
Thresholdvalue-
average
Sara
etal[14]
Assessrelativeimpo
rtance
andmutualinfl
uenceo
fbarrie
rsforc
arbo
ncapturea
ndsto
rage
deployment
AHP
Thresholdvalue-
average
Liaw
etal[62]
Analyze
theind
irectrelations
betweensubsystemsa
ndcompo
nentsa
ndprop
osea
reliability
allocatio
nmetho
dto
solvethe
fund
amentalproblem
sofcon
ventionalreliabilityappo
rtionm
ent
metho
dsME-OWA
Type
2interrelationships
andkeyfactors
AlaeiandAlro
aia[
63]
Identifyandprioritizethe
factorsa
ffectingandaffectedby
thep
erform
ance
ofsm
alland
medium
enterpris
es
Bacudioetal[64
]Analyze
cause-effectrelationships
ofbarriersto
implem
entin
gindu
stria
lsym
biosisnetworks
inan
indu
strialp
ark
Thresholdvalue-
averageinner
depend
ence
matrix
Balkovskayaa
ndFilneva[
65]
Identifycausalrelationships
betweenthek
eyevaluatio
nindicatorsof
bank
ingperfo
rmance
aswell
asdefin
ingthem
oststrategicallyim
portantind
icators
BSC
Threshold
value-second
quartile
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering 3
All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by
119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)
in which 119868 is denoted as an identity matrix
Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas
119877 = [119903119894]119899times1 = [[119899sum119895=1
119905119894119895]]119899times1
119862 = [119888119895]1times119899 = [119899sum119894=1
119905119894119895]119879
1times119899
(5)
where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors
Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making
311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria
In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach
Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM
If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]
Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840
To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale
119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)
where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is
119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)
Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in
4 Mathematical Problems in Engineering
Table1Va
rious
applications
ofthec
lassicalDEM
ATEL
Papers
Research
purposes
Com
binatio
nsRe
marks
Type
1interrelationships
BEfea
ndOFE
fe[42]
Specify
theinfl
uenced
egrees
ofthep
atient
perceivedvalues
whenapplying
lean
health-care
managem
entinan
emergencydepartment
Thresholdvalue-
average
Malekzadehetal[43]
Investigatethe
causea
ndeffectrelations
forthe
dimensio
nsandcompo
nentso
forganizational
intelligenceinIranianpu
blicun
iversities
Thresholdvalue
Ranjan
etal[44
]Ad
dressthe
interrelationships
betweendifferent
evaluatio
ncriteria
ofIndian
Railw
ayzones
VIKOR
Thresholdvalue-
average
Tzengetal[10]
Addressthe
depend
entrelations
ofevaluatio
ncriteria
andprop
osea
hybrid
MCD
Mmod
elfor
evaluatin
gintertwined
effectsin
e-learning
programs
FAA
HPfuzzy
integral
Threshold
value-experts
Huetal[45]
Establish
thec
ausalrelationshipandextent
ofmutualimpactam
ongqu
ality
features
andpu
tforth
adecision
analysismetho
dology
toremovep
otentia
lproblem
sfrom
thec
onventionalIPA
mod
elBP
NN
Huetal[46
]Analyze
thec
ause-effectrelationshipam
ongdifferent
quality
characteris
ticstomaker
evision
sto
thetraditio
nalIPA
mod
elandfin
dthec
orep
roblem
sinvolvedwith
winning
orders
GAM
RA
Chengetal[47]
Explorethe
conn
ectio
nbetweenserviceq
ualityattributes
andthes
ervice
quality
improvem
ent
priorityof
fine-dining
restaurantsa
nduseitasa
referencefor
serviceq
ualitystr
ategyplanning
andresource
reorganizing
IPGA
Hsie
handYeh[48]
Exam
inec
ause
andeffectrela
tions
offactorsinfl
uencingthe
serviceq
ualityinfastfood
restaurants
Thresholdvalue-
average
Chiu
etal[49]
Analyze
relatio
nships
ofcusto
mer
buying
decisio
nfactorsa
ndprovidea
marketin
gstr
ategy
planning
forfi
rmsintheL
CD-TVmarket
Hoetal[50]
Analyze
thec
ause-effectrelationbetweenqu
ality
characteris
ticsa
ndbu
ildam
etho
dology
ofsupp
lierq
ualityperfo
rmance
assessmenttoim
proves
upplierq
ualitythroug
hop
timizing
order-winnersandqu
alifiers
IPAM
RA
Tsaietal[51]
Determinethe
causalrelationships
ofandinteractiveinfl
uencea
mon
gcriteria
andprop
osea
mixed
mod
elto
evaluatejobsatisfactionin
high
-tech
indu
strie
sIPA
Najmiand
Makui
[52]
Und
ersta
ndther
elationshipbetweencomparis
onmetric
sand
prop
osea
conceptualmod
elfor
measurin
gsupp
lychainperfo
rmance
AHP
Shafiee
etal[53]
Determinethe
relationships
betweenfour
perspectives
ofBS
Candprop
osea
napproach
toevaluatethep
erform
ance
ofsupp
lychain
DEA
BSC
Thresholdvalue-
average
ShaikandAb
dul-K
ader
[16]
Und
ersta
ndtheinterdepend
ence
amon
gperfo
rmance
factorsa
nddevelopar
everse
logistics
enterpris
eperform
ance
measurementm
odel
BSC
Innerd
ependence
matrix
Mathematical Problems in Engineering 5
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
LinandTzeng[11]
Determinethe
relatio
nshipbetweenthee
valuationcriteria
contrib
utingindu
stryclu
stersand
establish
theirv
alue
structuresa
ndbu
ildav
alue-created
syste
mof
science(techno
logy)p
ark
Threshold
value-experts
LinandSun[18]
Exam
inethe
impactso
fand
determ
inethe
relationships
amon
gdifferent
drivingforces
forthe
grow
thof
indu
strialcluste
rs
Threshold
value-expertsinner
depend
ence
matrix
WangandHsueh
[54]
Recogn
izethe
causalrelationships
betweendesig
nattributes
andmarketin
grequ
irementsand
prop
osea
napproach
toincorporatec
ustomer
preference
andperceptio
ninto
prod
uct
developm
ent
AHPKa
nomod
el
WangandSh
ih[55]
Identifytheimpactso
ffun
ctionalattributes
oncusto
mer
requ
irementsandpresenta
fram
ework
toincorporatec
ustomer
preferencesintoprod
uctd
evelo
pment
CA1QFD
TO
PSIS
Koetal[56]
Analyze
directandindirectim
pactsa
mon
gvario
ustechno
logy
areasa
ndpresenta
combined
approach
toconstructtechn
olog
yim
pactnetworks
forR
ampDplanning
usingpatents
SNA
Yoon
etal[57]
Assesstechno
logicalimpactsa
nddegree
ofcauseo
reffectam
ongtechno
logy
areasw
ithin
the
Korean
techno
logy
syste
mandob
servetheirdynamictre
nds
PCCA
Shen
andTzeng[58]
Explorethe
cause-effectrelationships
amon
gthea
ttributes
inthes
trong
decisio
nrulesa
ndprop
osea
mod
elfortacklingthev
alue
stock
selectionprob
lem
DRS
AFCA
Altu
ntas
andDereli
[59]
Establish
causalrelationships
amon
gtechno
logies
andprop
osea
napproach
forp
rioritizing
investmentp
rojectsfrom
theg
overnm
entrsquos
perspective
PCA
Thresholdvalue-
average
Shen
andTzeng[60]
Explorethe
complex
relationshipam
ongfin
ancialindicatorsandim
provefuturefi
nancial
perfo
rmance
oftheITindu
stry
VC-D
RSAFIS
Leea
ndLin[13]
Find
theinterrelationshipof
financialratio
sidentified
bymanagerso
fshipp
ingcompanies
and
financialexpertsa
ndcompare
theirc
ognitio
nmapsb
ycoun
tryandexpertgrou
pTh
resholdvalue-
MMDE
W-K
Tan
andY-J
Tan[61]
Analyze
howdifferent
factorsinteractand
collectively
contrib
utetothes
uccessfultransform
ation
anddiffu
sionof
thes
mart-c
ard-basede-micropaym
entm
ultip
urpo
sescheme
Azadehetal[12]
Evaluatetheimpactdegree
ofleannessfactorsa
ndpresentsac
omprehensiv
eapp
roachfor
evaluatin
gandop
timizingtheleann
essd
egreeo
forganizations
(lean
prod
uctio
n)
DEA
fuzzy
DEA
FCM
AHP
Thresholdvalue-
average
Sara
etal[14]
Assessrelativeimpo
rtance
andmutualinfl
uenceo
fbarrie
rsforc
arbo
ncapturea
ndsto
rage
deployment
AHP
Thresholdvalue-
average
Liaw
etal[62]
Analyze
theind
irectrelations
betweensubsystemsa
ndcompo
nentsa
ndprop
osea
reliability
allocatio
nmetho
dto
solvethe
fund
amentalproblem
sofcon
ventionalreliabilityappo
rtionm
ent
metho
dsME-OWA
Type
2interrelationships
andkeyfactors
AlaeiandAlro
aia[
63]
Identifyandprioritizethe
factorsa
ffectingandaffectedby
thep
erform
ance
ofsm
alland
medium
enterpris
es
Bacudioetal[64
]Analyze
cause-effectrelationships
ofbarriersto
implem
entin
gindu
stria
lsym
biosisnetworks
inan
indu
strialp
ark
Thresholdvalue-
averageinner
depend
ence
matrix
Balkovskayaa
ndFilneva[
65]
Identifycausalrelationships
betweenthek
eyevaluatio
nindicatorsof
bank
ingperfo
rmance
aswell
asdefin
ingthem
oststrategicallyim
portantind
icators
BSC
Threshold
value-second
quartile
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
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rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
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entcapabilityEKM
Cenvironm
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ared
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linearinteger
programmingLIP
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ordera
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onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
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ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Applied MathematicsJournal of
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AnalysisInternational Journal of
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Submit your manuscripts atwwwhindawicom
4 Mathematical Problems in Engineering
Table1Va
rious
applications
ofthec
lassicalDEM
ATEL
Papers
Research
purposes
Com
binatio
nsRe
marks
Type
1interrelationships
BEfea
ndOFE
fe[42]
Specify
theinfl
uenced
egrees
ofthep
atient
perceivedvalues
whenapplying
lean
health-care
managem
entinan
emergencydepartment
Thresholdvalue-
average
Malekzadehetal[43]
Investigatethe
causea
ndeffectrelations
forthe
dimensio
nsandcompo
nentso
forganizational
intelligenceinIranianpu
blicun
iversities
Thresholdvalue
Ranjan
etal[44
]Ad
dressthe
interrelationships
betweendifferent
evaluatio
ncriteria
ofIndian
Railw
ayzones
VIKOR
Thresholdvalue-
average
Tzengetal[10]
Addressthe
depend
entrelations
ofevaluatio
ncriteria
andprop
osea
hybrid
MCD
Mmod
elfor
evaluatin
gintertwined
effectsin
e-learning
programs
FAA
HPfuzzy
integral
Threshold
value-experts
Huetal[45]
Establish
thec
ausalrelationshipandextent
ofmutualimpactam
ongqu
ality
features
andpu
tforth
adecision
analysismetho
dology
toremovep
otentia
lproblem
sfrom
thec
onventionalIPA
mod
elBP
NN
Huetal[46
]Analyze
thec
ause-effectrelationshipam
ongdifferent
quality
characteris
ticstomaker
evision
sto
thetraditio
nalIPA
mod
elandfin
dthec
orep
roblem
sinvolvedwith
winning
orders
GAM
RA
Chengetal[47]
Explorethe
conn
ectio
nbetweenserviceq
ualityattributes
andthes
ervice
quality
improvem
ent
priorityof
fine-dining
restaurantsa
nduseitasa
referencefor
serviceq
ualitystr
ategyplanning
andresource
reorganizing
IPGA
Hsie
handYeh[48]
Exam
inec
ause
andeffectrela
tions
offactorsinfl
uencingthe
serviceq
ualityinfastfood
restaurants
Thresholdvalue-
average
Chiu
etal[49]
Analyze
relatio
nships
ofcusto
mer
buying
decisio
nfactorsa
ndprovidea
marketin
gstr
ategy
planning
forfi
rmsintheL
CD-TVmarket
Hoetal[50]
Analyze
thec
ause-effectrelationbetweenqu
ality
characteris
ticsa
ndbu
ildam
etho
dology
ofsupp
lierq
ualityperfo
rmance
assessmenttoim
proves
upplierq
ualitythroug
hop
timizing
order-winnersandqu
alifiers
IPAM
RA
Tsaietal[51]
Determinethe
causalrelationships
ofandinteractiveinfl
uencea
mon
gcriteria
andprop
osea
mixed
mod
elto
evaluatejobsatisfactionin
high
-tech
indu
strie
sIPA
Najmiand
Makui
[52]
Und
ersta
ndther
elationshipbetweencomparis
onmetric
sand
prop
osea
conceptualmod
elfor
measurin
gsupp
lychainperfo
rmance
AHP
Shafiee
etal[53]
Determinethe
relationships
betweenfour
perspectives
ofBS
Candprop
osea
napproach
toevaluatethep
erform
ance
ofsupp
lychain
DEA
BSC
Thresholdvalue-
average
ShaikandAb
dul-K
ader
[16]
Und
ersta
ndtheinterdepend
ence
amon
gperfo
rmance
factorsa
nddevelopar
everse
logistics
enterpris
eperform
ance
measurementm
odel
BSC
Innerd
ependence
matrix
Mathematical Problems in Engineering 5
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
LinandTzeng[11]
Determinethe
relatio
nshipbetweenthee
valuationcriteria
contrib
utingindu
stryclu
stersand
establish
theirv
alue
structuresa
ndbu
ildav
alue-created
syste
mof
science(techno
logy)p
ark
Threshold
value-experts
LinandSun[18]
Exam
inethe
impactso
fand
determ
inethe
relationships
amon
gdifferent
drivingforces
forthe
grow
thof
indu
strialcluste
rs
Threshold
value-expertsinner
depend
ence
matrix
WangandHsueh
[54]
Recogn
izethe
causalrelationships
betweendesig
nattributes
andmarketin
grequ
irementsand
prop
osea
napproach
toincorporatec
ustomer
preference
andperceptio
ninto
prod
uct
developm
ent
AHPKa
nomod
el
WangandSh
ih[55]
Identifytheimpactso
ffun
ctionalattributes
oncusto
mer
requ
irementsandpresenta
fram
ework
toincorporatec
ustomer
preferencesintoprod
uctd
evelo
pment
CA1QFD
TO
PSIS
Koetal[56]
Analyze
directandindirectim
pactsa
mon
gvario
ustechno
logy
areasa
ndpresenta
combined
approach
toconstructtechn
olog
yim
pactnetworks
forR
ampDplanning
usingpatents
SNA
Yoon
etal[57]
Assesstechno
logicalimpactsa
nddegree
ofcauseo
reffectam
ongtechno
logy
areasw
ithin
the
Korean
techno
logy
syste
mandob
servetheirdynamictre
nds
PCCA
Shen
andTzeng[58]
Explorethe
cause-effectrelationships
amon
gthea
ttributes
inthes
trong
decisio
nrulesa
ndprop
osea
mod
elfortacklingthev
alue
stock
selectionprob
lem
DRS
AFCA
Altu
ntas
andDereli
[59]
Establish
causalrelationships
amon
gtechno
logies
andprop
osea
napproach
forp
rioritizing
investmentp
rojectsfrom
theg
overnm
entrsquos
perspective
PCA
Thresholdvalue-
average
Shen
andTzeng[60]
Explorethe
complex
relationshipam
ongfin
ancialindicatorsandim
provefuturefi
nancial
perfo
rmance
oftheITindu
stry
VC-D
RSAFIS
Leea
ndLin[13]
Find
theinterrelationshipof
financialratio
sidentified
bymanagerso
fshipp
ingcompanies
and
financialexpertsa
ndcompare
theirc
ognitio
nmapsb
ycoun
tryandexpertgrou
pTh
resholdvalue-
MMDE
W-K
Tan
andY-J
Tan[61]
Analyze
howdifferent
factorsinteractand
collectively
contrib
utetothes
uccessfultransform
ation
anddiffu
sionof
thes
mart-c
ard-basede-micropaym
entm
ultip
urpo
sescheme
Azadehetal[12]
Evaluatetheimpactdegree
ofleannessfactorsa
ndpresentsac
omprehensiv
eapp
roachfor
evaluatin
gandop
timizingtheleann
essd
egreeo
forganizations
(lean
prod
uctio
n)
DEA
fuzzy
DEA
FCM
AHP
Thresholdvalue-
average
Sara
etal[14]
Assessrelativeimpo
rtance
andmutualinfl
uenceo
fbarrie
rsforc
arbo
ncapturea
ndsto
rage
deployment
AHP
Thresholdvalue-
average
Liaw
etal[62]
Analyze
theind
irectrelations
betweensubsystemsa
ndcompo
nentsa
ndprop
osea
reliability
allocatio
nmetho
dto
solvethe
fund
amentalproblem
sofcon
ventionalreliabilityappo
rtionm
ent
metho
dsME-OWA
Type
2interrelationships
andkeyfactors
AlaeiandAlro
aia[
63]
Identifyandprioritizethe
factorsa
ffectingandaffectedby
thep
erform
ance
ofsm
alland
medium
enterpris
es
Bacudioetal[64
]Analyze
cause-effectrelationships
ofbarriersto
implem
entin
gindu
stria
lsym
biosisnetworks
inan
indu
strialp
ark
Thresholdvalue-
averageinner
depend
ence
matrix
Balkovskayaa
ndFilneva[
65]
Identifycausalrelationships
betweenthek
eyevaluatio
nindicatorsof
bank
ingperfo
rmance
aswell
asdefin
ingthem
oststrategicallyim
portantind
icators
BSC
Threshold
value-second
quartile
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
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Cenvironm
entalsup
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pmentprogram
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alsoftw
ared
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pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Applied MathematicsJournal of
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Probability and StatisticsHindawiwwwhindawicom Volume 2018
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AnalysisInternational Journal of
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 5
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
LinandTzeng[11]
Determinethe
relatio
nshipbetweenthee
valuationcriteria
contrib
utingindu
stryclu
stersand
establish
theirv
alue
structuresa
ndbu
ildav
alue-created
syste
mof
science(techno
logy)p
ark
Threshold
value-experts
LinandSun[18]
Exam
inethe
impactso
fand
determ
inethe
relationships
amon
gdifferent
drivingforces
forthe
grow
thof
indu
strialcluste
rs
Threshold
value-expertsinner
depend
ence
matrix
WangandHsueh
[54]
Recogn
izethe
causalrelationships
betweendesig
nattributes
andmarketin
grequ
irementsand
prop
osea
napproach
toincorporatec
ustomer
preference
andperceptio
ninto
prod
uct
developm
ent
AHPKa
nomod
el
WangandSh
ih[55]
Identifytheimpactso
ffun
ctionalattributes
oncusto
mer
requ
irementsandpresenta
fram
ework
toincorporatec
ustomer
preferencesintoprod
uctd
evelo
pment
CA1QFD
TO
PSIS
Koetal[56]
Analyze
directandindirectim
pactsa
mon
gvario
ustechno
logy
areasa
ndpresenta
combined
approach
toconstructtechn
olog
yim
pactnetworks
forR
ampDplanning
usingpatents
SNA
Yoon
etal[57]
Assesstechno
logicalimpactsa
nddegree
ofcauseo
reffectam
ongtechno
logy
areasw
ithin
the
Korean
techno
logy
syste
mandob
servetheirdynamictre
nds
PCCA
Shen
andTzeng[58]
Explorethe
cause-effectrelationships
amon
gthea
ttributes
inthes
trong
decisio
nrulesa
ndprop
osea
mod
elfortacklingthev
alue
stock
selectionprob
lem
DRS
AFCA
Altu
ntas
andDereli
[59]
Establish
causalrelationships
amon
gtechno
logies
andprop
osea
napproach
forp
rioritizing
investmentp
rojectsfrom
theg
overnm
entrsquos
perspective
PCA
Thresholdvalue-
average
Shen
andTzeng[60]
Explorethe
complex
relationshipam
ongfin
ancialindicatorsandim
provefuturefi
nancial
perfo
rmance
oftheITindu
stry
VC-D
RSAFIS
Leea
ndLin[13]
Find
theinterrelationshipof
financialratio
sidentified
bymanagerso
fshipp
ingcompanies
and
financialexpertsa
ndcompare
theirc
ognitio
nmapsb
ycoun
tryandexpertgrou
pTh
resholdvalue-
MMDE
W-K
Tan
andY-J
Tan[61]
Analyze
howdifferent
factorsinteractand
collectively
contrib
utetothes
uccessfultransform
ation
anddiffu
sionof
thes
mart-c
ard-basede-micropaym
entm
ultip
urpo
sescheme
Azadehetal[12]
Evaluatetheimpactdegree
ofleannessfactorsa
ndpresentsac
omprehensiv
eapp
roachfor
evaluatin
gandop
timizingtheleann
essd
egreeo
forganizations
(lean
prod
uctio
n)
DEA
fuzzy
DEA
FCM
AHP
Thresholdvalue-
average
Sara
etal[14]
Assessrelativeimpo
rtance
andmutualinfl
uenceo
fbarrie
rsforc
arbo
ncapturea
ndsto
rage
deployment
AHP
Thresholdvalue-
average
Liaw
etal[62]
Analyze
theind
irectrelations
betweensubsystemsa
ndcompo
nentsa
ndprop
osea
reliability
allocatio
nmetho
dto
solvethe
fund
amentalproblem
sofcon
ventionalreliabilityappo
rtionm
ent
metho
dsME-OWA
Type
2interrelationships
andkeyfactors
AlaeiandAlro
aia[
63]
Identifyandprioritizethe
factorsa
ffectingandaffectedby
thep
erform
ance
ofsm
alland
medium
enterpris
es
Bacudioetal[64
]Analyze
cause-effectrelationships
ofbarriersto
implem
entin
gindu
stria
lsym
biosisnetworks
inan
indu
strialp
ark
Thresholdvalue-
averageinner
depend
ence
matrix
Balkovskayaa
ndFilneva[
65]
Identifycausalrelationships
betweenthek
eyevaluatio
nindicatorsof
bank
ingperfo
rmance
aswell
asdefin
ingthem
oststrategicallyim
portantind
icators
BSC
Threshold
value-second
quartile
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
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ared
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pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
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[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
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Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
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Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
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Volume 2018
Hindawiwwwhindawicom Volume 2018Volume 2018
Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
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Dierential EquationsInternational Journal of
Volume 2018
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AnalysisInternational Journal of
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Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom
6 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Chen
[66]
Estim
atethe
impo
rtance
ofthes
ervice
factorso
fanacadem
iclib
rary
andidentifythec
ausal
factors
Threshold
value-experts
GovindanandCh
audh
uri[67]
Analyze
ther
isksfaced
bythird
-partylogisticsservice
providersinrelationto
oneo
fitscusto
mers
andextractthe
causalrelationships
amon
gthem
Govindanetal[68]
Investigatethe
influ
entia
lstre
ngth
offactorso
nadop
tionof
greensupp
lychainmanagem
ent
practic
esin
theInd
ianminingindu
stry
AHP
Thresholdvalue-
average
Gandh
ietal[69]
Evaluatesuccessfactorsin
implem
entatio
nof
greensupp
lychainmanagem
entinIndian
manufacturin
gindu
strie
s
Hwangetal[70]
Explorethe
causalrelatio
nships
amon
gdecisio
nfactorsrelatingto
greensupp
lychains
inthe
semicon
ductor
indu
stry
Hwangetal[71]
Identifydeterm
inantsandtheirc
ausalrela
tionships
affectin
gthea
doptionof
cloud
compu
tingin
sciencea
ndtechno
logy
institutio
nsTh
reshold
value-120583+
32120590Hwangetal[20]
Assessthed
ynam
icris
kinterdependenciesfor
distinctprojectp
hasesa
ndidentifycriticalrisk
factors
Threshold
value-experts
Rahimniaa
ndKa
rgozar
[72]
Disc
over
causalrelationships
betweenob
jectives
inun
iversitystr
ategymap
andprioritizethem
forresou
rcea
llocatio
nBS
CTh
resholdvalue-third
quartile
Sekh
aretal[73]
Prioritizea
ndmap
thec
ausalrelationstr
ucturesindimensio
nsandsubd
imensio
nsof
HR-flexibilityandfirm
perfo
rmance
from
ITindu
stry
perspective
Seleem
etal[74]
Selectandmanagethe
suita
blep
erform
ance
improvem
entinitia
tives
toenhancethe
internal
processeso
fmanufacturin
gcompanies
BSC
TOC
Rank
basedon119877an
d119862
Sharmae
tal[75]
Assessthec
ausalrelationships
amon
glean
criteria
andidentifycriticalonesfor
thes
uccessful
implem
entatio
nof
lean
manufacturin
gTh
resholdvalue-
average
Shen
[76]
Identifythek
eybarriersandtheirinterrelationships
impeding
theu
niversity
techno
logy
transfe
rfro
mam
ultistakeho
lder
perspective
Thresholdvalue-third
quartile
Seyed-Hosseinietal[77]
Analyze
ther
elationbetweencompo
nentso
fasyste
mandprop
osea
metho
dology
for
reprioritizationof
failu
remod
esin
FMEA
Rank
basedon119877minus
119862Ch
ang[78]
Analyze
ther
elationshipbetweencompo
nentso
fasyste
mandou
tline
ageneralalgorithm
for
prioritizationof
failu
remod
esin
FMEA
OWGA
Rank
basedon119877minus
119862Ch
angetal[79]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
GRA
Rank
basedon119877minus
119862Ch
angetal[80]
Exam
inethe
directandindirectrelationships
betweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
TOPS
ISRa
nkbasedon119877minus
119862
Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Engineering Mathematics
International Journal of
Hindawiwwwhindawicom Volume 2018
Operations ResearchAdvances in
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Hindawiwwwhindawicom Volume 2018
Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
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Mathematical Problems in Engineering 7
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Liuetal[81]
Con
structthe
influ
entia
lrelations
amon
gfailu
remod
esandcauses
offailu
resa
nddevelopa
fram
eworkforp
rioritizationof
failu
remod
esAHPVIKOR
Mentese
tal[82]
Con
sider
thed
irect-in
directrelationships
betweenfactorsa
ndprop
osea
nintegrated
metho
dology
forrisk
assessmento
fcargo
shipsa
tcoasts
andop
enseas
OWGA
Huang
etal[8]
Identifymajor
indu
stry
inno
vatio
nrequ
irementsandpresentrecon
figured
inno
vatio
npo
licy
portfolio
stodevelopTaiwanrsquosSIPMallind
ustry
GRA
CA1
Threshold
value-experts
LiandTzeng[9]
Disc
over
andillustratethe
keyservices
needed
toattractSIP
usersa
ndSIPproviderstoan
SIP
Mall
Threshold
value-experts
Horng
etal[83]
Identifyther
elationships
andinteractions
amon
gdimensio
nsof
restaurant
spaced
esignfro
mthe
expertrsquosp
erspectiv
eTh
resholdvalue-
average
Chen
etal[84]
Determinec
riticalcore
factorsa
ffectingconsum
erintentionto
dine
atgreenrestaurantsa
nddevelopspecificimprovem
entstrategies
SEMQ
FD
Chengetal[85]
Develo
pathree-tiered
serviceq
ualityim
provem
entm
odelto
identifycritical
educational-service-qualitydeficienciesinho
spita
litytourism
and
leisu
reun
dergradu
ate
programs
IPGAQ
FD
Shiehetal[86]
Evaluatetheimpo
rtance
andconstructthe
causalrelatio
nsof
criteria
from
patientsrsquoview
points
andidentifykeysuccessfactorsforimprovingtheh
ospitalservice
quality
SERV
QUA
Lmod
elTh
resholdvalue-
average
Ranjan
etal[87]
Analyze
andexplaintheinteractio
nrelationships
andim
pactlevelsbetweenevaluatio
ncriteria
anddevelopaframew
orkforp
erform
ance
evaluatio
nof
engineeringdepartmentsin
auniversity
VIKOR
entro
pymetho
dTh
resholdvalue-
average
TanandKu
o[15]
Prioritizefacilitatio
nstrategies
ofruralp
arkandrecreatio
nagencies
from
thep
erspectiv
eof
leisu
reconstraints
Threshold
value-maxim
umvalue
Wuetal[88]
Describethe
contextualrelationships
evaluatedam
ongcriteria
andevaluatetheimpo
rtance
ofthe
criteria
used
inem
ploymentservice
outre
achprogram
person
nel
Thresholdvalue-
average
Sun[89]
Handlethe
innerd
ependencea
ndidentifycore
competences
ofnewlyqu
alified
nurses
Threshold
value-experts
WuandTsai[90]
Describethe
contextualrelatio
nships
amon
gthec
riteriaandevaluatetheimpo
rtance
ofdimensio
nscriteriain
auto
sparep
artsindu
stry
Thresholdvalue-
average
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
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entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
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metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
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pliers
FuzzyAHP
Defuzzification-
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d(T)
Fetanatand
Kho
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Interrelationships
Criteria
weights
Dealw
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ofcriteria
into
each
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ndprop
osea
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MCD
Mapproach
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rewindfarm
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election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
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Huetal[183]
Interrelationships
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Addressesthe
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and
developah
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Mmod
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improvem
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VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
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anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
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metho
dweights-
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leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
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enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
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fuzzy
ANP
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EMAT
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rocessD
ANPfuzzyw
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Cmultio
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ftechn
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UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
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[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
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[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
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[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Applied MathematicsJournal of
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Submit your manuscripts atwwwhindawicom
8 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Sun[91]
Identifyandanalyzec
riticalsuccessfactorsin
thee
lectronicd
esignautomationindu
stry
Threshold
value-experts
WuandTsai[92]
Depictthe
causalrelatio
nsandevaluatetheimpo
rtance
ofcriteria
inauto
sparep
artsindu
stry
AHP
Thresholdvalue-
average
Weietal[93]
Reprioritizethe
amendedmod
esin
theS
EMmod
elandestablish
acausalrelationshipmod
elfor
Web-advertisingeffects
Wuetal[24]
Explorethe
factorsh
inderin
gthea
cceptanceo
fusin
ginternalclo
udservices
inau
niversity
TAM
Four
quadrants
Hsu
[94]
Find
thed
eterminantfactorsinflu
encing
blog
desig
nandsim
plify
andvisualizethe
interrelationships
betweencriteria
fore
achfactor
FATh
reshold
value-experts
Hsu
andLee[95]
Explorethe
criticalfactorsinflu
encing
theq
ualityof
blog
interfa
cesa
ndthec
ausalrela
tionships
betweenthesefactors
Leee
tal[96]
Establish
thec
ausalrela
tionshipandthed
egreeo
finterrelationshipof
DTP
Bvaria
bles
(university
library
website)
Wuetal[23]
Explored
ecisive
factorsa
ffectingan
organizatio
nrsquosSoftw
area
saService(SaaS)a
doption
Four
quadrants
Pathariand
Sonar[97]
Analyze
asetof
securitysta
tementsin
inform
ationsecuritypo
licyproceduresand
controlsto
establish
anim
plicithierarchyandrelativ
eimpo
rtance
amon
gthem
Jafarnejad
etal[98]
Classifythec
riteriain
ERPselectioninto
thetwogrou
psof
ldquocauserdquoa
ndldquoeffectrdquoa
ndprop
osea
combinedMCD
Mapproach
toselectthep
roperE
RPsyste
m
Entro
pymetho
dfuzzy
AHP
TsaiandCh
eng[99]
Analyze
KPIsforE
-com
merce
andInternetmarketin
gof
elderly
prod
ucts
BSC
Wangetal[25]
Capturethe
causalrelationships
amon
gdivisio
nsandidentifythosed
ivision
swith
inam
atrix
organizatio
nthatmay
berespon
sibleforthe
poor
perfo
rmance
ofah
igh-tech
facilitydesig
nproject
SIA
Netinflu
ence
matrix
Linetal[100]
Explorethe
core
competences
andinvestigatetheircausea
ndeffectrela
tionships
oftheICdesig
nservicec
ompany
Threshold
value-experts
Chuang
etal[21]
Investigatethe
complex
multid
imensio
naland
dynamicnature
ofmem
bere
ngagem
entb
ehavior
inenvironm
entalprotectionvirtualcom
mun
ities
ISM
Threshold
value-expertsfour
quadrants
Rahm
anandSubram
anian[101]
Identifycriticalfactorsforimplem
entin
gEO
Lcompu
terrecyclin
gop
erations
inreverses
upply
chainandinvestigatethec
ausalrelationshipam
ongthefactors
Thresholdvalue-
average
Hsu
etal[102]
Recogn
izethe
influ
entia
lcriteriaof
carbon
managem
entingreensupp
lychainto
improvethe
overallp
erform
ance
ofsupp
liers
Thresholdvalue
Falatoon
itoosietal[103]
Exam
inec
omplex
causalrelationshipbetweenfactorsingreensupp
lychainmanagem
entand
providea
nevaluatio
nfram
eworkto
selectthem
osteligiblegreensupp
liers
Renetal[104]
Identifykeydrivingfactorsa
ndmap
theirc
ause-effectrelationships
fore
nhancing
the
susta
inabilityof
hydrogen
supp
lychain
Threshold
value-experts
Mud
uliand
Barve[105]
Extractthe
causalrelationships
amon
ggreensupp
lychainmanagem
entb
arrie
rsandestablish
asustainabled
evelop
mentframew
orkin
scaleInd
ianminingindu
strie
s
Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
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Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
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Engineering Mathematics
International Journal of
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Operations ResearchAdvances in
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Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
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Mathematical Problems in Engineering 9
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
WuandCh
ang[106]
Identifythec
riticaldimensio
nsandfactorstoim
plem
entg
reen
supp
lychainmanagem
entinthe
electricalandele
ctronicind
ustries
Thresholdvalue-
average
Behera
andMuk
herje
e[107]
Capturer
elationships
andanalyzek
eyinflu
encing
factorsrele
vant
toselectionof
supp
lychain
coordinatio
nschemes
Thresholdvalue-
MMDE
Ahm
edetal[108]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
fore
valuatingsustainableE
OLvehicle
managem
entalternatives
FuzzyAHP
Ahm
edetal[109]
Selectthem
ostimpo
rtantd
imensio
nsandcriteria
andprop
osea
nintegrated
mod
elfor
sustainableE
OLvehicle
managem
entalternatives
election
AHPfuzzyA
HP
Miaoetal[110
]Ev
aluatetheimpo
rtance
andun
veiltheimplicitinterrela
tionships
amon
gdifferent
scales
ofCP
Vandconstructa
multiscalemod
elforthe
measuremento
fCPV
ofEV
sHoQ
Threshold
value-expertsrank
basedon119877+
119862Lin[111]
Analyze
interactions
amon
gindu
stria
ldevelo
pmentfactorsandexploreh
owto
establish
the
competitivenesso
fsolar
photovoltaicindu
stry
Porterrsquos
Diamon
dmod
el
AzarnivandandCh
itsaz
[112]
Quantify
theinterlin
kagesa
mon
gfund
amentalanthrop
ogenicindicatorsandprop
osea
syste
maticapproach
forw
ater
shortage
mitigatio
nin
thea
ridregion
seD
PSIRA
HP
COPR
AS-G
Chen
etal[113]
Quantify
theinfl
uenceo
nPM
25by
otherfactorsin
thew
eather
syste
mandidentifythem
ost
impo
rtantfactorsforP
M25
RMFo
urqu
adrants
dosM
uchangos
etal[114
]As
sesstheb
arrie
rsto
mun
icipalsolid
wastemanagem
entp
olicyplanning
andidentifythem
ost
onerou
sbarrie
rsto
thee
ffectiveimplem
entatio
nof
thep
olicy
ISM
Netinflu
ence
matrix
Guo
etal[115]
EvaluateandinvestigategreencorporateC
SRindicatorsof
manufacturin
gcorporations
from
agreenindu
strylawperspective
Four
quadrants
Chen
andCh
i[116
]Ex
plorek
eyfactorso
fChinarsquosCS
Rfro
mthep
erspectiv
eofaccou
ntingexperts
Changetal[117
]Identifykeystr
ategicfactorsintheimplem
entatio
nof
CSRin
airline
indu
stry
Leee
tal[118]
Calculatethe
causalrelationshipandinteractionlevelbetweenTA
Mvaria
bles
andfin
dthec
ore
varia
bles
form
anagem
ento
rimprovem
entw
hileintro
ducing
anew
etchingplasmatechn
olog
yFo
urqu
adrants
Wu[119]
Determinethe
causalrelationships
betweentheK
PIso
fthe
BSCandlin
kthem
into
astrategy
map
forb
anking
institutio
nsBS
C
Chienetal[22]
Identifyrelatio
nships
betweenris
kfactorsa
ndassesscriticalrisk
factorsfor
BIM
projects
Four
quadrants
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
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Pglob
alsoftw
ared
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pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
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onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
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ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
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Volume 2018
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Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
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AnalysisInternational Journal of
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Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom
10 Mathematical Problems in Engineering
Table1Con
tinued
Papers
Research
purposes
Com
binatio
nsRe
marks
Wangetal[26]
Evaluatethep
erform
ance
ofdesig
ndelay
factorsa
ndidentifykeyfactorsthatd
rived
esigndelay
sof
afacilityconstructio
nproject
ISA
Netinflu
ence
matrix
Tzeng[19
]Investigatethe
relationshipbetweenfactorsa
ffectingparolebo
ardsrsquodecision
makingin
Taiwan
Simplified
norm
alized
total-relation
matrix
threshold
value
Gazibey
etal[120]
Analyze
thec
ause
andeffectrelations
amon
gthec
riteriaaffectin
gmainbattletankselection
Thresholdvalue-
average
Type
3interrelationships
andcriteria
weights
Khalili-D
amgh
anietal[121]
Determinethe
relativ
eimpo
rtance
weightsof
compensatoryob
jectivefun
ctions
andprop
osea
hybrid
multip
leob
jectivem
etaheuris
ticalgorithm
tosolveland-uses
uitabilityanalysisand
planning
prob
lem
AHP
Khazaietal[29]
Analyze
directandindirectdepend
encies
with
insocialandindu
stria
lvulnerabilityindicatorsand
developaframew
orkforspatia
lassessm
ento
find
ustrialand
socialvulnerabilityto
indirect
disaste
rlosses
Threshold
valuedepend
ency
weights
Tseng[122]
Resolvec
riteriainterdependencyrelationships
weightsandprop
osea
hybrid
metho
dto
evaluate
serviceq
ualityexpectationin
hotspringho
telrsquosrank
ingprob
lem
FuzzyTO
PSIS
Innerd
ependence
matrix
Quadere
tal[123]
Determinethe
causea
ndeffectrelationships
amon
gcriteria
andevaluatethec
riticalcriteria
for
CO2capturea
ndsto
rage
intheironandste
elindu
stry
Criteria
weights-
vector
leng
thth
reshold
value
Quadera
ndAhm
ed[124]
Identifycriticalfactorsfore
valuatingalternativeiron-makingtechno
logies
with
carbon
capture
andsto
rage
syste
ms
FuzzyAHP
Criteria
weights-
vector
leng
thth
reshold
value
Seyedh
osseinietal[17]
Identifythec
ause
andeffectrela
tionships
amon
glean
objectives
andprop
osed
asystematicamp
logicalm
etho
dfora
utopartmanufacturersto
determ
inethe
companyrsquoslean
strategymap
BSC
Innerd
ependence
matrix
weights-119877+
119862Cebi[27]
Determineimpo
rtance
degreeso
fwebsited
esignparametersb
ased
oninteractions
andtypeso
fwebsites
Thresholdvalue-
averagedeterm
ining
weightsusing119877+
119862Yazdani-C
hamzini
etal[28]
Analyze
interdependencea
nddepend
encies
andcompu
tetheg
lobalw
eightsfore
valuation
indicatorsandprop
osea
newhybrid
mod
elto
selectthes
trategyof
investingin
apriv
ates
ector
AHPfuzzy
TOPS
IS
Thresholdvalue-
expertsweights-119877+
119862No
teB
ackpropagatio
nneuralnetworkBP
NNbalancedscorecardBS
Cbu
ildinginformationmod
elingBIMcluste
ranalysisC
A1conjoint
analysis
CA2corporatesocialrespo
nsibilityC
SRcustomerperceived
valueCP
Vdata
envelopm
enta
nalysis
DEA
decom
posedtheory
ofplannedbehaviorD
TPB
dominance-based
roug
hseta
pproach
DRS
Aelectric
vehicle
EV
enhanced
drivingforce-pressure-state-im
pact-
respon
seeDPS
IRenterprise
resource
planning
ERP
end
-of-lifeE
OLfactor
analysis
FAfailure
mod
eand
effectanalysisFMEA
fuzzy
cogn
itive
mapFCM
fuzzy
inferences
ystemFISformalconceptanalysis
FC
Agap
analysis
GAgreyc
omplex
prop
ortio
nalassessm
entCO
PRAS-Ggreyr
elationalanalysisG
RAhou
seso
fqualityHoQ
impo
rtance-perform
ance
analysis
IPAimpo
rtance-perform
ance
andgapanalysis
IPGAimpo
rtance-satisfactio
nanalysis
ISAinformationtechno
logyITinterpretiv
estructuralm
odeling
ISM
integratedcircuitICkey
perfo
rmance
indicatorKP
Imaxim
alentro
pyorderedweightedaveraging
ME-OWAm
ultip
leregressio
nanalysis
MRA
ordered
weightedgeom
etric
averagingOWGApatentcitatio
nanalysis
PCApatentcoclassificatio
nanalysis
PCCA
relationmapR
Msatisfi
edim
portance
analysis
SIAsiliconintellectualp
ropertyor
Semicon
ductor-Intellectual-P
ropertySIP
socialnetworkanalysis
SNAstructuralequ
ationmod
elingSE
Mtechn
olog
yacceptance
mod
elTA
Mtheoryof
constraintsTO
Cvaria
blec
onsis
tencyDRS
AV
C-DRS
A
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
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2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
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2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
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imensio
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securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
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drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
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2no
rmalization
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Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
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res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
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fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
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valuationcriteria
and
prop
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fuzzymod
elforsup
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Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
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Defuzzification-
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Interrelationships
Criteria
weights
Recogn
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ystems
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A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
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elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
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Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
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ofcriteria
into
each
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ndprop
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Mapproach
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Defuzzification-Yager
rank
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Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
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developah
ybrid
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Mmod
elto
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commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
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distance
metho
dweights-
vector
leng
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Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
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expertsweights-
fuzzy
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rocessD
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onM
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Cmultio
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makingMODMunifiedtheory
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Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 11
I
0
II
IVIII
Prominence
Rela
tion
Mean
R minus C
R + C
Figure 2 Four-quadrant IRM
Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making
In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]
Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which
Net119894119895 = 119905119894119895 minus 119905119895119894 (8)
Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]
119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)
I
0
II
IVIII
Cause factors ofperceived benefits
Cause factors ofperceived risks
Effect factors ofperceived benefits
Effect factors ofperceived risks
R minus C
R + C
Figure 3 The PB-PR matrix
To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria
119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)
where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by
119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im
119894 times 119908119889119894 (11)
where 119908im119894 is the importance weight of the 119894th criterion
assigned by a group of experts
312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods
In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative
12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
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Pglob
alsoftw
ared
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pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
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comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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12 Mathematical Problems in Engineering
should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations
On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods
313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their
dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]
32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following
321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]
Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale
In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885
After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by
119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1
119896119894119895= (1119897
119897sum119896=1
1199111198961198941198951 1119897119897sum119896=1
1199111198961198941198952 1119897119897sum119896=1
1199111198961198941198953) (12)
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 13
Table2Va
rious
applications
offuzzyDEM
ATEL
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Fuzzylogica
ndDEM
ATEL
Kuo[125]
Interrelationships
Con
structa
suitablee
valuationstructureb
etweencriteria
andprop
osea
hybrid
metho
dforo
ptim
allocatio
nselectionfora
ninternational
distrib
utioncenter
AHPANPfuzzy
TOPS
ISfuzzy
measure
Defuzzification-
CFCS
threshold
value-average
Altu
ntas
etal[126]
Interrelationships
Find
thec
losenessratin
gsbetweenthefacilitie
sand
prop
osea
fuzzy
approach
forfacilitylayout
prob
lem
Defuzzification-CF
CS
Altu
ntas
andYilm
az[127]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectfactorsof
marketin
gresourcesa
ndprioritizethem
forsmall-andmedium-sized
enterpris
es
Defuzzification-
CFCS
threshold
value-average
Kabaketal[128]
Interrelationships
Keyfactorscriteria
Determinec
riticalsuccessfactorsshapingthec
ompetitivenesslevelof
theironandste
elindu
stryin
Turkey
Defuzzification-CF
CS
Luthra
etal[129]
Interrelationships
Keyfactorscriteria
Evaluatethee
nablersinsolarp
ower
developm
entsin
inIndiarsquos
current
scenario
Defuzzification-
bisectionof
area
WuandLee[130]
Interrelationships
Keyfactorscriteria
Prop
osea
metho
dto
segm
entrequiredcompetenciesfor
prom
otingthe
competencydevelopm
ento
fglobalm
anagers
Defuzzification-CF
CS
Liou
etal[131]
Interrelationships
Keyfactorscriteria
Map
outthe
structuralrelations
andidentifykeyfactorsa
nddevelopa
metho
dforb
uildingan
effectiv
esafetymanagem
entsystem
fora
irlines
Defuzzification-
COAth
reshold
value-experts
Tseng[132]
Interrelationships
Keyfactorscriteria
Integrateh
otelserviceq
ualityperceptio
nsinto
acause-effectmod
elfor
assessingcharacteris
ticsc
riteriaof
serviceq
ualitymeasurement
Defuzzification-
CFCS
innerd
ependence
matrix
TsengandLin[133]
Interrelationships
Keyfactorscriteria
Handler
elatio
nsbetweencausea
ndeffecto
fcriteriaanddevelopac
ause
andeffectm
odelof
mun
icipalsolid
wastemanagem
ent
Defuzzification-
CFCS
innerd
ependence
matrix
Changetal[134]
Interrelationships
Keyfactorscriteria
Evaluatesupp
lierp
erform
ance
tofin
dinflu
entia
lcriteriain
selecting
supp
liers
Defuzzification-CF
CS
ChangandCh
eng[135]
Interrelationships
Keyfactorscriteria
Analyze
ther
elationbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
napproach
torank
ther
iskof
failu
res
FuzzyOWA
Defuzzification-
maxim
umdegree
ofmem
bership
Zhou
etal[136]
Interrelationships
Keyfactorscriteria
Analyze
causalrelationships
andidentifykeysuccessfactorsfor
improvingtheo
verallem
ergencymanagem
ent
Defuzzification-CF
CS
Tsengetal[137]
Interrelationships
Keyfactorscriteria
Handlethe
intertwiningwith
inas
etof
criteria
andprovidea
nintegrated
serviceq
ualityexpectationmod
elforimprovingho
tspringmanagem
ent
Innerd
ependence
matrix
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Applied MathematicsJournal of
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Submit your manuscripts atwwwhindawicom
14 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Tseng[138]
Interrelationships
Keyfactorscriteria
Handlethe
innerd
ependencew
ithin
decisio
ncriteria
ofEK
MCand
developam
odelfore
valuatingthefi
rmEK
MCcapacity
Defuzzification-
CFCS
innerd
ependence
matrix
Wu[139]
Interrelationships
Keyfactorscriteria
Segm
entthe
criticalfactorsforsuccessfulkno
wledgem
anagem
ent
implem
entatio
nsDefuzzification-CF
CS
Lin[14
0]Interrelationships
Keyfactorscriteria
Exam
inethe
causea
ndeffectrelationships
amon
gcriteria
andform
astructuralmod
elto
evaluategreensupp
lychainmanagem
entp
ractices
Defuzzification-
CFCS
innerd
ependence
matrix
Patil
andKa
nt[14
1]Interrelationships
Keyfactorscriteria
Identifycriticalsuccessfactorso
fkno
wledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-graded
mean
Rouh
anietal[14
2]Interrelationships
Keyfactorscriteria
Evaluateandassessthec
riticalfactorsinER
Pprojectimplem
entatio
nFu
zzyAHP
Defuzzification-CF
CS
Wuetal[143]
Interrelationships
Keyfactorscriteria
Identifycriticalfactorsinflu
encing
theu
seof
additiv
esby
food
enterpris
esin
China
Defuzzification-
CFCS
threshold
value-qu
artile
Zhou
etal[144]
Interrelationships
Keyfactorscriteria
Measure
ther
elatio
nships
amon
gdifferent
factorsa
nddevelopar
oot
caused
egreep
rocedu
reform
easurin
gintersectio
nsafetyfactors
Defuzzification-CF
CS
Dou
etal[145]
Interrelationships
Keyfactorscriteria
Exam
inethe
cause-effectinterrelationships
amon
gES
DPs
andprop
oses
amod
elforfocalcompanies
toevaluateES
DPs
Fuzzyscoringmetho
dDefuzzification-CF
CS
Govindanetal[146]
Interrelationships
Keyfactorscriteria
Evaluatethed
riverso
fcorpo
ratesocialrespon
sibilityim
plem
entatio
nin
them
iningindu
stry
Defuzzification-centroid
metho
d
RoutroyandSunilK
umar
[147]
Interrelationships
Keyfactorscriteria
Identifyandestablish
relatio
nshipam
ongvario
ussupp
lierd
evelo
pment
program
enablersin
aspecific
manufacturin
genvironm
ent
Defuzzification-
CFCS
threshold
value-average
Tyagietal[14
8]Interrelationships
Keyfactorscriteria
Assesscriticalenablersfor
flexibles
upplychainperfo
rmance
measurementsystem
Defuzzification-
CFCS
threshold
value-average
Wuetal[149]
Interrelationships
Keyfactorscriteria
Identifyinteractions
amon
gthesec
riteriaandexplored
ecisive
factorsin
greensupp
lychainpractic
es
Defuzzification-
CFCS
innerd
ependence
matrix
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 15
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Sang
aiah
etal[150]
Interrelationships
Keyfactorscriteria
Criteria
weights
EvaluateGSD
projecto
utcomefactorsandfin
dthes
ignificance
ofcriteria
inorganizatio
nalbehaviorresearchph
enom
enon
TOPS
ISDefuzzification-
CFCS
weights-
vector
leng
th
Malviya
andKa
nt[151]
Interrelationships
Criteria
weights
Predictand
measure
thes
uccesspo
ssibilityof
greensupp
lychain
managem
entimplem
entatio
nDefuzzification-
CFCS
weights-119877+
119862Patil
andKa
nt[152]
Interrelationships
Criteria
weights
Evaluatewe
ightingof
criteria
andprop
osea
predictio
nfram
eworkfor
know
ledgem
anagem
entado
ptionin
supp
lychain
Defuzzification-
CFCS
weights-119877+
119862Sang
aiah
etal[153]
Interrelationships
Criteria
weights
Presentanintegrated
fram
eworkto
evaluatekn
owledgetransfer
effectiv
enessw
ithreferencetoGSD
projecto
utcome
TOPS
ISE
LECT
REDefuzzification-
CFCS
weights-119877+
119862Ba
keshlouetal[154]
Interrelationships
Criteria
weights
Und
ersta
ndtheinterrelatio
nam
ongcriteria
andprop
osea
hybrid
MODM
algorithm
forg
reen
supp
liersele
ction
FuzzyANPfuzzy
MOLP
Defuzzification-
CFCS
weights-
fuzzy
ANP
Fuzzy-basedDEM
ATEL
Jassbietal[155]
Interrelationships
Capturethe
causalrelatio
nships
betweenstr
ategicob
jectives
fora
strategymap
BSC
Defuzzification-CO
G
Leee
tal[156]
Interrelationships
Reanalyzea
ndexplainthec
ausalrela
tionshipandlevelofm
utualeffect
betweenvaria
bles
inTA
M
Defuzzification-
CFCS
(T)threshold
value
Valm
oham
madiand
Sofiyabadi[157]
Interrelationships
Analyze
thec
ausesa
ndeffectsrelatio
nsof
strategy
map
anddevelopa
strategymap
fora
nautomotiveind
ustry
BSC
Defuzzification-
CFCS
2no
rmalization
andaggregation
Youn
esiand
Rogh
anian[158]
Interrelationships
Assumethe
interdependenceo
fcustomer
attributes
andprop
osea
fram
eworkforsustainableprod
uctd
esign
QFD
fuzzy
ANP
Defuzzification-
centroid
metho
dthreshold
value-fuzzyMMDE
16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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16 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
LinandWu[159]
Interrelationships
Keyfactorscriteria
Prop
osea
causalanalyticalmetho
dforg
roup
decisio
nmakingun
der
fuzzyenvironm
entand
applieditforR
ampDprojectsele
ction
Defuzzification-
CFCS
2no
rmalization
andaggregation
Fekrietal[160]
Interrelationships
Keyfactorscriteria
Identifythec
ause
andeffectg
roup
sofcriticalsuccessfactorsof
agile
newprod
uctd
evelo
pmentp
rocess
Explanatoryfactor
analysis
Defuzzification-
CFCS
2no
rmalization
andaggregation
Jeng
andTzeng[161]
Interrelationships
Keyfactorscriteria
Explorethe
causalrelatio
nshipbetweenUTA
UTvaria
bles
andexam
ine
socialinflu
ence
ontheu
seof
clinicald
ecision
supp
ortsystem
Defuzzification-CF
CS(T)threshold
value-experts
Chou
etal[162]
Interrelationships
Keyfactorscriteria
Establish
contextualrelationships
amon
gcriteria
andevaluatethe
criteria
forh
uman
resource
forscience
andtechno
logy
FuzzyAHP
Defuzzification-
CFCS
2no
rmalization
andaggregation
Afsharkazem
ietal[163]
Interrelationships
Keyfactorscriteria
Measure
directandindirectrelationships
betweenfactorsa
ndidentify
keyfactorsa
ffectingtheh
ospitalp
erform
ance
Defuzzification-
centroid
metho
dno
rmalization
andaggregation
RenandSovacool[164
]Interrelationships
Keyfactorscriteria
Identifycause-effectrelationships
amon
genergy
securitymetric
sto
determ
inethe
mostsalient
andmeaning
fuld
imensio
nsandenergy
securitystr
ategies
Defuzzification-CF
CS2
Akyuz
andCelik[165]
Interrelationships
Keyfactorscriteria
Evaluatecriticaloperatio
nalh
azards
durin
ggasfreeing
processincrud
eoiltankers
Defuzzification-CO
A
Tsao
andWu[166]
Interrelationships
Keyfactorscriteria
Evaluatethec
ause-effectrelatio
nshipof
complex
drillingprob
lemsfor
compo
undspecial-c
ored
rillin
gcompo
sitem
aterials
Defuzzification-
CFCS
2no
rmalization
andaggregation
Hoetal[167]
Interrelationships
Keyfactorscriteria
Analyze
thec
ause-effectrelationshipandthem
utualinfl
uenceo
finform
ationsecuritycontrolitemsa
ndidentifycore
controlitemsfor
inform
ationsecuritymanagem
entand
improvem
entstrategies
Defuzzification-
CFCS
2threshold
value
Jeng
[168]
Interrelationships
Keyfactorscriteria
Prob
ethe
relatio
nships
amon
gkeydimensio
nsin
supp
lychain
collabo
ratio
nto
enablebette
rstrategicdevelopm
ento
fmanufacturin
gfirms
Defuzzification-CF
CS(T)
Liuetal[169]
Interrelationships
Keyfactorscriteria
Analyze
ther
elatio
nsbetweenfailu
remod
esandcauses
offailu
reand
prop
osea
riskassessmentm
etho
dology
torank
ther
iskof
failu
res
FWA
Defuzzification-graded
mean
Panaihfare
tal[170]
Interrelationships
Keyfactorscriteria
Explorethe
keyfactorsinretailersele
ctionforc
ollabo
rativ
eplann
ing
forecastingandreplenish
mentand
ther
elatio
nships
betweenthese
factors
Defuzzification-
COAth
reshold
value-averageo
fpositive
119877minus119862
Hsu
etal[171]
Interrelationships
Criteria
weightsKe
yfactorscriteria
Find
t hek
eyfactorsinbu
ildingthes
tructure
relations
ofan
ideal
custo
merrsquoschoice
behavior
andprop
osea
fram
eworkform
arketin
gstrategicp
lann
ing
FuzzyANPfuzzy
AHP
Thresholdvalue-average
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 17
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
Cebi[172]
Interrelationships
Criteria
weights
Keyfactorscriteria
Determinec
riticaldesig
ncharacteris
ticso
fwebsites
basedon
interactions
amon
gthem
andpresentanintegrated
metho
dology
toevaluatethep
erceived
desig
nqu
ality
ofshop
ping
websites
Choq
uetintegral
Defuzzification-
centroid
metho
dweights-
119877+119862th
reshold
value
Gigovicetal[173]
Interrelationships
Criteria
weights
Evaluateland
suitabilityforthe
developm
ento
fecotourism
inther
egion
ofldquoD
unavskiK
ljucrdquo
Weights-
vector
leng
th
Jeon
getal[174]
Interrelationships
Criteria
weights
Identifyruralh
ousin
gsrsquosuitables
itesinreservoira
reas
under(mass)
tourism
Weights-
vector
leng
th
Rahimdeland
Bagh
erpo
ur[175]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
degree
ofcriteria
forthe
haulages
ystem
selectionforo
penpitm
ines
FuzzyTO
PSIS
Dalalah
etal[176]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uentialrelationshipbetweenthee
valuationcriteria
and
prop
osea
hybrid
fuzzymod
elforsup
pliersele
ction
Defuzzificationweights-
vector
leng
thnormalization
andaggregation
Hieteetal[177]
Interrelationships
Criteria
weights
Analyze
andcorrectfor
relations
betweenvaria
bles
inac
ompo
site
indicatorfor
disaste
rresilience
Dependency
weights
threshold
value-graphicalm
etho
d
WangandCh
en[178]
Interrelationships
Criteria
weights
Derivethe
prioritieso
ftechn
icalattributes
anddevelopafuzzy
MCD
MbasedQFD
toassis
tanenterpris
efor
collabo
rativ
eprodu
ctdesig
nQFD
LIP
Defuzzification-
centroid
metho
d(T)
Wang[179]
Interrelationships
Criteria
weights
Recogn
izethe
causalities
betweenmarketin
grequ
irementsandtechnical
attributes
andprop
osea
napproach
tocond
uctvendo
rassessm
entfor
busin
ess-intelligences
ystems
QFD
fuzzy
AHP
Defuzzification-CO
A(T)weights-|119877minus
119862|Ba
ykasoglu
etal[180]
Interrelationships
Criteria
weights
Evaluatethew
eightsof
thec
riteriaandprop
osea
mod
elforsolving
truckselectionprob
lem
ofalandtransportatio
ncompany
FuzzyTO
PSIS
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
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[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
18 Mathematical Problems in Engineering
Table2Con
tinued
Papers
Categorie
sRe
search
purposes
Com
binatio
nsRe
marks
WangandWu[181]
Interrelationships
Criteria
weights
Identifythed
ependencea
mon
gevaluatio
nfactorsa
ndprop
osea
fram
eworkto
evaluateprogrammablelogicc
ontro
llersup
pliers
FuzzyAHP
Defuzzification-
centroid
metho
d(T)
Fetanatand
Kho
rasaninejad[182]
Interrelationships
Criteria
weights
Dealw
iththeinfl
uences
ofcriteria
into
each
othera
ndprop
osea
hybrid
MCD
Mapproach
foro
ffsho
rewindfarm
sites
election
FuzzyANPfuzzy
ELEC
TRE
Defuzzification-Yager
rank
ingmetho
d(T)innerd
ependence
matrix
Huetal[183]
Interrelationships
Criteria
weights
Addressesthe
interdependencea
ndfeedback
effectsbetweencriteria
and
developah
ybrid
MCD
Mmod
elto
improvem
obile
commerce
adop
tion
FuzzyDANPfuzzy
VIKOR
Weights-
fuzzy
DANPfuzzyIRM
Keskin
[184]
Interrelationships
Criteria
weights
Analyze
theinteractio
nsbetweencriteria
anddeterm
inetheirweights
forsup
pliere
valuationandselection
Fuzzyc-means
algorithm
Defuzzification-sig
ned
distance
metho
dweights-
vector
leng
th
Pamucar
andCirovic[185]
Interrelationships
Criteria
weights
Obtainthew
eightcoefficientsof
criteria
andpresenta
mod
elforthe
selectionof
transportand
hand
lingresourcesinlogisticsc
enters
MABA
CDefuzzification-graded
mean(T)weights-
vector
leng
th
Taskin
etal[186]
Interrelationships
Criteria
weights
Determinethe
impo
rtance
weightsof
evaluatio
ncriteria
andprop
osea
fram
eworkfore
valuatingtheh
ospitalservice
quality
FuzzyANPVIKOR
Defuzzification-CF
CS(T)thresholdvalue-
expertsweights-
fuzzy
ANP
NoteD
EMAT
EL-based
analyticnetworkp
rocessD
ANPfuzzyw
eightedaverageFW
Aenviro
nmentalpracticesinkn
owledgem
anagem
entcapabilityEKM
Cenvironm
entalsup
plierd
evelo
pmentprogram
ESD
Pglob
alsoftw
ared
evelo
pmentGSD
linearinteger
programmingLIP
multiattributiveb
ordera
pproximationarea
comparis
onM
ABA
Cmultio
bjectiv
edecision
makingMODMunifiedtheory
ofacceptance
and
useo
ftechn
ologyUTA
UT
Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering 19
Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885
Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]
Step 4 Apply the classical DEMATEL approach to
(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM
From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]
Step 1 Evaluate the relationships between factors using fuzzylinguistic scale
Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by
119883 = 119885119903 (13)
where
119883 =[[[[[[[
11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d
1199091198991 1199091198992 sdot sdot sdot 119909119899119899
]]]]]]] (14)
119903 = max1le119894le119899
( 119899sum119895=1
1199111198941198953) (15)
At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual
direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]
119903 = max119894119895
[[max1le119894le119899
( 119899sum119895=1
1199111198941198953) max1le119895le119899
( 119899sum119894=1
1199111198941198953)]] (16)
Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by
= limℎrarrinfin
(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim
ℎrarrinfin119883ℎ = 119874 (17)
Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1
(18)
in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM
Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def
In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique
Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India
20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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20 Mathematical Problems in Engineering
323 Observations and Findings
(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies
The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]
Step 1 Normalization of the fuzzy numbers
1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)
1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)
1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)
Step 2 Compute left and right normalized values
119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)
119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)
Step 3 Compute total normalized crisp value
119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)
Step 4 Compute crisp values
119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)
Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by
119911119894119895 = 1119897119897sum119896=1
119911119896119894119895 (26)
In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]
119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)
where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center
of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations
119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063
(28)
In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts
119910 = 119897 + 2119898 + 1199064 (29)
119910 = 119897 + 4119898 + 1199066 (30)
119910 =
119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise
(31)
(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped
The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula
120596119894 = [(def119894 + 119862def
119894 )2 + (def119894 minus 119862def
119894 )2]12 (32)
Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering 21
Then theweight of any criterion can be normalized as follows
119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)
Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values
119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)
Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion
Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria
33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them
Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector
Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina
Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods
It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given
Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
22 Mathematical Problems in Engineering
Table3Ap
plications
ofgrey
DEM
ATEL
Papers
Research
purposes
Extensions
Remarks
Fuetal[187]
Evaluategreensupp
lierd
evelo
pmentp
rogram
sand
theirrelationships
toeach
other
andim
portance
forthe
organizatio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Dou
andSarkis[188]
Evaluatetheb
arrie
rsof
implem
entin
gCh
inaR
oHSregu
lations
from
amultip
lesta
keho
lder
perspective
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583di
stance
between
respon
dents
Zhuetal[189]
Exam
inethe
causal-effectrelatio
nships
amon
gtheimplem
entatio
nbarriersand
identifysupp
lychain-basedbarriersfortruck-eng
iner
emanufacturin
gin
China
Greytheory
andDEM
ATEL
CFCS
threshold
value-120583+
2120590distance
betweenrespon
dents
Rajesh
andRa
vi[19
0]Find
outcauseeffectrelationships
andascertainthem
ajor
enablersof
supp
lychain
riskmitigatio
nin
electro
nics
upplychains
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
15120590Shao
etal[191]
Visualizethe
prioritizationandinterrela
tionships
oftheb
arrie
rsbetween
environm
entally
friend
lyprod
uctsandtheirc
onsumerso
ntheE
urop
ean
automob
ileindu
stry
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Govindanetal[192]
Identifyim
portantcriteriaforthird-partylogisticsp
roviderselectio
nGreytheory
andDEM
ATEL
Mod
ified
CFCS
inner
depend
ence
matrix
Xiae
tal[19
3]Analyze
internalbarriersforrem
anufacturersin
thea
utom
otives
ectora
ndidentify
thec
ausalinternalbarrie
rsin
theC
hinese
automotives
ector
Greytheory
andDEM
ATEL
Mod
ified
CFCS
threshold
value-120583+
120590Ba
iand
Sarkis[19
4]Ev
aluatebu
sinessp
rocessmanagem
ent(BP
M)criticalsuccessfactorsto
aidproject
managersm
akep
roperB
PMinvestmentstrategies
GreyDEM
ATEL
Thresholdvalue-120583+
120590Liangetal[195]
Identifycriticalsuccessfactorsfor
sustainabled
evelo
pmento
fbiofuelindu
stry
inCh
ina
GreyDEM
ATEL
Tseng[19
6]Re
solveinterdepend
ency
relationships
amon
gcriteria
andpresenta
perceptio
napproach
todealwith
realestateagentservice
quality
expectationrank
ing
Grey-fuzzyDEM
ATEL
Innerd
ependencem
atrix
Suetal[197]
Identifyaspectso
fand
criteria
forsup
plierp
rioritizationandprop
osea
hierarchical
metho
dforimprovingsusta
inablesupp
lychainmanagem
ent
HierarchicalgreyDEM
ATEL
Ozcan
andTu
ysuz
[198]
Determinethe
impo
rtance
ofperfo
rmance
indicatorsandprop
osea
metho
dforthe
perfo
rmance
evaluatio
nof
retailsto
res
Grey-basedDEM
ATEL
Mod
ified
CFCS
Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering 23
Table4Ap
plications
ofotherD
EMAT
EL
Papers
Categorie
sRe
search
purposes
Extensions
Remarks
Jenabetal[199]
Interrelationships
Keyfactors
Prop
osea
syste
maticmetho
dfore
valuatingandselectingcompu
ter
integrated
manufacturin
g(C
IM)techn
ologiestakinginto
accoun
tmanagem
ento
bjectiv
esIntervalDEM
ATEL
Rank
basedon119877minus
119862Ab
dullahandZu
lkifli[200]
Interrelationships
Keyfactors
Capturethe
complex
relationships
amon
gdimensio
nsandcriteria
and
prop
osea
nintegrationmetho
dforh
uman
resourcesm
anagem
ent
IT2-fuzzyDEM
ATEL
fuzzyAHP
Defuzzification-
expected
value(T)
NikjooandSaeedp
oor[201]
Interrelationships
Keyfactors
Dealw
iththec
ausalrelationships
amon
gfactorsa
ndprop
osea
metho
dology
forp
rioritizingthec
ompo
nentso
fSWOTmatrix
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Govindanetal[202]
Interrelationships
Keyfactors
Handlethe
impo
rtantand
causalrelationships
betweengreensupp
lychain
managem
ent(GSC
M)p
ractices
andfin
dthem
ainpractices
toim
prove
environm
entaland
econ
omicperfo
rmances
IFS(ITF
N)a
ndDEM
ATEL
Defuzzification-
expected
valueinner
depend
ence
matrix
Fanetal[203]
Interrelationships
Keyfactors
Exam
inethe
interrelationships
amon
gther
iskfactorso
fITou
tsou
rcing
andidentifytheimpo
rtance
together
with
thec
lassificatio
nof
riskfactors
2-tuplea
ndDEM
ATEL
Liuetal[204]
Interrelationships
Criteria
weight
Obtainther
elativew
eightsof
criteria
andprop
osea
hybrid
MCD
Mfor
evaluatin
ghealth-carew
astetre
atmenttechn
ologies
2-tuplea
ndDEM
ATEL
fuzzyMULT
IMOORA
Criteria
weights-
vector
leng
th
Suoetal[205]
Interrelationships
Keyfactors
Dealw
ithcorrelated
factor
analysisprob
lemsu
singun
certainlin
guistic
term
sand
extend
thec
lassicalDEM
ATEL
metho
dto
anun
certain
linguisticenvironm
ent
Uncertain
linguistic
DEM
ATEL
Defuzzification-CO
G
Lietal[206]
Interrelationships
Keyfactors
Identifycriticalsuccessfactorsinem
ergencymanagem
ent
Evidentia
lDEM
ATEL
(D-S
theory
andIFS)
ChangandCh
eng[207]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
IFSandDEM
ATEL
Defuzzification-
centroid
metho
drank
basedon119877minus
119862Ch
ang[208]
Interrelationships
Keyfactors
Analyze
ther
elatio
nships
betweencompo
nentso
fasyste
mandou
tline
ageneralalgorith
mforp
rioritizationof
failu
remod
esin
FMEA
Softsetand
DEM
ATEL
Rank
basedon119877minus
119862GengandCh
u[209]
Interrelationships
Criteria
weights
Con
sider
them
utualinfl
uencer
elationships
amon
gattributes
andprop
ose
anew
impo
rtance-perform
ance
analysis(IPA
)app
roachforc
ustomer
satisfactionevaluatio
n
VagueD
EMAT
ELK
ano
mod
elDefuzzification-average
Wuetal[210]
Interrelationships
Criteria
weights
Analyze
theinterrelationships
amon
gcusto
mer
requ
irementsandprop
ose
anintegrated
analyticalmod
elforq
ualityfunctio
ndeployment(QFD
)Hesitant
fuzzy
DEM
ATEL
Criteria
weights-
vector
leng
th
24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
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Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
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Engineering Mathematics
International Journal of
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Operations ResearchAdvances in
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Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
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Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
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24 Mathematical Problems in Engineering
between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies
Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights
4 Bibliometric Analysis
Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years
Fuzzy DEMATELGrey DEMATEL
Classical DEMATELANP and DEMATELOther DEMATEL
01020304050607080
Num
ber o
f art
icle
s
Figure 4 Distribution of articles according to the years
Table 5 The top ten papers based on citation measures
Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075
establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty
From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)
In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 25
Computer science406
Engineering 357
Business andmanagements 264
Decision sciences177
Social sciences155
Mathematics 128
Environmentalscience 106
Medicine 67
Economics andeconometrics 52
Energy 52
Other 172
Figure 5 Distribution of articles according to application areas
and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations
5 Conclusions and Suggestions forFuture Work
In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems
Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First
to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as
26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972
[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014
Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
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26 Mathematical Problems in Engineering
threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]
From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies
Conflicts of Interest
The authors declare no conflicts of interest
Acknowledgments
This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)
References
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[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017
[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016
[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014
[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013
[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010
[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016
[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007
[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009
[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007
[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009
[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015
[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013
[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015
[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014
[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014
[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011
[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010
[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014
[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016
[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013
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Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
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[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Mathematical Problems in Engineering 27
[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011
[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013
[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012
[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014
[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013
[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014
[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013
[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015
[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015
[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014
[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016
[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014
[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989
[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004
[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016
[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981
[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014
[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008
[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014
[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016
[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016
[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016
[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009
[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011
[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012
[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015
[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006
[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012
[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016
[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012
[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
28 Mathematical Problems in Engineering
[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013
[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013
[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014
[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015
[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015
[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015
[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015
[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012
[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011
[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016
[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016
[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016
[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016
[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016
[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016
[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success
factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016
[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016
[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016
[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016
[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016
[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016
[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016
[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017
[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006
[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009
[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013
[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014
[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015
[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015
[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013
[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 29
ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017
[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016
[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010
[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015
[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010
[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014
[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011
[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015
[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012
[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010
[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012
[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014
[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013
[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012
[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012
[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012
[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo
Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011
[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012
[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013
[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014
[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013
[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013
[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015
[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015
[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016
[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016
[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014
[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011
[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015
[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015
[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
30 Mathematical Problems in Engineering
[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015
[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013
[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015
[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010
[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012
[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015
[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014
[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011
[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016
[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016
[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011
[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014
[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016
[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016
[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016
[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007
[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008
[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009
[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009
[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011
[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011
[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011
[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012
[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010
[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012
[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013
[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013
[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013
[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013
[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013
[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015
[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014
[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
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Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 31
[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015
[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015
[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015
[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016
[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014
[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017
[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017
[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011
[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011
[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015
[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015
[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008
[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009
[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012
[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012
[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013
[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014
[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015
[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014
[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015
[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015
[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015
[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015
[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007
[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013
[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016
[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016
[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016
[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011
[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012
[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Engineering Mathematics
International Journal of
Hindawiwwwhindawicom Volume 2018
Operations ResearchAdvances in
Journal of
Hindawiwwwhindawicom Volume 2018
Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
Hindawiwwwhindawicom Volume 2018Volume 2018
Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
Nature and SocietyHindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom
Dierential EquationsInternational Journal of
Volume 2018
Hindawiwwwhindawicom Volume 2018
Decision SciencesAdvances in
Hindawiwwwhindawicom Volume 2018
AnalysisInternational Journal of
Hindawiwwwhindawicom Volume 2018
Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom
32 Mathematical Problems in Engineering
[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015
[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013
[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016
[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015
[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015
[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015
[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015
[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015
[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012
[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013
[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014
[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015
[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016
[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016
[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015
[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo
International Journal of Production Economics vol 146 no 1pp 281ndash292 2013
[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016
[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009
[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016
[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016
[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015
[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015
[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014
[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015
[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012
[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015
[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012
[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014
[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010
[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014
[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Engineering Mathematics
International Journal of
Hindawiwwwhindawicom Volume 2018
Operations ResearchAdvances in
Journal of
Hindawiwwwhindawicom Volume 2018
Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
Hindawiwwwhindawicom Volume 2018Volume 2018
Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
Nature and SocietyHindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom
Dierential EquationsInternational Journal of
Volume 2018
Hindawiwwwhindawicom Volume 2018
Decision SciencesAdvances in
Hindawiwwwhindawicom Volume 2018
AnalysisInternational Journal of
Hindawiwwwhindawicom Volume 2018
Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom
Mathematical Problems in Engineering 33
[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017
[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008
[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012
[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009
[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965
[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003
[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015
[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015
[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Engineering Mathematics
International Journal of
Hindawiwwwhindawicom Volume 2018
Operations ResearchAdvances in
Journal of
Hindawiwwwhindawicom Volume 2018
Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
Hindawiwwwhindawicom Volume 2018Volume 2018
Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
Nature and SocietyHindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom
Dierential EquationsInternational Journal of
Volume 2018
Hindawiwwwhindawicom Volume 2018
Decision SciencesAdvances in
Hindawiwwwhindawicom Volume 2018
AnalysisInternational Journal of
Hindawiwwwhindawicom Volume 2018
Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom
Hindawiwwwhindawicom Volume 2018
MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Mathematical Problems in Engineering
Applied MathematicsJournal of
Hindawiwwwhindawicom Volume 2018
Probability and StatisticsHindawiwwwhindawicom Volume 2018
Journal of
Hindawiwwwhindawicom Volume 2018
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawiwwwhindawicom Volume 2018
OptimizationJournal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Engineering Mathematics
International Journal of
Hindawiwwwhindawicom Volume 2018
Operations ResearchAdvances in
Journal of
Hindawiwwwhindawicom Volume 2018
Function SpacesAbstract and Applied AnalysisHindawiwwwhindawicom Volume 2018
International Journal of Mathematics and Mathematical Sciences
Hindawiwwwhindawicom Volume 2018
Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom
The Scientific World Journal
Volume 2018
Hindawiwwwhindawicom Volume 2018Volume 2018
Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in
Nature and SocietyHindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom
Dierential EquationsInternational Journal of
Volume 2018
Hindawiwwwhindawicom Volume 2018
Decision SciencesAdvances in
Hindawiwwwhindawicom Volume 2018
AnalysisInternational Journal of
Hindawiwwwhindawicom Volume 2018
Stochastic AnalysisInternational Journal of
Submit your manuscripts atwwwhindawicom