fuzzymultidimensionalassessmentapproachoftravel ...and related weights. en, this fuzzy...

Research ArticleFuzzy Multidimensional Assessment Approach of TravelDeprivation in Small Underdeveloped Cities Case Study ofLhasa China

Gang Cheng 12 Simin Jiang 1 and Tao Zhang 3

1College of Engineering Tibet University Lhasa 850000 China2Center of Tibetan Studies (Everest Research Institute) Tibet University Lhasa 850000 China3School of Traffic and Logistics Engineering Taiyuan University of Science and Technology Taiyuan China

Correspondence should be addressed to Gang Cheng fengyunleng163com

Received 24 July 2020 Revised 10 March 2021 Accepted 21 March 2021 Published 16 April 2021

Academic Editor Giuseppe Musolino

Copyright copy 2021 Gang Cheng et al is 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

In small underdeveloped Chinese cities the travel needs of economically disadvantaged residents have not been satisfactorily met fora long time and thus the problem of travel inequality has become increasingly serious is study developed and applied a fuzzymultidimensional assessment approach of travel deprivation to assess the travel deprivations that arise because of this travel inequitye resulting model includes both monetary and nonmonetary indicators and involves multiple measurement items dimensionsand related weights en this fuzzy multidimensional assessment approach of travel deprivation is used to measure the traveldeprivation in the underdeveloped small city of Lhasa China e results identified both differences and similarities betweendifferent parts of the city Among all measured dimensions the following four dimensions cause strong travel deprivation disposableincome travel service quality travel time and available transportation Differences in the travel deprivation were identified betweendifferent parts of Lhasa indicatingmultidimensional travel deprivation Furthermore an early warning analysis on travel deprivationand an assessment of different levels of residentsrsquo travel deprivation in underdeveloped cities are presentedese findings provide aneffective evaluation of the current situation of travel inequity in underdeveloped small cities

1 Introduction

During the process of urbanization the problem of uneven andinadequate development among different countries regionsand cities has become a common challenge that residents faceacross the world Affected by multiple factors such as gov-ernmental policies macroeconomic factors regional resourceendowments and factor mobility the differences in develop-ment levels between different regions of China have becomeincreasingly apparent e result is the formation of developedand undeveloped regions In China the eastern region is themain developed region while both the western region and thenortheast region are the main underdeveloped regions

Underdeveloped and developed regions are a relativeconcept A certain gap still exists between the economicdevelopment levels and scientific and technological

development levels of these underdeveloped areas comparedwith developed areas As an important part of Chinarsquos urbansystem small cities (with a permanent population of 200000to 500000) are widely distributed Of these more small citiesare situated in underdeveloped areas than in developedareas In a number of small cities in western and north-eastern China an insufficiency of public facilities is wide-spread For example in the underdeveloped small cities ofthe Tibet Autonomous Region and the Qinghai Provincefactors such as harsh climate poor living conditions anddifficulty associated with population settlement restrictfurther development

In underdeveloped and small cities economically disad-vantaged residential groups are common and their number farexceeds that of economically advantaged groups Huangpointed out that economically disadvantaged groups to some

HindawiJournal of Advanced TransportationVolume 2021 Article ID 8851449 12 pageshttpsdoiorg10115520218851449

extent represent the economic characteristics of residents ofunderdeveloped small cities [1] Mallett reported that eco-nomically disadvantaged groups generally take part in life-sustaining behaviors while the demand for travel to participatein communicative and recreational activities is often sup-pressed [2] Blumenberg and Agrawal pointed out that for low-income groups which form a specific subgroup of economi-cally disadvantaged groups communicative and recreationaltravel increases their travel budget and thereby their burden oflivingerefore low-income groups generally utilize the maintype of travel behavior while the demand for other types oftravel is often suppressed [3]

In many developing countries the travel demand ofeconomically disadvantaged groups is easily ignored Chi-karaishi et al pointed out that the phenomenon of restrainedtravel demand is severe in India Specific economically dis-advantaged groups have lowmobility and spatial distance stillremains the main obstacle that restricts their travel needsExcept for the travel needs caused by school attendance andwork other travel needs of economically disadvantagedgroups cannot be effectively met [4] Salon and Gulyanicompared economically disadvantaged groups in the slums ofIndia with economically advantaged groups and found thateconomically advantaged groups can choose between moretravel methods Furthermore economically disadvantagedgroups can only rely on nonmotorized transportation [5]estudies of Srinivasan and Rogers as well as that of Li showedthat the cost of using private cars in relatively underdevelopedsmall cities is relatively high for most residents consequentlypublic transportation has become a dependent mode oftransportation for residents [6 7]

e current level of prioritization of public transport de-velopment policies in less-developed small cities is not idealGiuliano identified the low level of public transportationprovided (eg low service quality and low accessibility) as themain factor affecting the transportation-related decision-making of economically disadvantaged groups [8]e study ofNuworsoo et al showed that low-income groups experiencestrong dissatisfaction with inadequate public transportationfacilities and with the low frequency of bus departures Inunderdeveloped small cities public transportation does notmanage well to regulate travel equity is results in thecommon situation where the travel rights of economicallydisadvantaged groups cannot be effectively guaranteed [9]Grengs as well as Blumenberg andomas pointed out that thesocial exclusion of economically disadvantaged groups par-ticipating in urban transportation will exert a deeper impact onthe economic and social relationship network thus causing aseries of social problems such as social group events and riots[10 11] e urgent need to solve the travel inequity problemsunderdeveloped small cities are facing has prompted scholarsto conduct relevant travel equity assessments of such cities

2 Literature Review

Equity which originates from the concept of justice withinthe context of Western political philosophy has receivedextensive attention from various fields Related research onresidentsrsquo travel equity stems from the developmental

strategy of the USA that promoted private cars during theldquoPost World War IIrdquo(1946ndash1960) period

Rosenbloom and Altshuler studied the urbanization andmotorization of the USA from 1950 to 1972ey found thatthe US urban population and urban land grew rapidly atgrowth rates of 71 and 176 respectively Moreoverduring this time of growth the corresponding household carownership ratio increased from 52 to 79 and theownership ratio of more than two private cars increasedfrom 7 to 30 respectively [12] Sanchez demonstratedthat the rapid economic development of the USA has in-duced a series of social problems including that black peoplenot only had to face pressures of racial discrimination andhigh unemployment rates but their travel needs had alsobeen severely neglected which triggered the civil rightsmovement At this point many studies began to focus on thetravel needs of ethnic minorities and low-income groupsand the travel equity of urban residents has become thesubject of transportation engineering and related disciplines[13]

Deboosere and El-Geneidy from the Victoria Trans-portation Policy Research Institute have extensively studiedthe issue of travel equity and continuously conducted re-search for many years Deboosere and El-Geneidy dividedtravel equity into three types according to horizontal andvertical dimensions (1) Horizontal equity which involvesequity and egalitarianism (2) vertical equity which involvessocial justice environmental justice and social inclusionand (3) vertical equity regarding mobility needs and abilityIn the process toward achieving travel equity these threedifferent types of travel equity often overlap and diverge withregard to the specific travelerrsquos interest balance is is adynamic process requiring constant balance and coordi-nation [14] Hay showed that horizontal travel equity issuitable for balancing and coordinating the travel needs ofdifferent urban residents in a large area or region whileresearch on vertical travel equity usually uses a specific cityas research object and studies the interior of travel equity[15] From the perspectives of income level social class aswell as ethnic or racial differences studies on the distri-bution of benefits of a specificmode of urban travel belong tothe category of vertical travel equity [16ndash21]

Travel equity assessment from the perspective of sub-jective perception has become a research hotspot includingtravel well-being and travel deprivation ese two con-flicting subjective perceptions form the psychologicalfeedback of the public with regard to travel equity isfeedback not only includes the cognition and demand for theoverall travel supply or a certain aspect but also the emotionsand feelings that emerge during the travel process Conse-quently many aspects are involved such as travel interestsand travel opportunities

Bell showed that the goal of transportation policies is toimprove travel well-being including satisfaction mobilityand accessibility [22] Stanley and Vella-Brodrick foundthat using travel well-being to evaluate travel equity is moremeaningful than assessments based on mobilitye reasonis that the simple improvement of mobility will cause aseries of problems such as traffic congestion and

2 Journal of Advanced Transportation

environmental pollution [23] Lucas et al investigated el-derly and disabled groups with weak mobility and showedthat these two groups benefited very little from an ex-pansion of the road infrastructure or an expanded andshortened travel time therefore it is more valuable toevaluate travel equity from the perspective of psychologicalperception [24] Steg and Gifford as well as De Groot andSteg identified objective indicators and subjective attitudeindicators as equally important to measure travel equityfrom the perspective of well-being [25 26] Jones et al useda number of indicators such as reliability speed and trafficvolume to assess travel well-being [27] Busari et al as wellas Delbosc and Currie showed that improving the mobilityof residents will increase their sense of freedom of traveland their sense of happiness especially when responding toemergencies e positive psychological effect is moreobvious [28 29] According to Delbosc accessibilitymobility and transportation infrastructure are key factorsthat affect residentsrsquo travel well-being [30] Watson et aland Bergstad et al used objective indicators such asmobility trip times and trip frequency to assess travelwell-beinge Satisfaction with Travel Scale ( STS) and theSwedish Core Affect Scale (SCAS) they proposed haveplayed a positive role in promoting travel well-being relatedresearch [31 32] Currie and Delbosc used travel satis-faction and travel cost acceptability to assess travel well-being [33] Later Delbosc and Currie studied the travelwell-being in Melbourne Australia and found that the fourvariables of transport disadvantage public transport dis-advantage traffic-disadvantaged groups and relying onothers to travel exert significant effects on travel well-being[34]

Scholarsrsquo concerns about travel deprivation mainly focuson residentsrsquo inequity during travel however few studiesmeasured the value of travel deprivation Duvarci and Miz-okami assumed that the travel needs of traffic-vulnerablegroups were all met and on this basis they further assessedtravel equity among different groups and proposed corre-sponding travel guidance strategies to reduce travel depriva-tion [35] Lucas studied the phenomenon of travel deprivationin developing countries of Southern Africa e resultsidentified weak infrastructure and poor traffic management asthe main reasons for the social exclusion of vulnerable groupsin society Lucas proposed a travel guidance strategy to alle-viate travel deprivation [36] Ferguson et al found that thephenomenon of travel deprivation should be reduced in detailFor example travel equity should inform the setting of busdeparture intervals to provide more travel opportunities forlow-income groups and increase their employment shoppingand medical service opportunities [37]

To the best of the authorrsquos knowledge so far travelequity in small and underdeveloped cities has not beenstudied Despite the increasing attention devoted to theassessment of travel equity the current literature suffersfrom a number of research gaps that have motivated thisresearch

e contributions of this paper are threefold Much ofthe previous work on the travels of economically disad-vantaged residents suffers from large differences in the study

background ese include differences between countriesand between the cities of the same country Residentsrsquo in-come and travel costs vary greatly between cities with dif-ferent economic development levels Similar to cities withdifferent population sizes residentsrsquo travel patterns andlifestyles also differ significantly Studies on residentsrsquo travelbehavior found significant regional and city size differencesbut these results are insufficient to guide the economicallydisadvantaged groups of Chinarsquos underdeveloped smallcities to solve the travel problems they face erefore thisstudy investigated the travel conditions of residents inChinarsquos underdeveloped small cities and proposed an ef-fective travel deprivation assessment method Empiricalanalysis of a specific investigated city provides a reference forsolving travel inequity problems of similar cities

In addition when studying travel equity from the per-spective of subjective perception most previous studiesfocused on travel well-being and travel deprivation whichrefer to negative feelings that arise because of perceivedtravel inequity is paper presents a survey to measure thevalue of travel deprivation which enriches research on travelequity assessment

Finally with few exceptions most previous studies ontravel deprivation have only considered a specific link or aspecific set of factors associated with the travel processHowever research that comprehensively considers thecauses of travel deprivation is insufficient is study ana-lyzed causes of the travel deprivation in the underdevelopedsmall cities from both monetary and nonmonetary indica-tors is makes the assessment of travel deprivation morebroadly meaningful and can better reflect the inequity as-sociated with travel Following previous studies the devel-oped approach proposes a fuzzy multidimensionalassessment approach of travel deprivation and provides thepossibility for residents in underdeveloped small cities toimplement traffic demand management strategies to alle-viate the travel inequity problem

3 Methodology

Walker and Mann defined the concept of relative depriva-tion is concept implies that someone expects to owncertain things without currently owning these things (be-cause of eg income housing conditions transportationand personal physical condition) [38] De la Sablonniereet al studied the adaptability of both horizontal relativedeprivation and vertical relative deprivation in applicationsey pointed out that the field of sociology is more con-cerned with horizontal relative deprivation while the field ofpolitical science is more concerned with vertical relativedeprivation [39] Smith et al standardized the process ofrelative deprivation and divided the generation of relativedeprivation into three steps (1) comparative motivation (2)personal cognitive assessment where an individual realizesthat he or the group is at a disadvantage and (3) negativeemotional identification where the perceiver believes thatthe current disadvantage he or his group faces is unfairwhich triggers negative emotions When the relative dep-rivation level of a group reaches a certain threshold it is easy

Journal of Advanced Transportation 3

to induce group events such as protests demonstrationsprocessions and strikes [40] Tiraboschi and Maass verifiedthis conclusion through situational experiments [41]Combined with the integrated fuzzy and relative (IFR)deprivation measurement model this paper proposes ameasurement model for travel deprivation which can reflectthe travel inequity problem in underdeveloped small citiese IFR deprivation measurement model considers twofactors the share of the number of individuals whose indexvalue exceeds the research target in the sample set and theshare of the total index of the total index value of otherindividuals whose index value exceeds that of the individualBased on considering both monetary and nonmonetaryindicators the IFR method is used to identify the size of thedeprivation sensing value and to assess the deprivation ofboth monetary and nonmonetary dimensions in underde-veloped small cities e method this study utilized tomeasure residentsrsquo sense of deprivation is summarized in thefollowing based on the individual attributes and mea-surement items in different dimensions the individualrsquostravel deprivation index values are calculated in differentdimensions then they are weighed to ensure that the in-dividual belongs to the same group Dimensional total traveldeprivation and the average individual travel deprivation ofindividual groups in different dimensions are finallycalculated

31 Model Hypothesis

Hypothesis 1 In the study of the relationship between in-come and travel ability Blumenberg and Agrawal Chi-karaishi et al as well as Salon and Gulyani found thatincome and travel ability are closely relatedis is one of theimportant reasons why the travel demand of economicallyvulnerable groups cannot be effectively met [3ndash5] Income isan important factor for testing the individualrsquos compre-hensive ability and it has been extensively applied in thesocial deprivation perception as an effective tool To a largeextent income represents the consumption or purchasingpower of commodities and includes personal incomefamily income disposable income and hidden income (egsocial welfare) erefore it is assumed that the incomefactor (monetary index M) is the same as other importantfactors that lead to travel deprivation for residents in smallunderdeveloped cities (nonmonetary index S)

Hypothesis 2 Monetary indicators and nonmonetary in-dicators have significant differences in travel deprivationand the inherent correlation between both is not considered

Hypothesis 3 If the travel needs of residents in underde-veloped small cities cannot be met (or cannot be met suf-ficiently) this will cause deep-seated social exclusion issues(spatial exclusion temporal exclusion and economic ex-clusion) ese in turn will impose adverse effects onresidentsrsquo employment education entertainment and socialaspects [35] Particularly in underdeveloped small citiestraffic-disadvantaged groups face more difficulties to obtain

effective protection for their travel rights compared withother groupse insufficiency of barrier-free transportationfacilities is the main reason that restrains the travel demandof physically disadvantaged groups At the same time thisgroup is also vulnerable to restrictions in terms of traveldistance travel mode and travel coste social exclusion ofsuch economically disadvantaged groups is mainly man-ifested in three aspects spatial exclusion temporal exclu-sion and economic exclusion Spatial exclusion mainlymanifests as poor travel accessibility time exclusion mainlymanifests as an inability to choose efficient travel modes andeconomic exclusion has a significant impact on employmentconsumption and entertainment in addition to the impactcaused by the need to pay for travel expenses

Hypothesis 4 Travel deprivation not only originates fromthe relative comparison of residents during the process oftravel but also from the comparison of the travel status ofresidents with their past and future (or their desired situ-ation) erefore travel events (eg traffic accidents trafficcongestion and travel disputes) and the desire for a certainmeans of transportation will increase the probability ofresidentsrsquo travel deprivation

Hypothesis 5 e factors that affect the travel deprivation ofresidents in small and underdeveloped cities are discreterandom variables e factors that cause residents to ex-perience travel deprivation are discrete random variables1113954X 1113954X1

1113954X2 1113954Xn 1113954X1113954n1113966 1113967 where 1113954n represents thenumber of influencing factors Among these one or moreinfluencing factors with the same attribute can form a di-mension that creates travel deprivation δ1113954δ isin (1 2 δ 1113954h) Each dimension causes travel dep-rivation and the combination of multiple dimensions causescomprehensive travel deprivation

Hypothesis 6 All dimensions of travel deprivation arepositive indicators ie a larger index value indicates a higherlevel of travel deprivation In contrast a smaller index valueindicates a weaker travel deprivation perceived by residents

Hypothesis 7 e deprivation values produced by residentsin different indicators and different dimensions are com-parable and additive

32 Index Value e dichotomy method has good appli-cability for assessments of travel deprivation when nonmon-etary indicators are used [42]e distribution function offers agood assessment of individual deprivation of nonmonetaryindicators When the nonmonetary index deprivation value(μi) is 1 the travel demand is not satisfied and travel dep-rivation emerges In contrast when the value of μi is 0 thetravel request is satisfied and there is no travel deprivation

For nonmonetary indicators that involve more than twoordered categories Cerioli and Zani proposed a calculationmethod that uses equally spaced and ordered categories toreflect the different degrees of deprivation experienced byindividuals (1113954dki) and it can be written as follows [4]


1113954dki 1113954C minus 1113954ci

1113954C minus 1 1le1113954ci le 1113954C (1)

In equation (1) the value of the deprivation assessmentitem (k) represents the ordered category of [1 1113954C] and 1113954ci

represents the value of the ordered category of the individual(i) in the assessment item k e value of deprivation is 1 toindicate the highest deprivation and the value 1113954C representsthe minimum deprivation

Belhadj proposed the use of the distribution function(F

(1113954ci)) to replace the relatively simple ordered category

ranking in equation (1) to assess the deprivation of indi-vidual nonmonetary indicators as shown in [43]

1113954dki 1 minus F

ci( 11138571113882 1113883

1 minus F

(1)1113882 1113883

(2)

when 1113954C 2 equation (2) presents a dichotomy 1113954dki 1represents deprived and 1113954dki 0 represents not deprived

In the deprivation assessment income is a typicalmonetary indicator e threshold of monetary indicators(1113954z) is set as the basis for dividing deprivation and non-deprivation When the value of a certain type of currencyindicator of an individual (yi

prime) is lower than the setthreshold the individual (i) will feel a sense of deprivationand the value is 1 In contrast when yi

prime is higher than 1113954z theindividual is not deprived and the sense of deprivation is 0e monetary indicator travel deprivation function (mf )based on binary classification is calculated by

mf μi 1 yi

prime lt 1113954z

μi 0 yiprime ge 1113954z

⎧⎨

⎩ (3)

Based on the dichotomy Cerioli and Zani used intervalforms to represent monetary indicators and defined theindividual deprivation value as a linear value of [0 1] withinthe income interval (1113954z1 minus 1113954z2) is is represented by [42]

mf

μi 1 yiprime lt 1113954z1

μi z2 minus yi

z2 minus z1 1113954z1 leyi

prime le 1113954z2

μi 0 yiprime ge 1113954z2

⎧⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎩

(4)

33 Model Development By combining monetary andnonmonetary indicators the developed approach proposes afuzzy multidimensional assessment approach to assess traveldeprivation from multiple dimensions is approach usesthe above framework with a number of important refine-ments as outlined in the following

Step 1 the influencing factors of the deprivation ofresidents in small cities is first analyzed and screenedfor then items of travel deprivation sensitivity are setbased on the determined influencing factors finally thefactor analysis method is used to divide the items intodifferent dimensions according to nonmonetary indi-cators and monetary indicators δ

Step 2 the weight and deprivation value of the itemsare determined in the same assessment dimensionCombined with the analytic hierarchy process theweight of different items in the same latitude di-mension is determined and the weight set is estab-lished as follows [44]

Wδ ωδ1ωδ2 ωδk ωδ _k1113872 1113873 (5)

where ωδk represents the weight of item k in dimensionδ and ωδk ge 0 1113936

_kk1 ωδk 1

Furthermore based on the deprivation index valuemethod the travel deprivation value obtained corre-sponds to each item in different assessment dimen-sions Finally the travel deprivation value of differentassessment dimensions (SMδi) is calculated with

SMδi 1113936kisinδωδk 1 minus dδki1113872 1113873

1113936kisinδωδk

δ isin (1 2 3 1113954h) (6)

where dδki represents the travel deprivation valueobtained from item k in dimension δStep 3 based on the totally fuzzy and relative (TFR)method combined with the deprivation of the travelfunction in different assessment dimensions and theLorentz curve of the deprivation of travel (i) the in-dividualrsquos travel deprivation (1113957μ) is determined etravel deprivation of any individual can be expressed inthree forms

Step 31 using the TFR method the distributionfunction F

(δ)i of the travel deprivation (SM) of the

individual i in the dimension δ can be obtained F(δ)i

is expressed as follows

F(δ)i 1 minus

1113936hωδh|SMδh gt SMi

1113936hωδh|SMδh gt SM11113888 1113889 (7)

Furthermore the proportion of samples with a senseof travel deprivation lower than that of individual i inthe total sample can be obtained ie the fuzzy indexof the sense of travel deprivation ζ i which can beexpressed as

ζ i FSMδi 1 minus F

(δ)i1113872 1113873 i isin (1 2 3 n) (8)

Step 32 based on the fuzzy index of travel depri-vation as determined in Step 31 the fuzzy index isoptimized using the deprivation curve e opti-mized fuzzy index of travel deprivation (ζ i

prime) can becalculated using

ζ iprime FSMδ

i 1 minus L(δ)i1113872 1113873 i isin (1 2 3 n) (9)

where Lδi represents the value of the deprivation

curve of individual i in the first dimension δ Lδi can

be calculated by

L(δ)i 1 minus

1113936nωδhSMδh|SMδh gt SMi

1113936nωδhSMδh|SMδh gt SM11113888 1113889 (10)


Step 4 using the IFRmethod combined with equations(8) and (9) an individualrsquos travel deprivation mea-surement model in individual dimensions can be ob-tained according to equation (11) [45ndash47] e modelconsiders the index weights in different assessmentdimensions

μ FSM(δ) 1113944

h

δ1α(SMδ)

1 minus F(δ)i1113872 1113873 middot 1 minus L

(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

where α(SMδ) represents the weight of different di-mensions of monetary and nonmonetary indicatorsand 0lt α(SMδ) lt 1 1113936h

1 α(SMδ) 1is model considers

the index weights in different measurement dimen-sions A Bayesian network is used to measure thedegree of difference between travel deprivation mea-surement dimensions ie to determine the indexweights within different measurement dimensions

4 Study Area Details and Data

According to the 2018 Statistical Yearbook of the TibetAutonomous Region Lhasa had a registered population of540000 at the end of 2018 and a population of 300000 in themunicipal district is is typical for an underdevelopedsmall city in the plateau regionerefore this paper selectedLhasa as a case city to assess the travel deprivation value andconduct an empirical analysis of the constructed traveldeprivation measurement model

e investigation team randomly selected 15 residentialdistricts from the four districts under the jurisdiction ofLhasa (ie areas of Zhucheng Duilong Liuwu-Cijuelin andBaidian-Dazi ) from a total of 60 districts A questionnairesurvey on residentsrsquo deprivation of travel was carried out Inthe investigation adults over 18 years of age were selected asfamily representatives to complete the questionnaire ontravel deprivation

In reference to relevant questionnaires of the socialdeprivation survey and the residentsrsquo travel behavior surveythe questionnaire items for the travel deprivation sensitivitysurvey in the underdeveloped small cities were prescreenedand evaluated Finally seven assessment dimensions wereformed including both monetary indicators and non-monetary indicators totaling 27 items as shown in Tables 1and 2 [48] In the questionnaire nonmonetary indicatorsallow two alternative answers ldquoYesrdquo and ldquoNordquo ldquoYesrdquo isrepresented by a value of 0 indicating that there is nodeprivation ldquoNordquo is represented by a value of 1 indicatingthat there is deprivation the items involved in monetaryindicators mainly investigate the residentsrsquo monthly dis-posable income and the respondentsrsquo needs to provide aspecific income e final number of valid questionnaireswas 52 in the areas of Zhucheng 39 in Duilong 43 in Liuwu-Cijuelin and 49 in Baidian-Dazi Finally 30 sets of effectivedata were extracted from each area to assess the deprivation

of the residents of Lhasa Descriptive statistics differencesbetween cities are the result of sampling and are repre-sentative of the descriptive statistics of the city overall Inorder to balance the population differences between citiesour analysis does not focus on the differences between citiesbut rather on their similarities

5 Empirical Results and Discussion

51Case Study of Lhasa According to the travel deprivationevaluation model proposed in Section 3 the average valuesof travel deprivation for the seven assessment dimensionsthat correspond to the four investigated areas of Lhasa areshown in Table 3 (for the travel deprivation examples ofZhucheng area see Tables A1 and B1 in SupplementaryMaterials) FSM1 is the travel deprivation perceived for theincome dimension (ie the currency indicator) FSM2FSM3 FSM4 FSM5 FSM6 and FSM7 are the deprivation oftravel produced by S1 S2 S3 S4 S5 and S6 dimensions undernonmonetary indicators respectively

Table 3 shows that all the seven assessment dimensionsplay an important role in the assessment of travel deprivatione average value of travel deprivation corresponding to thedimensions of income travel conditions service qualitytransportation travel values travel efficiency and travel costscan explain residentsrsquo perceived travel deprivation enonmonetary indicator dimensions (FSM2 FSM3 FSM4FSM5 FSM6 and FSM7) as well as the monetary indicatordimension as a whole are negatively correlated In otherwords the higher the per capita disposable income the lowerthe probability of travel deprivation generated by the non-monetary indicator dimension In contrast the lower theincome the higher the probability of travel deprivationgenerated by the nonmonetary indicator dimension

ese results confirm that the sense of deprivation causedby different dimensions is different and uniform in differentareas and the intensity of the sense of travel deprivationcaused by different dimensions is also inconsistent especific conditions are summarized in the following

e same dimension leads to different travel depriva-tions in different areas Among these the three dimensionsof FSM2 (travel condition) FSM3 (service quality) andFSM6 (travel efficiency) showed the most significant dif-ferences in deprivation in different areas e differencesbetween the maximum and minimum travel deprivationvalues were 01235 01202 and 00834 respectively etravel deprivation generated by the dimension of travelconditions is related to the location of the residence A largedifference was found in the transportation resources availablefor residents in noncommercial areas and commercial areas(ie the administrative center)is leads to a large differencein the sense of travel deprivation perceived by residents indifferent areas For example the Zhucheng area has anabundance of transportation infrastructure therefore thedeprivation value of the travel condition dimension issmallest in this areae service quality dimension focused onthe travel safety travel experience and mobility of travelinvolved in the travel process of residents e service qualityproblems are most typical in the Liuwu-Cijuelin area e


Princess Wencheng live performance venue is located in thisarea the phenomenon of scattered residents is quite commonand service quality cannot be guaranteed continuously At thesame time because the transportation planning in this areahas entered the adjustment stage the residentsrsquo demands forservice quality have been ignored by both the government andtransportation planning departments Travel time is the mainreason why the travel efficiency dimension leads to residentsrsquoperceived travel deprivation Underdeveloped small citiesface a higher probability of traffic congestion in denselypopulated areas When congestion is not managed in a timelymanner the likelihood of travel deprivation caused by travelefficiency increases which is the case in the Duilong area

e travel deprivation is uniform in different areas withthe same dimension Transportation (FSM4) mainly assessesthe deprivation of residents caused by a long-term lack of a

Table 1 Distribution of travel deprivation questionnaire

Types of indicators Dimensions Purpose of assessment

Comprehensive indicators(SM)

Nonmonetary indicators(S)

Travel conditions S1Advantages and disadvantages of residentsrsquo travel

conditionsService quality S2 Level of service qualityTransportation S3 Travel demands for missing means of transportationTravel values S4 Regional travel culture cognition

Travel efficiency S5 Travel time consumption toleranceTravel cost S6 Acceptability of travel cost

Monetary indicator (M) Income M1Economic status of respondents (related to travel

capacity)

Table 2 Content of travel deprivation items

Dimensions Items NoIncome M1 Monthly disposable income (disnic) M11

Travel conditions S1

Good public transportation conditions S11Existence of conditions for private car travel S12

Existence of conditions that facilitate transportation S13Existence of conditions for travel by taxi S14

Good walking conditions S15Existence of other travel conditions such as commuter shuttle S16

Service quality S2

Existence of good travel security S21Existence of a more satisfactory travel experience S22

Existence of a smooth travel environment S23

Transportation S3

No appeal for private cars S31No appeal for electric vehicles S32

No appeal for bicycles S33No appeal for the subway S34

No appeal for light rail and other transportation means S35

Travel values S4

Has good consistency with the surrounding people in the choice of travel mode S41Frequently used travel methods are not easily affected by other travel modes S42

Assuming that the chosen way of travel is guaranteed S43Satisfaction with current travel mode S44

Travel efficiency S5

e time from the departure point to the boarding point is within an acceptable range S51e waiting time is within an acceptable range S52

e travel time of the vehicle is within an acceptable range S53e time from the drop-off point to destination is within an acceptable range S54Transfer time and other time consumptions are within an acceptable range S55

Travel cost S6

Travel costs are totally unacceptable for an extended time S61Travel costs are high but can be accepted for an extended time S62

Travel costs are reasonable and can be accepted for an extended time S63Travel costs can be accepted for an extended time but lower costs would be better S64

Table 3 Mean deprivation of travel in a single dimension

Lhasa Zhucheng Duilong Baidian-Dazi

Liuwu-Cijuelin

FSM1 04372 04082 04202 04922 04283FSM2 04118 03019 04782 04416 04254FSM3 04846 04439 04991 04491 05461FSM4 03645 03593 03644 03672 03669FSM5 03519 03569 03474 03539 03494FSM6 04579 04430 04798 04312 03596FSM7 03057 02924 02905 02927 03472Note According to the raw data of these four areas the per capita disposableincomes of the residents of Lhasa and the four assessed areas (ie areas ofZhucheng Duilong Baidian-Dazi and Liuwu-Cijuelin ) are 1974 20401921 1981 and 1953 respectively e mean value of the nonmonetarydimensions (FSM2 FSM3 FSM4 FSM5 FSM6 and FSM7) in Lhasa and thefour areas were 03960 03662 04099 03893 and 03991 respectively


specific means of transportation e traffic congestion inLhasa is becoming increasingly severe therefore residents inthe four districts have a strong desire for large-capacitytransportation such as rail transit In different areas the traveldeprivation produced by the vehicle dimension is relativelyuniform and the difference between the maximum andminimum value of travel deprivation is only 00076e travelvalue dimension (FSM5) mainly reflects the residentsrsquo cog-nition and assessment of the currently existing travel statuswhich involves travel mode recognition road rights alloca-tion and other relevant aspects e caused deprivation isrelatively consistent across all four areas and the differencebetween the maximum and minimum deprivation values is00095 indicating strong uniformity Traffic jams are com-mon in Lhasaerefore the residents of the four areas have aunified desire for increased transportation capacity (in theform of eg rail transit) e sense of deprivation caused bythe vehicle dimensions is more uniform and the differencebetween the maximum and minimum deprivation is 00076

e degree of travel deprivation caused by differentdimensions differs e four assessment dimensions ofservice quality travel efficiency income and travel condi-tions are associated with the highest levels of travel depri-vation e average values of travel deprivation in Lhasa are04846 04579 04372 and 04118 respectively e level oftravel supply in underdeveloped small cities was evaluatedthrough the quality of travel conditions the level of travelservice quality and the efficiency of travel e incomedimension mainly assesses the economic status of residentsIn underdeveloped small cities where economically dis-advantaged groups form the main body of residents theincome level of residents is relatively low compared withother cities erefore income has a close relationship withthe ability of residents to travel and their sense of traveldeprivation indicates their satisfaction with their currentincome Weak traffic infrastructure and backward trafficmanagement are important factors that restrict the level oftravel supply e three dimensions of travel quality travelefficiency and travel conditions cause higher travel depri-vation which represents the comparatively low level of travelsupply in underdeveloped small cities Among the sevenassessment dimensions the travel cost dimension causes arelatively small travel deprivation with an average value of03519 is indicates that compared with other dimensionssuch as travel quality and travel efficiency the residentsrsquoacceptability of travel costs is relatively high is furtherindicates that residents pay more attention to travel qualitytravel efficiency and travel conditions during travel

Based on the values of travel deprivation in differentdimensions the comprehensive travel deprivation generatedby residents of Lhasa in multiple dimensions as well as bothmonetary and nonmonetary indicators are assessed edeprivation assessment results are shown in Table 4

Table 4 shows that residents in different areas of Lhasahave different perceptions of the comprehensive traveldeprivation they face Of the investigated areas the Baidian-Dazi area has the largest comprehensive travel deprivationvalue while the Zhucheng area has the smallest value edifference in travel deprivation between these two areas was

0056 e reason for the observed differences in the com-prehensive travel deprivation among different areas of Lhasais related to the degree of urbanization and motorization inthis area Since it is the location of the Potala Palace theZhucheng area forms the political and economic center ofLhasa e government and transportation-related man-agement departments attach relatively high importance tothis area which manifests as an increased allocation oftransportation resources and improved transportationmanagement At the same time residents living in theZhucheng area have relatively higher incomes comparedwith those living in other areas e Baidian-Dazi area is farfrom the city center and factors such as weak transportationinfrastructure and low-income levels of residents have led toa low degree of satisfaction of residentsrsquo travel needserefore residents in the areas of Zhucheng and Baidian-Dazi present stronger differences in travel deprivationwhich means that the degree of travel deprivation in dif-ferent areas is inconsistent

52EarlyWarningAnalysis ofTravelDeprivation If a certaindegree of travel deprivation accumulates as a result ofnegative psychological and emotional feedback caused byperceived travel injustice it will not be conducive tomaintaining the normal travel order of residents in small andunderdeveloped cities Based on previous studies on the Ginicoefficient of social equity and by combining the relationshipbetween the deprivation function and the Gini coefficient inthe travel deprivation measurement model this paper cal-ibrates the critical threshold of the comprehensive traveldeprivation of residents in small and underdeveloped citiesto 04ndash045 If the comprehensive travel deprivation valueexceeds 045 this indicates a severe urban travel deprivationproblem that can easily induce discontent in other socialgroups

Based on the results of the mean deprivation of single-dimensional travel Figure 1 shows a comparison of dep-rivation in different dimensions e color distribution inFigure 1 depicts the size of the single-dimensional traveldeprivation in different areas

Based on the results of comprehensive travel depriva-tion the comprehensive travel deprivation value of Lhasa is04194 e range of the critical value classifies this as awarning state the comprehensive travel deprivation value ofthe main city area is 03883 which is classified as a non-warning state the comprehensive travel deprivation valuesof the areas of Duilong Baidian-Dazi and Liuwu-Cijuelinare all in an early warning state the comprehensive traveldeprivation value of Baidian-Dazi area is 04443 which

Table 4 Comprehensive deprivation of residents in Lhasa

Macro-region μLhasa 04194Zhucheng area 03883Duilong area 04190Baidian-Dazi area 04443Liuwu-Cijuelin area 04174


represents a high early warning state e warning status ofLhasarsquos comprehensive travel deprivation is shown in Fig-ure 2 e color-coded areas in the figure show the warningareas of Lhasa and the red area indicates areas with a highwarning state

Figure 2 shows that the comprehensive travel depriva-tion in Lhasa city center (ie Zhucheng area) is in a non-warning state while other (non-Zhucheng) areas are in anearly warning state is is consistent with previous studieson travel equity in other types of cities [34] In China manyeconomically disadvantaged groups live in nonurban cen-ters and the urban marginalization of such places of resi-dence increases the vulnerability of economicallydisadvantaged groups Compared with the residents in the

urban centers the economically disadvantaged groups livein nonurban centers Participation in urban transportationneither manifests in the fact that their travel needs are notwell met in space and time nor in the economic and socialnetworks Grengs as well as Blumenberg andomas foundthat low-income groups that live on the edge of cities areprone to miss job opportunities throughout the cityerefore they generally choose a job nearby and theirprobability to receive comparatively low salaries and re-muneration is high which is not conducive to the reductionof residentsrsquo perceived travel deprivation [10 11]

e assessment of comprehensive travel deprivation is infact an assessment of the relationship between travel supplyand travel demand e value of travel deprivation can better

FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1

Zhucheng Duilong Baidian-dazi Liuwu-ci juelinLhasa03

035

04

045

05

Figure 1 Comparative analysis of single-dimensional travel deprivation

RiversRoadsNonwarning state

Early-warning stateHigh-warning state

0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend

Figure 2 e warning status of Lhasarsquos comprehensive travel deprivation


represent the satisfaction of the travel needs of residents insmall and underdeveloped cities ie travel deprivation re-flects the contradiction between travel-related supply anddemand e more the comprehensive travel deprivationvalue exceeds a critical threshold the more severe the traveldeprivation in the city will be Based on the results of the earlywarning status of urban comprehensive travel deprivationthe large difference of comprehensive travel deprivationvalues in different areas indicates that Lhasa not only faces atravel inequity problem but also that it suffers from a deep-seated problem of perceived internal travel inequity ere-fore the implementation of traffic demand managementpolicies or other measures that alleviate the contradictionbetween travel demand and supply is very important towardrealizing travel equity in underdeveloped small cities

6 Conclusions

is study investigated the travel inequity problem in smalland underdeveloped cities of China and identified the im-pacts of both monetary and nonmonetary indicators ontravel deprivation e authors have conducted long-termintermittent observations and research on the travel be-havior of local residents to promote travel equity in un-derdeveloped small cities in China is paper proposes afuzzy multidimensional assessment approach of traveldeprivation to assess residentsrsquo negative feelings that arisebecause of a sense of travel inequity based on relativedeprivation theory combined with the IFR deprivationmeasurement model is model involves both monetaryand nonmonetary indicators multiple measurement itemsdimensions and related weights en the travel depriva-tion measurement model is used to assess the travel dep-rivation in underdeveloped small cities is assessmentyielded several interesting conclusions

e first conclusion is that both monetary and non-monetary factors are important reasons for the deprivationof residents in small and underdeveloped cities e di-mensions of income travel conditions service qualitytransportation travel values travel efficiency and travelcosts significantly impact the value of travel deprivation

e three factors of travel conditions service quality andtravel efficiency lead to obvious differences in travel dep-rivation in different areas of the city e difference in theavailable transportation resources in different areas is animportant reason for the inconsistency of travel deprivationbetween different areas in the same measurement dimensionof small and underdeveloped cities

e two measurement dimensions of transportationdemand and travel values are uniform in the travel depri-vation of different areas of the city therefore the differencein the value of travel deprivation between the investigatedareas is small In underdeveloped small cities traffic con-gestion is becoming increasingly severe and therefore ur-ban residents have a relatively strong demand for large-capacity transportation Residents in different regions ofLhasa have a better understanding of the overall travel statussuch as travel mode recognition and road rights allocatione fact that these two measurement dimensions have

unified travel deprivation in different areas of Lhasa forms aunique regional travel culture

e measurement dimensions of service quality travelefficiency income and travel conditions have high levels oftravel deprivation while the travel cost measurement di-mension has a lower level of travel deprivation is alsoindicates that residents of underdeveloped small cities aremore prone to perceive travel deprivation because of travelefficiency and travel conditions

Since comprehensive travel deprivation is at an earlywarning state the governments and transportation man-agement departments of underdeveloped small cities ur-gently need to implement transportation demandmanagement policies and measures to alleviate the ongoingcontradiction between travel supply and travel demand Inthe process of improving the travel inequality situation it isnecessary to focus on the differences in the values of traveldeprivation in different areas of the same city ie the deeperlevel of travel inequality issues

Data Availability

In this study the data of travel deprivation scores formonetary and nonmonetary indicators are presented in thesupplemental files All other data used are contained withinthe article

Conflicts of Interest

e authors declare no conflicts of interest

Acknowledgments

is research was supported by the National Natural ScienceFoundation of China (Grant No 51968063) the WuhanUniversity of Technology and Tibet University Joint Project(Grant No lzt2020007) the Cultivation Project of TibetUniversity (Grant No ZDTSJH19-01) and the Tibet Uni-versity Plateau Train Operation Control Simulation Plat-form Scientific Research Innovation Team ConstructionProjecte authors are very grateful toe Bus Company ofthe Lhasa Public Traffic Group as well as investigators andrespondents who helped with data collection

Supplementary Materials

Table A1 travel deprivation scores for monetary andnonmonetary indicators of 30 samples in the Zhucheng areaTable B1 average values of travel deprivation in the case ofthe Zhucheng area (Supplementary Materials)

References

[1] Y Huang ldquoLow-income housing in Chinese cities policiesand practicesrdquo 7e China Quarterly vol 212 pp 941ndash9642012

[2] W J Mallett ldquoLong-distance travel by women results fromthe 1995 American travel surveyrdquo Transportation ResearchRecord Journal of the Transportation Research Boardvol 1693 no 1 pp 71ndash78 1999


[3] E Blumenberg and A W Agrawal ldquorsquoGetting around whenyoursquore just getting by transportation survival strategies of thepoorrdquo Journal of Poverty vol 18 no 4 pp 355ndash378 2014

[4] M Chikaraishi A Jana R Bardhan et al ldquoTime use of theurban poor and rural poor on activities and travel in GujaratIndia similarities and differencesrdquo Asian Transport Studiesvol 4 no 1 pp 19ndash36 2016

[5] D Salon and S Gulyani ldquolsquoMobility poverty and gendertravel ldquochoicesrdquo of slum residents in nairobi KenyardquoTransport Reviews vol 30 no 5 pp 641ndash657 2010

[6] S Srinivasan and P Rogers ldquoTravel behavior of low-incomeresidents studying two contrasting locations in the city ofChennai Indiardquo Journal of Transport Geography vol 13no 3 pp 265ndash274 2005

[7] J Li ldquoDecoupling urban transport from GHG emissions inIndian cities-A critical review and perspectivesrdquo EnergyPolicy vol 39 no 6 pp 3503ndash3514 2011

[8] G Giuliano ldquoLow income public transit and mobilityrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1927 no 1 pp 63ndash70 2005

[9] C Nuworsoo A Golub and E Deakin ldquoAnalyzing equityimpacts of transit fare changes case study of AlamedandashContraCosta Transit Californiardquo Evaluation and Program Planningvol 32 no 4 pp 360ndash368 2009

[10] J Grengs ldquoEquity and the social distribution of job acces-sibility in Detroitrdquo Environment and Planning B Planningand Design vol 39 no 5 pp 785ndash800 2012

[11] E Blumenberg and T omas ldquoTravel behavior of the poorafter welfare reformrdquo Transportation Research Record Journalof the Transportation Research Board vol 2452 no 1pp 53ndash61 2014

[12] S Rosenbloom and A Altshuler ldquoEquity issues in urbantransportationrdquo Policy Studies Journal vol 6 no 1 pp 29ndash401977

[13] T W Sanchez ldquoPoverty policy and public transportationrdquoTransportation Research Part A Policy and Practice vol 42no 5 pp 833ndash841 2008

[14] R Deboosere and A El-Geneidy ldquoEvaluating equity andaccessibility to jobs by public transport across CanadardquoJournal of Transport Geography vol 73 pp 54ndash63 2018

[15] A Hay ldquoEquity and welfare in the geography of publictransport provisionrdquo Journal of Transport Geography vol 1no 2 pp 95ndash101 1993

[16] M Garrett and B Taylor ldquoReconsidering social equity inpublic transitrdquo Berkeley Planning Journal vol 13 no 1pp 6ndash27 2012

[17] P Bearse S Gurmu C Rapaport and S Stern ldquoParatransitdemand of disabled peoplerdquo Transportation Research Part BMethodological vol 38 no 9 pp 809ndash831 2004

[18] B Jones ldquoDisadvantage and disenfranchisement in Britishlabour markets a social constitutions perspectiverdquo Interna-tional Review of Sociology vol 8 no 1 pp 95ndash113 1998

[19] C Wright ldquoExport credit agencies and global energy pro-moting national exports in a changing Worldrdquo Global Policyvol 2 pp 133ndash143 2011

[20] Z He ldquoSpatial-temporal fractal of urban agglomeration traveldemandrdquo Physica A-Statistical Mechanics and Its Applica-tions vol 549 pp 1ndash11 2020

[21] J Xiong B Chen X Li et al ldquoDemand responsive service-based optimization on flexible routes and departure time ofcommunity shuttlesrdquo Sustainability vol 12 no 897 pp 1ndash202020

[22] W G Bell ldquoTransport coordination and social policyrdquoTransportation Research Part A General vol 24 no 6pp 497ndash499 1990

[23] J Stanley and D Vella-Brodrick ldquoe usefulness of socialexclusion to inform social policy in transportrdquo TransportPolicy vol 16 no 3 pp 90ndash96 2009

[24] K Lucas S Tyler and G Christodoulou ldquoAssessing theldquovaluerdquo of new transport initiatives in deprived neighbour-hoods in the UKrdquo Transport Policy vol 16 no 3 pp 115ndash1222009

[25] L Steg and R Gifford ldquoSustainable transportation and qualityof liferdquo Journal of Transport Geography vol 13 no 1pp 59ndash69 2005

[26] J I M D Groot and L Steg ldquoImpact of transport pricing onquality of life acceptability and intentions to reduce car usean exploratory study in five European countriesrdquo Journal ofTransport Geography vol 16 no 4 pp 463ndash470 2006

[27] P Jones K Lucas and M Whittles ldquoEvaluating andimplementing transport measures in a wider policy contextthe ldquoCivilising Citiesrdquo initiativerdquo Transport Policy vol 10no 3 pp 209ndash221 2003

[28] A A Busari D O Oluwafemi S A Ojo et al ldquoMobilitydynamics of the elderly review of literaturesrdquo IOP ConferenceSeries Materials Science and Engineering vol 640 pp 1ndash82019

[29] A Delbosc and G Currie ldquoPiecing it together a structuralequation model of transport social exclusion and well-beingrdquoNew Perspectives and Methods in Transport and Social Ex-clusion Research vol 34 pp 157ndash167 2011

[30] A Delbosc ldquoe role of well-being in transport policyrdquoTransport Policy vol 23 pp 25ndash33 2012

[31] D Watson L A Clark and A Tellegen ldquoDevelopment andvalidation of brief measures of positive and negative affect thePANAS scalesrdquo Journal of Personality and Social Psychologyvol 54 no 6 pp 1063ndash1070 1988

[32] C J Bergstad A Gamble T Garling et al ldquoSubjective well-being related to satisfaction with daily travelrdquo Transportationvol 38 no 1 pp 1ndash15 2011

[33] G Currie and A Delbosc ldquoModelling the social and psy-chological impacts of transport disadvantagerdquo Trans-portation vol 37 no 6 pp 953ndash966 2010

[34] A Delbosc and G Currie ldquoTransport problems that matter-social and psychological links to transport disadvantagerdquoJournal of Transport Geography vol 19 no 1 pp 170ndash1782011

[35] Y Duvarci and S Mizokami ldquoA suppressed demand analysismethod of the transportation disadvantaged in policy mak-ingrdquo Transportation Planning and Technology vol 32 no 2pp 187ndash214 2009

[36] K Lucas ldquoMaking the connections between transport dis-advantage and the social exclusion of low income populationsin the Tshwane Region of South Africardquo Journal of TransportGeography vol 19 no 6 pp 1320ndash1334 2011

[37] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-settingproblemrdquo Transportation Research Part A Policy and Practicevol 46 no 1 pp 190ndash199 2012

[38] L Walker and L Mann ldquoUnemployment relative depriva-tion and social protestrdquo Personality and Social PsychologyBulletin vol 13 no 2 pp 275ndash283 1987

[39] R D L Sablonniere F Tougas and M Lortielussier ldquoDra-matic social change in Russia and Mongolia connectingrelative deprivation to social identityrdquo Journal of Cross-Cul-tural Psychology vol 40 no 3 pp 327ndash348 2009


[40] H J Smith T F Pettigrew G M Pippin and S BialosiewiczldquoRelative deprivationrdquo Personality and Social PsychologyReview vol 16 no 3 pp 203ndash232 2012

[41] M Tiraboschi and A Maass ldquoReactions to perceived depri-vation in ingroup and outgroup a cross-cultural compari-sonrdquo European Journal of Social Psychology vol 28 no 3pp 403ndash421 1998

[42] A Cerioli and S Zani ldquoA fuzzy approach to the measurementof povertyrdquo Studies in Contemporary Economics vol 34pp 272ndash284 1990

[43] B Belhadj ldquoNew fuzzy indices of poverty by distinguishingthree levels of povertyrdquo Research in Economics vol 65 no 3pp 221ndash231 2011

[44] F T S Chan and N Kumar ldquoGlobal supplier developmentconsidering risk factors using fuzzy extended AHP-basedapproachrdquo Omega vol 35 no 4 pp 417ndash431 2007

[45] G Betti and V Verma ldquoMeasuring the degree of poverty in adynamic and comparative context a multi-dimensional ap-proach using fuzzy set theoryrdquo in Proceedings of the ICCS-VIvol 11 pp 289ndash301 London UK 1999

[46] G Betti B Cheli A Lemmi et al ldquoMultidimensional andlongitudinal poverty an integrated fuzzy approachrdquo Eco-nomic Studies in Inequality Social Exclusion and Well-Beingvol 65 no 3 pp 111ndash137 2006

[47] B Cheli and A Lemmi ldquoA totally fuzzy and relative approachto the multidimensional analysis of povertyrdquo Economic Notesvol 24 pp 115ndash134 1995

[48] G Betti and V Verma ldquoFuzzy measures of the incidence ofrelative poverty and deprivation a multi-dimensional per-spectiverdquo Statistical Methods and Applications vol 17 no 2pp 225ndash250 2008


extent represent the economic characteristics of residents ofunderdeveloped small cities [1] Mallett reported that eco-nomically disadvantaged groups generally take part in life-sustaining behaviors while the demand for travel to participatein communicative and recreational activities is often sup-pressed [2] Blumenberg and Agrawal pointed out that for low-income groups which form a specific subgroup of economi-cally disadvantaged groups communicative and recreationaltravel increases their travel budget and thereby their burden oflivingerefore low-income groups generally utilize the maintype of travel behavior while the demand for other types oftravel is often suppressed [3]

In many developing countries the travel demand ofeconomically disadvantaged groups is easily ignored Chi-karaishi et al pointed out that the phenomenon of restrainedtravel demand is severe in India Specific economically dis-advantaged groups have lowmobility and spatial distance stillremains the main obstacle that restricts their travel needsExcept for the travel needs caused by school attendance andwork other travel needs of economically disadvantagedgroups cannot be effectively met [4] Salon and Gulyanicompared economically disadvantaged groups in the slums ofIndia with economically advantaged groups and found thateconomically advantaged groups can choose between moretravel methods Furthermore economically disadvantagedgroups can only rely on nonmotorized transportation [5]estudies of Srinivasan and Rogers as well as that of Li showedthat the cost of using private cars in relatively underdevelopedsmall cities is relatively high for most residents consequentlypublic transportation has become a dependent mode oftransportation for residents [6 7]

e current level of prioritization of public transport de-velopment policies in less-developed small cities is not idealGiuliano identified the low level of public transportationprovided (eg low service quality and low accessibility) as themain factor affecting the transportation-related decision-making of economically disadvantaged groups [8]e study ofNuworsoo et al showed that low-income groups experiencestrong dissatisfaction with inadequate public transportationfacilities and with the low frequency of bus departures Inunderdeveloped small cities public transportation does notmanage well to regulate travel equity is results in thecommon situation where the travel rights of economicallydisadvantaged groups cannot be effectively guaranteed [9]Grengs as well as Blumenberg andomas pointed out that thesocial exclusion of economically disadvantaged groups par-ticipating in urban transportation will exert a deeper impact onthe economic and social relationship network thus causing aseries of social problems such as social group events and riots[10 11] e urgent need to solve the travel inequity problemsunderdeveloped small cities are facing has prompted scholarsto conduct relevant travel equity assessments of such cities

2 Literature Review

Equity which originates from the concept of justice withinthe context of Western political philosophy has receivedextensive attention from various fields Related research onresidentsrsquo travel equity stems from the developmental

strategy of the USA that promoted private cars during theldquoPost World War IIrdquo(1946ndash1960) period

Rosenbloom and Altshuler studied the urbanization andmotorization of the USA from 1950 to 1972ey found thatthe US urban population and urban land grew rapidly atgrowth rates of 71 and 176 respectively Moreoverduring this time of growth the corresponding household carownership ratio increased from 52 to 79 and theownership ratio of more than two private cars increasedfrom 7 to 30 respectively [12] Sanchez demonstratedthat the rapid economic development of the USA has in-duced a series of social problems including that black peoplenot only had to face pressures of racial discrimination andhigh unemployment rates but their travel needs had alsobeen severely neglected which triggered the civil rightsmovement At this point many studies began to focus on thetravel needs of ethnic minorities and low-income groupsand the travel equity of urban residents has become thesubject of transportation engineering and related disciplines[13]

Deboosere and El-Geneidy from the Victoria Trans-portation Policy Research Institute have extensively studiedthe issue of travel equity and continuously conducted re-search for many years Deboosere and El-Geneidy dividedtravel equity into three types according to horizontal andvertical dimensions (1) Horizontal equity which involvesequity and egalitarianism (2) vertical equity which involvessocial justice environmental justice and social inclusionand (3) vertical equity regarding mobility needs and abilityIn the process toward achieving travel equity these threedifferent types of travel equity often overlap and diverge withregard to the specific travelerrsquos interest balance is is adynamic process requiring constant balance and coordi-nation [14] Hay showed that horizontal travel equity issuitable for balancing and coordinating the travel needs ofdifferent urban residents in a large area or region whileresearch on vertical travel equity usually uses a specific cityas research object and studies the interior of travel equity[15] From the perspectives of income level social class aswell as ethnic or racial differences studies on the distri-bution of benefits of a specificmode of urban travel belong tothe category of vertical travel equity [16ndash21]

Travel equity assessment from the perspective of sub-jective perception has become a research hotspot includingtravel well-being and travel deprivation ese two con-flicting subjective perceptions form the psychologicalfeedback of the public with regard to travel equity isfeedback not only includes the cognition and demand for theoverall travel supply or a certain aspect but also the emotionsand feelings that emerge during the travel process Conse-quently many aspects are involved such as travel interestsand travel opportunities

Bell showed that the goal of transportation policies is toimprove travel well-being including satisfaction mobilityand accessibility [22] Stanley and Vella-Brodrick foundthat using travel well-being to evaluate travel equity is moremeaningful than assessments based on mobilitye reasonis that the simple improvement of mobility will cause aseries of problems such as traffic congestion and









3 Methodology




31 Model Hypothesis













1113954dki 1113954C minus 1113954ci

1113954C minus 1 1le1113954ci le 1113954C (1)







ci( 11138571113882 1113883

1 minus F

(1)1113882 1113883

(2)





mf μi 1 yi

prime lt 1113954z


⎧⎨

⎩ (3)


mf


μi z2 minus yi


prime le 1113954z2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎩

(4)




Wδ ωδ1ωδ2 ωδk ωδ _k1113872 1113873 (5)


_kk1 ωδk 1



1113936kisinδωδk

δ isin (1 2 3 1113954h) (6)






F(δ)i 1 minus


1113936hωδh|SMδh gt SM11113888 1113889 (7)



(δ)i1113872 1113873 i isin (1 2 3 n) (8)



ζ iprime FSMδ




be calculated by

L(δ)i 1 minus





μ FSM(δ) 1113944

h

δ1α(SMδ)


(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

























capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References



























































3 Methodology




31 Model Hypothesis













1113954dki 1113954C minus 1113954ci

1113954C minus 1 1le1113954ci le 1113954C (1)







ci( 11138571113882 1113883

1 minus F

(1)1113882 1113883

(2)





mf μi 1 yi

prime lt 1113954z


⎧⎨

⎩ (3)


mf


μi z2 minus yi


prime le 1113954z2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎩

(4)




Wδ ωδ1ωδ2 ωδk ωδ _k1113872 1113873 (5)


_kk1 ωδk 1



1113936kisinδωδk

δ isin (1 2 3 1113954h) (6)






F(δ)i 1 minus


1113936hωδh|SMδh gt SM11113888 1113889 (7)



(δ)i1113872 1113873 i isin (1 2 3 n) (8)



ζ iprime FSMδ




be calculated by

L(δ)i 1 minus





μ FSM(δ) 1113944

h

δ1α(SMδ)


(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

























capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References





















































31 Model Hypothesis













1113954dki 1113954C minus 1113954ci

1113954C minus 1 1le1113954ci le 1113954C (1)







ci( 11138571113882 1113883

1 minus F

(1)1113882 1113883

(2)





mf μi 1 yi

prime lt 1113954z


⎧⎨

⎩ (3)


mf


μi z2 minus yi


prime le 1113954z2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎩

(4)




Wδ ωδ1ωδ2 ωδk ωδ _k1113872 1113873 (5)


_kk1 ωδk 1



1113936kisinδωδk

δ isin (1 2 3 1113954h) (6)






F(δ)i 1 minus


1113936hωδh|SMδh gt SM11113888 1113889 (7)



(δ)i1113872 1113873 i isin (1 2 3 n) (8)



ζ iprime FSMδ




be calculated by

L(δ)i 1 minus





μ FSM(δ) 1113944

h

δ1α(SMδ)


(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

























capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References




















































1113954dki 1113954C minus 1113954ci

1113954C minus 1 1le1113954ci le 1113954C (1)







ci( 11138571113882 1113883

1 minus F

(1)1113882 1113883

(2)





mf μi 1 yi

prime lt 1113954z


⎧⎨

⎩ (3)


mf


μi z2 minus yi


prime le 1113954z2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎩

(4)




Wδ ωδ1ωδ2 ωδk ωδ _k1113872 1113873 (5)


_kk1 ωδk 1



1113936kisinδωδk

δ isin (1 2 3 1113954h) (6)






F(δ)i 1 minus


1113936hωδh|SMδh gt SM11113888 1113889 (7)



(δ)i1113872 1113873 i isin (1 2 3 n) (8)



ζ iprime FSMδ




be calculated by

L(δ)i 1 minus





μ FSM(δ) 1113944

h

δ1α(SMδ)


(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

























capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References





















































μ FSM(δ) 1113944

h

δ1α(SMδ)


(δ)i1113872 1113873

n⎡⎢⎣ ⎤⎥⎦

i isin (1 2 3 n)

(11)

























capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References






























































capacity)







Service quality S2



Transportation S3




Travel values S4






Travel cost S6





Liuwu-Cijuelin


















FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References



































































FSM7

FSM6

FSM5

FSM4

FSM3

FSM2

FSM1


035

04

045

05




0 5 10 20km

Liuwu-Cijuelin area

Duilong area

N

W E

SZhucheng area

Baidian-Dazi area

Legend




6 Conclusions








Data Availability




Acknowledgments




References





















































6 Conclusions








Data Availability




Acknowledgments




References




















































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