research article risk determination, prioritization, and...

Research ArticleRisk Determination, Prioritization,and Classifying in Construction Project Case Study:Gharb Tehran Commercial-Administrative Complex

Azadeh Sohrabinejad1 and Mehdi Rahimi2

1University of Science and Technology of Iran, Unit 3, No. 59, 38th Street, Gisha Avenue, Tehran 14489 43593, Iran2Bordeaux University, France

Correspondence should be addressed to Azadeh Sohrabinejad; [email protected]

Received 26 May 2015; Revised 18 August 2015; Accepted 8 September 2015

Academic Editor: Eric Lui

Copyright © 2015 A. Sohrabinejad and M. Rahimi. This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work isproperly cited.

Construction projects play an important role in infrastructure projects in developing countries. According to type, size, andcomplexity of the project, the number and importance of each risk could be different and many projects cannot reach the projectgoals due to exposure to multiple risks. Many papers have been published on the subject of risk management in constructionprojects; unfortunately most of them have not been implemented in practical conditions. The aim of this study is to identify andprioritize risks in construction projects.The classical approach used probability and impact for risk assessment, but these criteria donot sufficiently address all aspects of projects risks and there might be a relationship between different criteria.This study proposesthe hierarchical dependencies between criteria. A case study of construction project is presented to illustrate performance andusage of the proposed model. Utilizing library studies and interview with experts, managers, and specialists, decision criteria wereidentified through brain storming. Risks were categorized by the experts into eleven risks. Important risks were evaluated based onthe fuzzy ANP, fuzzy DEMATEL, and fuzzy TOPSIS methods. The proposed model is more suitable than the traditional decision-making methods in prioritizing risk concerning cost, time, and quality.

1. Introduction

The risk management can be defined as a process to identify,analyze, and respond to project risks in order to enhanceopportunities and reduce threats affecting the objectivesof the project. The first step of risk management is riskidentification and the next steps can be risk analysis, riskprioritization, and selecting appropriate strategy for dealingwith risks.

Construction projects are very risky due to the amountof money invested in them which shows the necessity ofidentification of risk drivers, the level of each risk effect,intensity of the influence of the risk on the project, and theprobability of each risk. Finally, based on these evidences, theappropriate action should be selected by project managers toreduce the loss of projects.

In the case that project managers encounter lots ofrisk drivers, fuzzy technique is a suitable solution for risk

management. Additionally, using fuzzy technique is veryhelpful to manage uncertain conditions. One of the charac-teristics of our model in this research is that all aspects ofthe projects are concerned which is very important in megaprojects. Cost, time, and quality are the main elements ofproject success which should be concerned.

In this paper, by using fuzzy technique, we tried to presentamethod to identify and prioritize project risks in the ProjectLife Cycle of construction projects and consequently helpmanagers in decision-making. As a case study, we used aconstruction project in the west of Tehran and based on theproject owner request we do not disclose the company’s infor-mation. In following sections, firstly, problem statement andimportance of research are described. Secondly, a brief reviewof literature in riskmanagement, risk identification, and fuzzytechnique is done. As our research methodology, we usedANP to define appropriate weight for each factor, DEMATEL

Hindawi Publishing CorporationJournal of Construction EngineeringVolume 2015, Article ID 203468, 10 pageshttp://dx.doi.org/10.1155/2015/203468

2 Journal of Construction Engineering

to identify network of criteria and also a supporter of ANPmethod, and finally TOPSIS to rank subcriteria.

2. Literature Review

Risk is an event or a probable situation, the occurrenceof which can have effect on project objectives [1]. Theoccurrence of a riskmay have different reasons like economicfluctuation, financial crisis, social changes, and politicalissues. Also changes in stockholder relationship can be veryeffective in increasing or decreasing the risk level in projects[2].

Although every construction project has different risks,there are lots of common risks among construction projects.Every project has three main items of cost, time plan, andquality in its objectives and related risks to them are the mostcommon risks.

The construction industry is one of the most importantcriteria in a country development. Establishment of allinfrastructures like roads, power plants, mega projects, andso many other projects needs construction as a part of it [3].

Some researchers believe that construction projectsencounter risks more than other projects which are unavoid-able but manageable [4]. Numerous stakeholders, long timeof production, and necessity of interactions between allinternal and external parts of a project are the main factorswhich increase risks in construction projects [5].

The literature review on previous studies of risk manage-ment shows that only a few studies at least in the academiclevel of studies about construction projects risks focusedon it. Lack of risk management knowledge and also usingsystematic approach of identification and solving the riskissues in the field of construction projects are very obviousin previous studies [6, 7].

There are different categories of risks. Perry and Hayescategorized the risks into three main drivers, namely, sub-contractors, consultants, and customers [2]. Cooper andChapman classified the risks in two categories of primaryrisks and secondary risks [8]. US Department of Energycategorized the risks based on the point of risk effect[1].

Abdou divided construction risks into three categoriesof financial risks, time risks, and design risks [9]. Rezakhanidefined eight accounting risks based on the questionnaire hedistributed among project experts [10]. Carr and Tah usedhierarchical organization to categorize risks into two groupsof internal and external risks [11]. Chapman categorized risksinto four groups of environmental, industrial, customers,and project [12]. Shen et al. introduced six groups of riskaccording to the content of the risks including finance, legal,management, market, policy, and politic [13]. Chen et al.categorized fifteen main risks of projects into three maincategories, namely, resource factors,management factors, andparent factors [14].

Assaf and Al-Hejji defined the project risk elements aseffective factors in delay of projects [15]. Dickmen et al. usedcause-effect diagram to categorize risks of projects [16]. Zenget al. categorized the risk drivers into four groups of human,raw material, instruments, and work yard [17].

Nieto-Morote and Ruz-Vila used fuzzy AHP approachfor risk evaluation in their study. Based on a distributedquestionnaire, they gathered expert ideas and categorizedthe project risks into four groups of implementation risks,resources risks, engineering risks, andmanagement risks [18].Rezakhani on his study usedRisk Breakdown Structure (RBS)to categorize and rate the risks [10].

Tummala and Burchett used Work Breakdown Structure(WBS) to identify project risks of high voltage transmissionlines and categorized all risks into six groups of finance andeconomy, environmental and political, design, construction,physical, and unexpected events [19].

In this study, 160 common risks were collected fromliterature review that could affect the time schedule, cost,and quality in construction project (Appendix) [1–3, 6, 9–11, 15, 16, 20–25].

3. Research Methodology

3.1. ANP. Just like AHP approach, Saaty also introducedANP method which was an extended form of AHP whileAHP presents a framework with unidirectional hierarchicalconnections used in multicriteria decision analysis. ANP isa mathematical theory that can systematically overcome allkinds of dependencies [26].

3.2. Fuzzy ANP Method. In the proposed algorithm, fuzzyANP (FANP) will be used to determine the degree of impor-tance of each of these indicators of prioritization in improve-ment projects. FANP is a useful method in case whichprovides a framework for dealing with decision-makingproblems within which assumptions about dependenciesbetween criteria and alternatives are unnecessary [27]. Inthis method, pairwise comparison matrix for each row of thematrix is filled with the triangular fuzzy numbers. Also, theamount of each parameter is calculated as a triangular fuzzynumber.

3.3. Fuzzy DEMATEL. In this research DEMATEL techniqueis used, too.TheDecision-Making Trail and Evaluation Labo-ratory (DEMATEL) analyzed the criteria causal relationshipsand used diagrams to show the weights of criteria. This tech-nique was very helpful to solve the problems based on graphtechnique. Lately, researchers have found that DEMATELcould not be useful to solve uncertainty problems. Therefore,they suggested fuzzyDEMATELmethod.The recentmethod,using fuzzy linguistic variables, solves uncertainty problems[14].

3.4. TOPSIS. The Technique for Order of Preference bySimilarity to Ideal Solution (TOPSIS) is a MCDM methodwhich evaluates 𝑚 alternatives with 𝑛 criteria. Based onTOPSIS concept and logic, the evaluated alternative shouldhave the shortest distance to positive ideal solution andlongest distance to negative ideal solution. According to thislogic, the closer solutions to the positive ideal have betterranking.

Journal of Construction Engineering 3

Riskprioritization

Quality Cost Time

PartnersResources

andequipment

Humanresources

Planningand

scheduling

Projectmanagement

Execution Design PoliticalEconomic

factorsLegalfactors

Environmentaland social

Figure 1: Analytic network process of risks in construction project.

3.5. Data Collection Instrument. Data were collected throughquestionnaires and interviews. The present study uses belowmethod for data collecting:

(1) Expert interviews.(2) Field study (questionnaire).(3) Literature review.

Four questionnaires were used for data collecting contained:identifying risk questionnaire, paired comparisons basedon fuzzy ANP, fuzzy DEMATEL questionnaire, and fuzzyTOPSIS questionnaire. The result of the reliability measuredwith Cronbach’s alpha in risk identification questionnairewas 𝛼 = 0.963. Questionnaires are generally accepted asreliable when Cronbach’s alpha is higher than 0.7. In otherquestionnaires, compatibility is measured.

Research population contains five project teams andeach team consists of a project manager, technical expert,deputy executive, project office manager, execution super-visor, and financial manager. For paired comparisons, tenexperienced experts specializing in the construction industrywere selected.

4. Case Study

After about three years, Gharb Tehran Commercial-Administrative Complex had only five percent progress. Theinability of the company to handle the risks causes delays inthe project. Therefore, it is necessary to establish a system forthe identification and management of the risks which helpsthe company to find out efficient solutions against differentkinds of risks.

Literature review and using Delphi technique for inter-viewing and gathering data from fourteen experts withintheir domain of risk expertise and a minimum of ten yearsof experience in construction projects led us to identify risksin this research. Experts have recommended sixty-seven riskswhich are divided into eleven groups.

Literature review helped us to find out 160 risks withinpast studies (see Table 4). In order to collect the opinionof experts, a questionnaire has been prepared getting theprobability of occurrence for each risk. Moreover, the experthas been asked if the questionnaire is comprehensive andif there is a risk that projects are dealing with and was notmentioned in the questionnaire. After collecting comments,a new list of risks has been developed. The results of thisquestionnaire have been compiled and analyzed and basedon the responses another questionnaire has been developed,which wasmailed back to the experts.The experts were askedagain to leave comments, give suggestions, and answer thequestions. The responses to this second questionnaire werecompiled and analyzed when a consensus has been reachedon risks and a list of 67 risks in eleven groups was preparedas per Figure 1.

ANP method can solve dependency issues and feedbackrelations among multiple criteria.Thus, this study applies theDEMATEL to establish the correlation between the mutualeffects of the criteria and alternatives (group of risks) and usesANP to determine the weight of each group of the risks. Theresearch processes and architecture are shown in Figure 2.

For finding the interrelations between different criteria,experts were asked to indicate the degree of direct influenceof all criteria and alternatives. An average matrix was derivedthrough the mean of the same criteria in the various directmatrices of the experts Table 1.

For normalizing the average matrix, the following for-mula was used:

�̃�𝑖𝑗=

�̃�𝑖𝑗

𝑟

= (

𝑙

𝑖𝑗

𝑟

,

𝑚

𝑖𝑗

𝑟

,

𝑢

𝑖𝑗

𝑟

) = (𝑙

𝑖𝑗, 𝑚

𝑖𝑗, 𝑢

𝑖𝑗) ,

𝑟 = max1≤𝑖≤𝑛

(

𝑛

∑

𝑗=1

𝑢𝑖𝑗) .

(1)


Construction projects risk

Sanction

War

Change in governmental

rules

Design changes

Humanresources

EconomicfactorsLegal factors

Environmental and social

Political Design ExecutionProject

managementPlanning and scheduling

Resources and equipment

Contractors financial failures

Strike

Rules changes

Ambiguity in the rules

Environmental risks

Unstable security situation

Change in negotiation

trend

Delays in payments

Lack of moderator

Legal disputes

Investment problems

Currency change rate

Economical instability

Payment delay

Governmental changes

Nonqualified designers

Hurry in design

Misdesign

Delay in design

Deviations between spec.

and implementation

Losingexperienced

staffsChange in managerial

methodsNot to assign

tasks to experienced

staff

Inappropriate project team

Rush at auction

Inappropriate goals and objectives definitions

Inefficient planning

Estimation/planning errors

Wrong time planprediction

Human resources turnover

Lack of specialists

Equipment performance

Machine failure

Inappropriate material and instruments

Environmental instability

Project closure

Permits and licenses

Delayed,incomplete, and

incorrect reviews

Natural disasters Inflation

Delays in resolving disputes

Events during execution

Damage to property and

persons

Delays in executive plan confirmation

Landslides

Supplying spare parts problems

Lack of machines and

equipment

Changes in materials during

construction

Materials quality

Lack of materials

Delay in material supply

Partners

Delay of consultants

Delay in decision-making

(owner)

Interference by the owner

Delay in payment to contractorsChallenges

between stakeholders

Lack of consultant

knowledge on terms and conditions

Method of tendering and

vendor selection

Lack of mediators to

solve problems

Poor communication between project

parties

Contractors delay

Contractors mismanagement

Weak workshop management

Contractors lack of experience

Contractor financial power

Figure 2: Risk Breakdown Structure for construction projects.

Table 1: Average matrix of interrelations of criteria.

Time Cost QualityTime (0.000, 0.000, 0.000) (0.175, 0.425, 0.675) (0.675, 0.925, 1.000)Cost (0.150, 0.400, 0.650) (0.000, 0.000, 0.000) (0.650, 0.900, 1.000)Quality (0.325, 0.575, 0.825) (0.625, 0.875, 1.000) (0.000, 0.000, 0.000)

After calculating above matrix, total relation matrix wascomputed by the following formula:

𝑇 = lim𝑘→+∞

(�̃�1⊕ �̃�2⊕ ⋅ ⋅ ⋅ ⊕ �̃�

𝑘) . (2)

Each cell of thematrix is a triangular fuzzy number calculatedas follows:

[𝑙𝑡

𝑖𝑗] = 𝐻

𝑙× (1 − 𝐻

𝑙)−1,

[𝑚𝑡

𝑖𝑗] = 𝐻

𝑚× (1 − 𝐻

𝑚)−1,

[𝑢𝑡

𝑖𝑗] = 𝐻

𝑢× (1 − 𝐻

𝑢)−1.

(3)

In these formulas 𝐼 is unit matrix; 𝐻𝑙, 𝐻𝑚, and 𝐻

𝑢are 𝑛 × 𝑛

matrix. 𝐻𝑙, 𝐻𝑚, and 𝐻

𝑢are lower limit, medium value, and

upper limit of the triangular fuzzy number related to thematrix𝐻:

𝐷 = (𝐷𝑖)𝑛×1

=[

[

𝑛

∑

𝑗=1

̃𝑇𝑖𝑗]

]𝑛×1

,

�̃� = (�̃�𝑖)1×𝑛

= [

𝑛

∑

𝑖=1

̃𝑇𝑖𝑗]

1×𝑛

.

(4)

�̃�𝑖shows the row sum of 𝑖th row of matrix 𝑇 and shows the

sum of direct and indirect effects of the criteria on the othercriteria.𝐷

𝑖similarly shows the column sum of 𝑗th column of

matrix𝑇 and shows the sum of direct and indirect effects thatcriterion 𝑗 has received from the other criteria. In addition,when 𝑖 = 𝑗 (i.e., the sum of the row and column aggregates),(�̃�𝑖+𝐷𝑖) provides an index of the strength of influences given

and received. It means that (�̃�𝑖+ 𝐷𝑖) shows the degree of

Journal of Construction Engineering 5Eff

ect

1.0

0.8

0.6

0.4

0.2

0.0

−0.2

−0.4

−0.6

−0.8

−1.0

Time

Cost

Quality

11 11.5 12 12.5 13 13.5

Figure 3: DEMATEL cause-effect diagram for criteria.

1.5

1.0

0.5

0.0

−0.5

−1.0

−1.5

Political

DesignLegal factorsPartners

Economic factors

Human resourcesResources

and equipment

Planning andscheduling Environmental

and social

Execution

Projectmanagement

1 2 3 4 5 6

Figure 4: DEMATEL cause-effect diagram for group of risks.

the central role that factor 𝑖 plays in the problem. If (�̃�𝑖−𝐷𝑖) is

positive, then factor 𝑖 is affecting other factors, and if (�̃�𝑖−𝐷𝑖)

is negative, then factor 𝑖 is being influenced by other factors.Cause-effect diagram is drawn after defuzzification of thefuzzy number �̃�

𝑖+ 𝐷𝑖, �̃�𝑖− 𝐷𝑖.

Figure 3 illustrates the importance (the horizontal axis)and influence and effect (vertical axis) on each criterion. Asseen in the diagram, time is effective and quality and cost areinfluential.

Similarly, causal relationship between eleven groups ofrisks in construction projects is determined by using fuzzyDEMATEL technique.

As seen in Figure 4, the criteria of political, legal factors,design, financial, partners, and staffing are at the top ofthe axis. Therefore, these factors are more influential thanother factors. In other words, these are the cause. On theother hand, project management, resources and equipment,planning and implementation, and social environment are atthe bottom of the diagram. Among these factors, the mostinfluential was criteria of political and social environmentfactors that had the greatest influence.

In the next step, the fuzzy ANP method is used todetermine the relative weights of a set of the evaluationcriteria and obtaining the weight of eleven groups of risks. Inorder to achieve the purpose of this research, experts wereasked for pairwise comparison between criteria that couldilluminate the amount of vitality/impact. The relative vitalityquality can be resolved utilizing a scale of fuzzy numbers tospeak to equivalent significance to great critics.

In this paper, Gogus and Boucher technique have beenused to calculate compatibility. In this method, for investi-gating the compatibility of two matrices (mean number andfuzzy number range), each fuzzy matrix should be deviatedinto two matrices. First matrix contains medium value 𝐴𝑚 =[𝑎𝑖𝑗𝑚] and second matrix contains geometric mean of the

high and low numbers of triangular fuzzy numbers 𝐴𝑔 =√𝑎𝑖𝑗𝑢

⋅ 𝑎𝑖𝑗𝑙.

Weight vector matrix is calculated as follows:

𝑤𝑚= [𝑤𝑚

𝑖] 𝑤

𝑚

𝑖=

1

𝑛

𝑛

∑

𝑗=1

𝑎𝑖𝑗𝑚

∑𝑛

𝑖=1𝑎𝑖𝑗𝑚

,

𝑤𝑔= [𝑤𝑔

𝑖] 𝑤

𝑔

𝑖=

1

𝑛

𝑛

∑

𝑗=1

√𝑎𝑖𝑗𝑢⋅ 𝑎𝑖𝑗𝑙

∑𝑛

𝑖=1√𝑎𝑖𝑗𝑢⋅ 𝑎𝑖𝑗𝑙

.

(5)

Largest eigenvalues for any matrix are calculated by using thefollowing formulas:

𝜆𝑚

max =1

𝑛

𝑛

∑

𝑖=1

𝑛

∑

𝑗=1

𝑎𝑖𝑗𝑚(

𝑤𝑚

𝑗

𝑤𝑚

𝑖

) ,

𝜆𝑚

max =1

𝑛

𝑛

∑

𝑖=1

𝑛

∑

𝑗=1

𝑎𝑖𝑗𝑚(

𝑤𝑚

𝑗

𝑤𝑚

𝑖

) .

(6)

And then the compatibility of eachmatrix is calculated by thefollowing formulas:

CI𝑚 =(𝜆𝑚

max − 𝑛)

(𝑛 − 1)

,

CI𝑔 =(𝜆𝑔

max − 𝑛)

(𝑛 − 1)

.

(7)

To calculate the incompatibility rate (CR), the followingequation is used:

CR𝑔 = CI𝑔

RI𝑔,

CR𝑚 = CI𝑚

RI𝑚.

(8)

The result will be comparedwith 0.1 threshold. If both of theseindexes were less than 0.1, fuzzy matrix is incompatible. Theamount of CR should be lower than 0.1.

For finding out the indexes’ weight, fuzzy ANP statisticalmethod will be used. According to super matrix, four stepshave been released for calculating the components’ weight.

In the first step, geometrical mean of respondents’ paircomparisons about criteria is calculated. Then in the secondstep eigenvectormust be calculated. For calculating eigenvec-tor of all summed pair comparisons tables, logarithmmethodof minimum square roots will be used as

𝑤𝑠

𝑘=

(∏𝑛

𝑗=1𝑎𝑠

𝑘𝑗)

1/𝑛

∑𝑛

𝑖=1(∏𝑛

𝑗=1𝑎𝑚

𝑖𝑗)

1/𝑛, 𝑠 ∈ {𝑙, 𝑚, 𝑢} ,

𝑤𝑘= (𝑤𝑙

𝑘, 𝑤𝑚

𝑘, 𝑤𝑢

𝑘) 𝑘 = 1, 2, 3, . . . , 𝑛.

(9)


Table 2: Matrix of final weights of the group of risks.

Group of risks Fuzzy weight Final relative weight RankEconomic factors (0.0059, 0.1122, 4.5749) 0.1084 1Project management (0.0059, 0.1134, 4.5680) 0.1084 2Partners (0.0061, 0.1089, 4.2552) 0.1012 3Execution (0.0047, 0.0969, 4.1197) 0.0972 4Human resource (0.0047, 0.0969, 4.1197) 0.0970 5Political (0.0038, 0.0820, 3.7043) 0.0870 6Legal factors (0.0036, 0.0816, 3.6879) 0.0866 7Environmental and social (0.0032, 0.0753, 3.5225) 0.0825 8Resources and equipment (0.0029, 0.0722, 3.4371) 0.0804 9Planning and scheduling (0.0023, 0.0657, 3.2821) 0.0765 10Design (0.0026, 0.0657, 3.2078) 0.0749 11

The third step is formation of eigenvector’s matrixes; thesematrixes include eigenvectors obtained from pair compar-isons of the second step.

The fourth step is calculation of final weights of thelevels Table 2. In order to calculate final weight of each level’scomponent,𝑊

𝑖= 𝑊𝑖𝑖×𝑊𝑖(𝑖−1)

×𝑊∗

𝑖−1.

5. Prioritizing Risk Using FuzzyTOPSIS Technique

In the previous section, eleven groups of construction riskpriorities were set. This section aims to rank risks amongeleven groups of risks with conflicting criteria including time,cost, and quality which can help managers and decisionmakers to find solutions.

First, experts’ opinions were collected. Because of theverbal expressions, their opinions were ambiguous. In orderto use them, it is better to convert these expressions into fuzzynumbers. Decision matrix is created.

In the next step, the fuzzy decision matrix should benormalized. The raw data were normalized utilizing linearscale transformation to bring the different criteria scales intoan analogous scale. The normalized fuzzy decision matrix iscalculated by the following formula:

𝑟𝑖𝑗= (

𝑎𝑖𝑗

𝑐∗

𝑗

,

𝑏𝑖𝑗

𝑐∗

𝑗

,

𝑐𝑖𝑗

𝑐∗

𝑗

) 𝑗 ∈ 𝐵,

𝑐∗

𝑗= max 𝑐

𝑖𝑗if 𝑗 ∈ 𝐵,

𝑟𝑖𝑗= (

𝑎−

𝑗

𝑐𝑖𝑗

,

𝑎−

𝑗

𝑏𝑖𝑗

,

𝑐𝑎−

𝑗

𝑐𝑖𝑗

) 𝑗 ∈ 𝐶,

𝑎−

𝑗= min 𝑎

𝑖𝑗if 𝑗 ∈ 𝐶.

(10)

Then, the weighted normalized matrix should be computed.The weighted normalized value𝑉 is calculated by the follow-ing formula:

Ṽ𝑖𝑗= 𝑟𝑖𝑗⋅ 𝑤𝑗

𝑖 = 1, 2, . . . , 𝑚, 𝑗 = 1, 2, . . . , 𝑛. (11)

In this paper, experts’ opinions were given equal weight.

As the fourth step, the fuzzy positive ideal solution (FPIS)and fuzzy negative ideal solution (FNIS) should be computedby using the following formulas:

𝐴+= (Ṽ∗1, Ṽ∗2, . . . , Ṽ∗

𝑛) ,

𝐴−= (Ṽ−1, Ṽ−2, . . . , Ṽ−

𝑛) .

(12)

In the fifth step, the distance of each alternative from FPISand FNIS should be calculated as follows:

𝑑∗

𝑖=

𝑛

∑

𝑗=1

𝑑 (Ṽ𝑖𝑗− Ṽ∗𝑗) 𝑖 = 1, 2, . . . , 𝑚,

𝑑−

𝑖=

𝑛

∑

𝑗=1

𝑑 (Ṽ𝑖𝑗− Ṽ−𝑗) 𝑖 = 1, 2, . . . , 𝑚.

(13)

In the next step, the closeness coefficient (CC𝑖) of each

alternative should be calculated:

CC𝑖=

𝑑−

𝑖

𝑑∗

𝑖+ 𝑑−

𝑖

𝑖 = 1, 2, . . . , 𝑚. (14)

CC𝑖represents the distances to the fuzzy positive ideal

solution𝐴+ and the fuzzy negative ideal solution𝐴− simulta-neously.

In the final step, the final list of responses for eachimportant risk would be prepared by ranking the differentalternatives according to the closeness to coefficient CC

𝑖in

decreasing order.The best alternative is the closest to the FPISand the farthest from the FNIS.

The result has been shown in Table 3.

6. Conclusion

Themain objective of this research was identifying construc-tion project risks and also developing a method to prioritizethe risks. As all companies have limited resources to manageand solve all the risks, the prioritization of the risks isunavoidable. Assignment of resources tomanage risks shouldbe done based on the priorities and from the top of the list.

As the classic approach to prioritize and manage risksof projects, only probability and effect of each risk are


Table3:Risk

prioritizationforc

onstr

uctio

nprojects.

Prioritizationof

riskgrou

p1

23

45

67

89

1011

1213

14

1Econ

omic

factors

Inflatio

nAnn

ualbud

get

revisio

nCu

rrency

change

rate

Con

tractors

financial

failu

res

Econ

omical

insta

bility

Investm

ent

prob

lems

2Project

managem

ent

Change

inmanagerial

metho

ds

Losin

gexperie

nced

staffs

Inapprop

riate

projectteam

Not

toassig

ntasksto

experie

nced

staff

Inapprop

riate

goalsa

ndob

jectives

defin

ition

s

Rush

atauction

3Partners

Interfe

rence

bytheo

wner

Delay

ofconsultants

Delay

indecisio

n-making

(owner)

Delay

inpaym

entto

contractors

Challeng

esbetween

stakeho

lders

Lack

ofconsultant

know

ledgeo

nterm

sand

cond

ition

s

Metho

dof

tend

ering

andvend

orselection

Poor

commu-

nicatio

nbetween

projectp

artie

s

Lack

ofmediators

tosolve

prob

lems

Con

tractors

delay

Con

tractors

mism

anagem

ent

Weak

worksho

pmanagem

ent

Con

tractors

lack

ofexperie

nce

Con

tractor

financial

power

4Ex

ecution

Delaysin

executive

plan

confi

rmation

Delayed,

incomplete,

andincorrect

review

s

Project

closure

Perm

itsand

licenses

Events

durin

gexecution

Deviatio

nsbetweenspec.

and

implem

entatio

n

Inapprop

riate

materialand

instr

uments

Environm

ental

insta

bility

Dam

age

to prop

erty

and

person

s

Land

slides

5Hum

anresources

Hum

anresources

turnover

Lack

ofspecialists

6Po

litical

Sanctio

nGovernm

ental

changes

Change

ingovernmen-

tal

rules

War

7Legalfactors

Legal

disputes

Change

innegotia

tion

trend

Delaysin

paym

ents

Delaysin

resolving

disputes

Lack

ofmod

erator

8En

vironm

ental

andsocial

Rules

changes

Ambiguity

inther

ules

Strik

eEn

vironm

ental

risks

9Re

sourcesa

ndequipm

ent

Changesin

materials

durin

gconstructio

n

Delay

inmaterial

supp

ly

Lack

ofmachines

and

equipm

ent

Equipm

ent

perfo

rmance

Supp

lying

sparep

arts

prob

lems

Materials

quality

Machine

failu

reLack

ofmaterials

10Planning

and

schedu

ling

Estim

ation/

planning

errors

Wrong

time

plan

predictio

n

Ineffi

cient

planning

11Design

Delay

indesig

nDesign

changes

Hurry

indesig

nMisd

esign

Non

qualified

desig

ners


Table 4: All project risks categorization gathered from literature review.

Environmental and social Legal factors Economic factors

(i) Brutality(ii) Assaults(iii) Neglect(iv) Seasonal work(v) Unstable security situation(vi) Environmental pollution(vii) Incorrect or incompleteenvironmental analysis

(i) Disputes(1) Delays in the analysis of disputes(2) Legal disputes between thestakeholders involved in theconstruction project(3) Lack of mediators to acceleratesolving of dispute(ii) Contracts(1) Delays in payment(2) Ambiguities in the contract

(i) Inflation(ii) Investment(iii) Changing currency value(iv) Economic instability(v) Changing rules and standards(vi) Contractor financial failure(vii) Unmanaged cash flow(viii) Consulting cost(ix) Political interruptions(x) Market situation(xi) Work law ambiguities

Political Design Execution

(i) New government legislation ornew rules(ii) Exchange rate fluctuations(iii) Monopoly of raw materials due to theunexpected political conditions(iv) Internal and external politics(v) War(vi) The influence of pressure groups andlobbying by interest groups(vii) Sanction

(i) Nonqualified designer(ii) Incorrect choice of raw materials(iii) The need for design based onexceptions(iv) Errors in estimating/scheduling(v) Out-of-date documents for design(vi) Complexity of design phase ofproject(vii) Duplication(viii) Design changes(ix) Inconsistency between registry ofvalues, design, and specifications(x) Hurry in design(xi) Changes in process of works

(i) Delays in executive plan confirmation(ii) Available resources(iii) Events(iv) Bad design(v) Deviations between spec. andimplementation(vi) Incorrect size and values(vii) The complexity of the projectimplementation(viii) Difficulty in accessing the project yard(ix) The difference between the actual valueswith the values in the contract(x) Poor weather conditions(xi) Installation of equipment(xii) Permits and licenses(xiii) Surface and subsurface water condition(xiv) Implementation method(xv) Events during execution(xvi) Delayed, incomplete, and incorrectreviews(xvii) Contradiction of cost, time, scope,and qualitative objectives

Unexpected and nonpreventable events Project management Contract

(i) Flood(ii) Fire(iii) Earthquake(iv) Lightning

(i) Losing experienced staffs(ii) Change in managerial methods(iii) Not to assign tasks to experiencedstaff(iv) Many projects to manage(v) Inappropriate project team(vi) Mismanagement of contracts(vii) Rush at auction(viii) Commands to change withoutdocument

(i) Changing priorities in existing programs(ii) Changes in the budget for the financialyear(iii) Late changes requested by shareholders(iv) New shareholders(v) Cheating(vi) Ambiguity of planning

Planning and scheduling Human resources Resources and Equipment

(i) Conflicting goals of cost, time, quality,and scope(ii) Uncertain constraints and lack ofplanning(iii) Estimation/planning errors(iv) Wrong time plan prediction(vi) Weaknesses in project definition andultimate performance(vii) Lack of specialized staff

(i) Supplying manpower(ii) Efficiency of manpower(iii) Lack of specialists(iv) Human resources turnover

(i) Machinery failure(ii) Machinery performance(iii) Spare parts supply(iv) Low quality equipment(v) Theft of equipment(vi) Lack of access to machinery orequipment(vii) Lack of materials(viii) Delay in supplying materials(ix) Theft of materials


Table 4: Continued.

Owners Contractors Consultants(i) Delay in payments to contractors(ii) Owner interference(iii) Owner’s delay in decision-making(iv) Methods of contractor selection(v) Unsuitable forecast period for projectimplementation(vi) Change in project tasks(vii) Owner’s administrative bureaucracy

(i) Small contractors(ii) Lack of contractors experience(iii) Workshop mismanagement(iv) Inefficient planning(v) Contractor financial power(vi) Errors during execution(vii) Contractors delays(viii) Contractors mismanagement

(i) Lack of consultant knowledge aboutcontract(ii) Delay in the approval of executive plans(iii) Quality control/assurance(iv) Expectations for approval tests andinvestigations(v) Consultants delays

Stakeholders relationships Procurement management Risk management

(i) Conflict between stakeholders

(i) Limited time(ii) Underestimation of requirements(iii) Overestimation of requirements(iv) Misinterpretation of requirements(v) Insufficient budget(vi) Mismanagement of risks(vii) Dishonesty and unethicalrelationship

(i) Inattention to risks(ii) Deficiency of people involved in riskmanagement(iii) Lack of training(iv) Lack of cooperation among teammembers(v) Lack of control and complexity ofchanges(vi) Lack of knowledge(vii) Weak relationship between projectstakeholders(viii) Unavailability of information

Quality management Project initiation risks Control

(i) Low quality due to limited timeframe(ii) Quality of equipment(iii) Manpower productivity(iv) Raw material(v) Construction(vi) Design(vii) Mapping(viii) Laboratory

(i) Unsuitable estimation of customers(ii) Unsuitable estimation ofcustomer’s requirements(iii) Vague definition and constantchanges in the project(iv) Choosing high risk lands(v) Unsuitable marketing(vi) Unsuitable feasibility study(vii) The lack of a precise definition ofthe project

(i) Lack of integrity in control of differentareas(ii) Delays in reporting and identifying thecorrective control(iii) Lack of coordination between thecontrol and implementation(iv) Different levels of control

concerned, but using these two elements is not sufficient andcannot cover all aspects of risk management. Additionally,the above-mentioned items also cannot handle the relationbetween different risk drivers. Choosing AHP method toprioritize the risks is a way to overcome the limitations of theclassic method.

As discussed before, managing our case study in west ofTehran due to high levels of investment on it requires usingadvanced level of risk management. Cost, time, and qualitywere three main items on which managers mostly focus tocontrol the projects, but risk management by itself should benoticed as a factor that affects other items. Accordingly, tofinalize the project and meet predefined objectives in cost,time, and quality, riskmanagement should be concerned par-allel with other objectives. Identification and prioritization ofrisks in this project can be useful as a managerial toolkit toreduce project failures.

In this project also risks of Project Life Cycle have beenidentified and shared with project experts in the mentionedcompany; then all gathered ideas and solutions were sharedwith project managers to reduce project costs.

These results help managers to focus on the most impor-tant risks and problems. Based on the prioritization resultsby experts ideas, from all the 11 groups of identified risks,

financial risks and projectmanagement risks were of themostimportance.

Reducing financial risk in our project needs integratedand quantitative management of finance with focus oneconomic risks which can have an effective role in reducingtotal risk of project.

Project management risk is another important riskamong our priorities whichmainly happens due to the lack ofappropriate experience of the people involved in the projector unsuitable controlling of the human resources. Suggestedsolutions to reduce this risk are increasing the knowledgelevel of the human resources, internal and external train-ing, hiring experienced human resources, establishment ofprojectmanagement software, defining rules and responsibil-ities of the people, and routine reporting from the system. Inthis study, all risks are considered during life cycle of project.For further study, the ranking of risks from the perspectiveof the employer, contractor, and consultant will be proposed.Additionally, giving weight to experts and using statisticalmethods for prioritization of risks are recommended.

Appendix

See Table 4.


Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

References

[1] US Department of Energy, The Owner’s Role in Project RiskManagement, 2005.

[2] J. G. Perry and R. W. Hayes, “Risk and its management inconstruction projects,” Proceedings of the Institution of CivilEngineers, vol. 78, no. 1, pp. 499–521, 1985.

[3] A. H. Yimam, Project management maturity in the constructionindustry of developing countries (the case of Ethiopian contrac-tors) [Ph.D. thesis], University of Maryland, College Park, Md,USA, 2011.

[4] J. Bennett, R. Flanagan, and G. Norman, The Japanese Con-struction Industry, Centre for Strategic Studies in Construction,University of Reading, 1987.

[5] BSI, “Project management—guide to project management inthe construction industry,” PD 6079-4:2006, British StandardsInstitution, 2006.

[6] M. Wolbers, Application of risk management in public worksorganizations in Chile [Ph.D. thesis], Pontifical Catholic Univer-sity of Chile, 2009.

[7] R. Howard and A. Serpell, “Procurement management: analyz-ing key risk management factors,” in Proceedings of the RICSCOBRA 2012 Conference, vol. 1, pp. 1461–1469, Las Vegas, Nev,USA, September 2012.

[8] D. F. Cooper and C. B. Chapman, Risk Analysis for LargeProjects, John Wiley & Sons, Chichester, UK, 1987.

[9] O. A. Abdou, “Managing construction risks,” Journal of Archi-tectural Engineering, vol. 2, no. 1, pp. 3–10, 1996.

[10] P. Rezakhani, “Classifying key risk factors in construc-tion projects,” Bulletin of the Polytechnic Institute of Iasi—Construction & Architecture Section, vol. 62, no. 2, p. 27, 2012.

[11] V. Carr and J. H. M. Tah, “A fuzzy approach to constructionproject risk assessment and analysis: construction project riskmanagement system,”Advances in Engineering Software, vol. 32,no. 10-11, pp. 847–857, 2001.

[12] R. J. Chapman, “The controlling influences on effective riskidentification and assessment for construction design manage-ment,” International Journal of Project Management, vol. 19, no.3, pp. 147–160, 2001.

[13] L. Y. Shen, G. W. C. Wu, and C. S. K. Ng, “Risk assessment forconstruction joint ventures in China,” Journal of ConstructionEngineering and Management, vol. 127, no. 1, pp. 76–81, 2001.

[14] S. Chen, C. Hwang, and F. Hwang, Fuzzy Multiple AttributeDecision Making, vol. 375 of Lecture Notes in Economics andMathematical Systems, Springer, Berlin, Germany, 1992.

[15] S. A.Assaf and S.Al-Hejji, “Causes of delay in large constructionprojects,” International Journal of Project Management, vol. 24,no. 4, pp. 349–357, 2006.

[16] I. Dikmen, M. T. Birgonul, and S. Han, “Using fuzzy risk assess-ment to rate cost overrun risk in international constructionprojects,” International Journal of Project Management, vol. 25,no. 5, pp. 494–505, 2007.

[17] J. Zeng, M. An, and N. J. Smith, “Application of a fuzzy baseddecision making methodology to construction project riskassessment,” International Journal of Project Management, vol.25, no. 6, pp. 589–600, 2007.

[18] A. Nieto-Morote and F. Ruz-Vila, “A fuzzy approach to con-struction project risk assessment,” International Journal ofProject Management, vol. 29, no. 2, pp. 220–231, 2011.

[19] V. M. R. Tummala and J. F. Burchett, “Applying a Risk Manage-ment Process (RMP) to manage cost risk for an EHV transmis-sion line project,” International Journal of Project Management,vol. 17, no. 4, pp. 223–235, 1999.

[20] A. Ismail, A. M. Abd, and Z. B. Chik, “Approach to analyze riskfactors for construction projects utilizing fuzzy logic,” Journalof Applied Sciences, vol. 8, no. 20, pp. 3738–3742, 2008.

[21] B. A. K. S. Perera, I. Dhanasinghe, and R. Rameezdeen, “Riskmanagement in road construction: the case of Sri Lanka,”International Journal of Strategic Property Management, vol. 13,no. 2, pp. 87–102, 2009.

[22] J. H. M. Tah, A. Thorpe, and R. McCaffer, “Contractor projectrisks contingency allocation using linguistic approximation,”Computing Systems in Engineering, vol. 4, no. 2-3, pp. 281–293,1993.

[23] K. Simu, Risk management in small construction projects [Ph.D.thesis], Luleå University of Technology, Luleå, Sweden, 2006.

[24] L. Y. Shen, “Project risk management in Hong Kong,” Interna-tional Journal of Project Management, vol. 15, no. 2, pp. 101–105,1997.

[25] T. Lyons,Project riskmanagement in theQueensland engineeringconstruction industry [Ph.D. thesis], Libraries Australia, 2002.

[26] T. L. Saaty, The Analytic Network Process—Decision Makingwith Dependence and Feedback, University of Pittsburgh, RWSPublications, Pittsburgh, Pa, USA, 1996.

[27] R. P. Mohanty, R. Agarwal, A. K. Choudhury, andM. K. Tiwari,“A fuzzy ANP-based approach to R&D project selection: a casestudy,” International Journal of Production Research, vol. 43, no.24, pp. 5199–5216, 2005.

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