Analysing causal relationships between delay factors in construction projects A case study of Iran

被引:17
作者
Rezaee, Mustafa Jahangoshai [1 ]
Yousefi, Samuel [1 ]
Chakrabortty, Ripon K. [2 ]
机构
[1] Urmia Univ Technol, Fac Ind Engn, Orumiyeh, Iran
[2] UNSW Canberra, Sch IT, ADFA, Campbell, Australia
关键词
Construction projects; Interpretive structural modelling; Causal relationships; Fuzzy data envelopment analysis; Fuzzy cognitive map; Delay factors; FUZZY COGNITIVE MAP; COST OVERRUNS; TIME; SUPPLIER; CRITERIA; INDUSTRY; RANKING; RISKS;
D O I
10.1108/IJMPB-01-2019-0020
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose Analyzing factors of delays in construction projects and determining their impact on project performance is necessary to better manage and control projects. Identification of root factors which may lead to project delay and increased cost is vital at the early or planning stage. Better identification of delay factors at the early stage can help the practitioners to reduce their impacts over the long run. Hence, the purpose of this paper is to propose an intelligent method to analyze causal relationships between delay factors in construction projects. The proposed approach is further validated by a real case study of the construction projects in West Azerbaijan province in Iran. Design/methodology/approach During the first phase, the fuzzy cognitive map (FCM) is drawn to indicate the causal relationships between the delay factors and the evaluation factors. For this purpose, the causal relationships between 20 delay factors and four evaluation factors are considered. Afterward, the effect of each factor on management goals is evaluated by using a hybrid learning algorithm. Delay factors are further prioritized by applying fuzzy data envelopment analysis (FDEA). In the second phase, an interpretive structural modeling (ISM) is employed to determine the root causes of delay factors. Findings Results of the first phase show that "supervision technical weaknesses for overcoming technical and executive workshop problems" and "Inaccurate estimation of workload, required equipment and project completion time" are the most significant delay factors. In contrary, "non-use of new engineering contracts" has the lowest impact on the management goals. Meanwhile, the results of the second phase conclude that factors like "Inaccurate estimation of workload, required equipment and project completion time" "weakness of laws and regulations related to job responsibilities" and "lack of foreseen of fines and encouragements in the contracts" are the most significant root factors of delay in construction projects. Originality/value This paper integrates three methods including FCM method, FDEA and ISM. In the first phase, FCM is drawn according to the experts' opinions and concerning management goals and delay factors. Later, these factors are prioritized according to the results of running the algorithm and using the FDEA model. The second phase, the seven-step in the ISM methodology, is done to identify the root factors. To ensure that the root factors of the delay are at a lower level of hierarchical structure, delay factors are partitioned by drawing the ISM model.
引用
收藏
页码:412 / 444
页数:33
相关论文
共 64 条
[1]  
Al-Hazim N., 2015, International Journal of Engineering Technology, V4, P288, DOI [10.14419/ijet.v4i2.4409, DOI 10.14419/IJET.V4I2.4409]
[2]  
Al-Momani A.H., 2000, INT J PROJ MANAG, V18, P51, DOI [10.1016/S0263-7863(98)00060-X, DOI 10.1016/S0263-7863(98)00060-X]
[3]   The significant factors causing delay of building construction projects in Malaysia [J].
Alaghbari, Wa'el ;
Kadir, Mohd. Razali A. ;
Salim, Azizah ;
Ernawati .
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT, 2007, 14 (02) :192-+
[4]  
Alinaitwe H, 2013, J CONSTR DEV CTRIES, V18, P33
[5]   An integrated Taguchi loss function-fuzzy cognitive map-MCGP with utility function approach for supplier selection problem [J].
Alizadeh, Arash ;
Yousefi, Samuel .
NEURAL COMPUTING & APPLICATIONS, 2019, 31 (11) :7595-7614
[6]   A novel hybrid method based on fuzzy cognitive maps and fuzzy clustering algorithms for grading celiac disease [J].
Amirkhani, Abdollah ;
Mosavi, Mohammad R. ;
Mohammadi, Karim ;
Papageorgiou, Elpiniki, I .
NEURAL COMPUTING & APPLICATIONS, 2018, 30 (05) :1573-1588
[7]   Analysing delay causes and effects in Ghanaian state housing construction projects [J].
Amoatey, Charles Teye ;
Ameyaw, Yaa Asabea ;
Adaku, Ebenezer ;
Famiyeh, Samuel .
INTERNATIONAL JOURNAL OF MANAGING PROJECTS IN BUSINESS, 2015, 8 (01) :198-214
[8]   A PROCEDURE FOR RANKING EFFICIENT UNITS IN DATA ENVELOPMENT ANALYSIS [J].
ANDERSEN, P ;
PETERSEN, NC .
MANAGEMENT SCIENCE, 1993, 39 (10) :1261-1265
[9]  
[Anonymous], INT C EC ADM
[10]  
[Anonymous], 2016, Journal of Construction in Developing Countries, V21, P51, DOI [DOI 10.21315/JCDC2016.21.1.4, 10.21315/jcdc2016.21.1]