A Review of Structural Equation Model for Construction Delay Study

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Structural Equation Modelling (SEM) has been widely used in science social area compared to construction engineering and management field especially in area of delay construction. SEM is a second generation multivariate analysis that has an advance features compare to first generations of analysis tools. First generation techniques suffer with some assumptions such as error measurement is neglected, only observed variable allowed, only for simple model and other limitations. In construction delay study, comprehensive and complex analysis which involves hidden variables need to be considered to get precise results. Therefore, the main objective of this paper is to review the importance of applying SEM for construction delay study. Various papers which were taken from construction delay and construction management studies has been reviewed to observe the suitability of SEM for construction delay study. Outcome of this review reveals that SEM can include latent variable in the analysis model and consider of error measurement as integral part of the model as well as simultaneously analyse theory and measurement in a structural model while it is unobtainable for first generation techniques.  This review proves that SEM can be an appropriate analysis tool for construction delay study.

  • Keywords

    Construction delay; construction management; multivariate analysis; error measurement; Structural Equation Modelling (SEM)

  • References

      [1] G. J. Kikwasi, “Causes and Effects of Delays and Disruptions in Construction Projects in Tanzania,” Australas. J. Constr. Econ. Build. Conf. Ser. Rev., vol. 1, no. 2, pp. 52–59, 2012.

      [2] N. Braimah and I. Ndekugri, “Factors Influencing the Selection of Delay Analysis Methodologies,” Int. J. Proj. Manag., vol. 26, pp. 789–799, 2008.

      [3] R. Ali Khan, M. Shahir Liew, and Z. Ghazali, “Malaysian Construction Sector and Malaysia Vision 2020 : Developed Nation Status,” Procedia - Soc. Behav. Sci., vol. 109, pp. 507–513, 2014.

      [4] F. Beckers, E. Silva, N. Chiara, A. Flesch, J. Maly, and U. Stegemann, “A Risk - Management Approach to a Successful Infrastructure Project,” Singapore, 2013.

      [5] R. Ghazali, “Transport Ministry: KLIA2 Construction Never Experienced Cost Overruns,” The Star Online, 2015. [Online]. Available: https://www.thestar.com.my/news/nation/2015/05/19/klia2-no-cost-overun-minsistry/. [Accessed: 05-Dec-2017].

      [6] The Star, “Bakun Project Firms in Deal to Withdraw All Claims,” The Star Online, 2014. [Online]. Available: http://www.thestar.com.my/business/business-news/2014/08/13/bakun-project-firms-in-deal-to-withdraw-all-claims/. [Accessed: 17-Aug-2017].

      [7] S. Zailani, H. A. M. Ariffin, M. Iranmanesh, S. Moeinzadeh, and M. Iranmanesh, “The Moderating Effect of Project Risk Mitigation Strategies on the Relationship Between Delay Factors and Construction Project Performance Abstract,” J. Sci. Technol. Policy Manag., vol. 7, no. 3, 2016.

      [8] F. Z. Ariffin, “Jambatan ke-2 Dibuka Oktober,” Utusan Online, 2013. [Online]. Available: http://ww1.utusan.com.my/utusan/Ekonomi/20130718/ek_01/Jambatan-ke-2-dibuka-Oktober. [Accessed: 03-Jan-2018].

      [9] R. Hassan and N. Z. Nordin, “Projek RMK-9 dikaji balik - Jambatan Pulau Pinang lewat sebab kos, tanah, reka bentuk – PM,” Utusan Online, 2008. [Online]. Available: http://ww1.utusan.com.my/utusan/info.asp?y=2008&dt=0423&pub=Utusan_Malaysia&sec=Muka_Hadapan&pg=mh_01.htm. [Accessed: 03-Jan-2018].

      [10] G. K. Pall, A. J. Bridge, M. Skitmore, and J. Gray, “Comprehensive Review of Delays in Power Transmission Projects,” Inst. Eng. Technol., vol. 10, no. 14, pp. 3393–3404, 2016.

      [11] H. Doloi, A. Sawhney, K. C. Iyer, and S. Rentala, “Analysing Factors Affecting Delays in Indian Construction Projects,” Int. J. Proj. Manag., vol. 30, pp. 479–489, 2012.

      [12] M. A. Salam, H. J. Staines, D. J. Blackwood, and S. Sarkar, “Analysis of the Relationships Between Causes of Delay in Construction Projects in Bangladesh,” in Proceeding of 17th Annual ARCOM Conference, 5-7 September, University of Salford, UK, 2001, vol. 1, no. September, pp. 619–28.

      [13] K. Wong and V. Vimonsatit, “A Study of the Factors Affecting Construction Time in Western Australia,” Sci. Res. Essays, vol. 7, no. 40, pp. 3390–3398, 2012.

      [14] L. Van Truong, N. M. Sang, and N. T. Viet, “A Conceptual Model of Delay Factors affecting Government Construction Projects,” ARPN J. Sci. Technol., vol. 5, no. 2, pp. 92–100, 2015.

      [15] J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis (7th Edition), 7th ed. Pearson Prentice Hall, 2010.

      [16] N. N. Zainol, “A Structural Model of Green Cleaning Components and Requirements for Green Buildings,” Universiti Teknologi Malaysia, 2016.

      [17] D. W. Barclay and R. Thompson, “The Partial Least Squares (PLS) Approach to Causal Modelling: Personal Computer Adaptation and Use as an Illustration,” Technol. Stud., vol. 2, no. 2, pp. 286–309, 1995.

      [18] J.-B. Yang and S.-F. Ou, “Using Structural Equation Modeling to Analyze Relationships among Key Causes of Delay in Construction,” Can. J. Civ. Eng., vol. 35, no. 4, pp. 321–332, 2008.

      [19] M. Haenlein and A. M. Kaplan, “A Beginner’s Guide to Partial Least Squares Analysis,” Underst. Stat., vol. 3, no. 4, pp. 283–297, 2004.

      [20] P. B. Lowry and J. Gaskin, “Partial Least Squares (PLS) Structural Equation Modeling (SEM) for Building and Testing Behavioral Causal Theory: When to Choose It and How to Use It,” IEEE Trans. Prof. Commun., vol. 57, no. 2, pp. 123–146, 2014.

      [21] D. Gefen, D. W. Straub, and M.-C. Boudreau, “Structural Equation Modeling and Regression : Guidelines for Research Practice,” Commun. Assoc. Inf. Syst., vol. 4, 2000.

      [22] L. Trinchera and G. Russolillo, “On The Use of Structural Equation Models and PLS Path Modeling to Build Composite Indicators,” 2010.

      [23] R. B. Kline, Exploratory and Confirmatory Factor Analysis. New York: Routledge: In Y. Petscher & C. Schatsschneider. (Eds.), Applied Quantitative Analysis in the Social Sciences, 2013.

      [24] H. Doloi, “Analysis of Pre-qualification Criteria in Contractor Selection and their Impacts on Project Success,” Constr. Manag. Econ., vol. 27, no. 12, pp. 1245–1263, 2009.

      [25] A. S. Hussein, “Penelitian Bisnis dan Manajemen Menggunakan Partial Least Squares (PLS) dengan SmartPLS 3.0,” University of Brawijaya, 2015.

      [26] W. W. Chin, B. L. Marcolin, and P. Newsted, “A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and Voice Mail Emotion/Adoption Study,” in Proceedings of the Seventeenth International Conference on Information Systems, 1996, pp. 21–41.

      [27] R. M. Baron and D. a. Kenny, “The Moderator-Mediator Variable Distinction in Social The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations,” J. Pers. Soc. Psychol., vol. 51, no. 6, pp. 1173–1182, 1986.

      [28] H. Aguinis, J. R. Edwards, and K. J. Bradley, “Improving Our Understanding of Moderation and Mediation in Strategic Management Research,” Organ. Res. Methods, vol. 20, no. 4, pp. 665–685, 2017.

      [29] D. Iacobucci, “Everything You Always Wanted to Know about SEM (Structural Equations Modeling) but were Afraid to Ask,” J. Consum. Psychol., vol. 19, pp. 673–680, 2009.

      [30] R. Ho, Handbook of Univariate And Multivariate Data Analysis And Interpretation With SPSS. Boca Raton, Florida: Chapman & Hall/CRC Taylor & Francis Group, 2006.

      [31] D. Gefen and D. Straub, “A Practical Guide To Factorial Validity Using PLS- Graph: Tutorial and Annotated Example,” Commun. Assoc. Inf. Syst., vol. 16, pp. 91–109, 2005.

      [32] C. Nitzl, J. L. Roldan, and G. Cepeda, “Mediation Analysis in Partial Least Squares Path Modeling: Helping Researchers Discuss More Sophisticated Models,” Ind. Manag. Data Syst., vol. 116, no. 9, pp. 1849–1864, 2016.

      [33] D. A. Kenny and C. M. Judd, “Estimating the Linear and Interactive Effects of Latent Variables,” Am. Psychol. Assoc. Inc., vol. 96, no. I, pp. 201–210, 1984.

      [34] K. G. Jöreskog and F. Y. Wallentin, Nonlinear Structural Equation Models: The Kenny–Judd model with Interaction Effects. Lawrence Erlbaum Associates, 1996.

      [35] K. G. Jöreskog and D. Sörbom, LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Lincolnwood, USA, 1993.

      [36] Arbuckle and J. L, Amos 18 User’s Guide. USA, 2009.

      [37] B. M. Byrne, Structural Equation Modeling With EQS: Basic Concepts, Applications, 2nd Editio. New York: Lawrence Erlbaum Associates, Inc., 2006.

      [38] J. Henseler, C. M. Ringle, and M. Sarstedt, Using Partial Least Squares Path Modeling in International Advertising Research: Basic Concepts and Recent Issues. Edward Elgar, 2012.

      [39] Nebojša St. Davčik, “The Use And Misuse Of Structural Equation Modeling in Management Research,” 2007.

      [40] H. Hwang, N. K. Malhotra, Y. Kim, M. A. Tomiuk, and S. Hong, “A Comparative Study on Parameter Recovery of Three Approaches to Structural Equation Modeling,” J. Mark. Res., vol. 47, no. 4, pp. 699–712, 2010.

      [41] H. Hwang and Y. Takane, “Generalized Structured Component Analysis,” Psychom. Sociiety, vol. 69, no. 1, pp. 81–99, 2004.

      [42] F. Buckler and T. Hennig-Thurau, “Identifying Hidden Structures in Marketing’s Structural Models Through Universal Structure Modeling: An Explorative Bayesian Neural Network Complement to LISREL and PLS,” Mark. Res. Manag., vol. 4, no. 2, pp. 47–66, 2008.

      [43] J. F. Hair, M. Sarstedt, T. M. Pieper, and C. M. Ringle, “Applications of Partial Least Squares Path Modeling in Management Journals: A Review of Past Practices and Recommendations for Future Applications,” Long Range Plann., vol. 45, no. 5–6, pp. 320–340, 2012.

      [44] A. Khamis, N. K. K. Kamarudin, M. E. Nor, S. Saharan, and N. M. Asrah, “Covariance Based and Partial Least Square Structural Equation Modeling to Model Job Satisfaction among Lecturers,” Sci. Res. J., vol. 5, no. 3, pp. 19–28, 2017.

      [45] J. Joseph F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications, 2014.

      [46] C. Fornell and F. L. Bookstein, “Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory,” J. Mark. Res., vol. 19, no. 4, pp. 440–452, 1982.

      [47] J. F. Hair, C. M. Ringle, and M. Sarstedt, “Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance,” Long Range Plann., vol. 46, pp. 1–12, 2013.

      [48] K. Bollen and R. Lennox, “Conventional Wisdom on Measurement: A Structural Equation Perspective,” Psychol. Bull., vol. 110, no. 2, pp. 305–314, 1991.

      [49] T. Coltman, T. M. Devinney, D. F. Midgley, and S. Venaik, “Formative versus Reflective Measurement Models: Two Applications of Erroneous Measurement,” J. Bus. Res., vol. 61, no. 12, pp. 1250–1262, 2008.

      [50] D. X. Peng and F. Lai, “Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research,” J. Oper. Manag., vol. 30, no. 6, pp. 467–480, 2012.

      [51] B. Schneider, M. Carnoy, J. Kilpatrick, W. H. Schmidt, and R. J. Shavelson, Estimating Causal Effects Using Experimental and Observational Designs. Washington, D.C.: The Governing Board of the American Educational Research Association Grant Program, 2007.

      [52] K. G. Jöreskog, “Some contributions to maximum likelihood factor analysis,” Psychometrika, vol. 32, no. 4, pp. 443–482, 1967.

      [53] J. F. Hair, C. M. Ringle, and M. Sarstedt, “PLS-SEM: Indeed a Silver Bullet,” J. Mark. Theory Pract., vol. 19, no. 2, pp. 139–152, 2011.

      [54] C. T. B. College, W. W. Chin, B. L. Marcolin, and P. R. Newsted, “A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects : Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion / Adoption Study,” vol. 14, no. 2, pp. 189–217, 2003.

      [55] A. Boomsma and J. J. Hoogland, The Robustness of LISREL Modeling Revisited. A Festschrift in honor of Karl Jöreskog, 2001.

      [56] J. Henseler and W. W. Chin, “A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables using Partial Least Squares Path Modeling,” Struct. Equ. Model., vol. 17, pp. 82–109, 2010.

      [57] B. Xiong, M. Skitmore, and B. Xia, “A Critical Review of Structural Equation Modeling Applications in Construction Research,” Autom. Constr., vol. 49, no. PA, pp. 59–70, 2015.

      [58] K. Molenaar, S. Washington, and J. Diekmann, “Structural Equation Model of Construction Contract Dispute Potential,” J. Constr. Eng. Manag., vol. 126, no. 4, pp. 268–277, 2000.

      [59] L. Zhang and X. Huo, “The Impact of Interpersonal Conflict on Construction Project Performance: A Moderated Mediation Study from China,” Int. J. Oper. Prod. Manag., vol. 26, no. 4, pp. 479–498, 2015.

      [60] S. Helm, A. Eggert, and I. Garnefeld, “Modeling the Impact of Corporate Reputation on Customer Satisfaction and Loyalty Using Partial Least Squares,” in In Handbook of Partial Least Squares, Berlin, Heidelberg: Springer, 2010, pp. 515–534.

      [61] W. Oetomo, “Model of Influence to Delay Construction Projects of Multistoried Buildings Using Multi-Dimensional of Stage with Analysis of Second Order,” J. Basic Appl. Sci. Res., vol. 6, no. 1, pp. 15–25, 2016.

      [62] S. A. Assaf and S. Al-Hejji, “Causes of Delay in Large Construction Projects,” Int. J. Proj. Manag., vol. 24, pp. 349–357, 2006.

      [63] Z. Shehu, I. R. Endut, A. Akintoye, and G. D. Holt, “Cost Overrun in the Malaysian Construction Industry Projects: A Deeper Insight,” Int. J. Proj. Manag., vol. 32, pp. 1471–1480, 2014.

      [64] C. B. Astrachan, V. K. Patel, and G. Wanzenried, “A Comparative Study of CB-SEM and PLS-SEM for Theory Development in Family Firm Research,” J. Fam. Bus. Strateg., vol. 5, pp. 116–128, 2014.




Article ID: 22750
DOI: 10.14419/ijet.v7i4.35.22750

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.