Project Cost Overrun Management in Universities Using Partial Least Squares-Structural Equation Modelling
American Journal of Applied Mathematics
Volume 5, Issue 4, August 2017, Pages: 108-113
Received: May 9, 2017;
Accepted: Jun. 2, 2017;
Published: Jul. 13, 2017
Views 2513 Downloads 166
Abam Ayeni Omini, Department of Mathematics, Faculty of Science, Federal University Lafia, Lafia, Nigeria
Ogbonna Eric Nnamdi, Department of Statistics, Faculty of Science, Abia State Polytechnic, Aba, Nigeria
Nsien Edwin, Department of Statistics, Faculty of Science, University of Uyo, Uyo, Nigeria
Nzeako Gladys, Department of Mathematics, Faculty of Science, Federal University Lafia, Lafia, Nigeria
The construction industry is a very important sector of the Nigerian economy. It contributes significantly to the Gross National Product. Cost overrun is an integral part of the construction industry. It generates in projects financial loss to both contractors and owners (clients). It is an important parameter for success of any project that results to serious sequences. Cost overrun is a chronic problem for tertiary institutions. This is because, it is common for projects not to be completed on time and within the initial project budget. The paper assess the management of project cost overrun, reasons for cost overrun and suggested solutions in selected Public Tertiary Institutions in Lafia Metropolis using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The results show that contractor’s site management related factors has 97.6% effect on cost overrun, followed by non-human resource related factors with an effect of 94.4% on cost overrun. The least was information and communication technology related factors having 75.7% effect on cost overrun. The findings reveal that the PLS-SEM is a model that evaluates a data as a collective entity.
Abam Ayeni Omini,
Ogbonna Eric Nnamdi,
Project Cost Overrun Management in Universities Using Partial Least Squares-Structural Equation Modelling, American Journal of Applied Mathematics.
Vol. 5, No. 4,
2017, pp. 108-113.
Abam, A. O. & Nzeako, G. C., (2017). A comparative study of Project Cost Overrun Management using Partial Least Squares- Structural Equation Modelling and Fuzzy Inference System. Department of Mathematics, Federal University Lafia, Unpublished Undergraduate Project.
Ali, A. S. & Kamaruzzaman, S. N., (2010), “Cost Performance for Building Construction Projects in Klang Valley”, Journal of Building Performance, 1(1), 110-110.
Azhar, N., Farooqui, R. U. & Ahmed, S. M., (2008). Cost Overrun Factors in Construction Industry in Pakistan. Proceeding of First International Conference on Construction in Developing Countries (ICCIDE-1), Karachi, Pakistan, 4-5 August, 499-508, retrieved from http://www.neduet.edu.pk/Civil/ICCIDC-conference%20Proceedings/Papers/051.pdf.
Bubshait, A. A. & Al-Juwait, Y. A., (2002). Factors Contributing to Construction Costs in Saudi Arabia. Cost Engineering, 44(5), 30.
Chin W. (2000). “Partial Least Squares for Researchers: An Overview and Presentation of Recent Advances Using the PLS Approach”, http://disc-nt.cba.uh.edu/chin/indx.html.
Choudhury, I., & Phatak, O., (2004). Correlates of time overrun in commercial construction, ASC Proceeding of 4th Annual Conference, Brigham Young University- provo-Utah, April 8-10. Arabian international Journal of Project Management, 17(2), 101-106.
Kagiri, D. (2005). Time and cost overruns in power projects: A case study of Kenya Electricity Generating Company. Unpublished MBA Project, University of Nairobi.
Kaliba, C., Muya, M. & Mumba, K., (2009). Cost Escalation and Schedule Delay in Road Construction Projects in Zambia, International Journal of Project Management, 5(27), 522-531.
Koushki, P. A., Al‐Rashid, K., & Kartam, N., (2005). Delays and cost increases in the construction of private residential projects in Kuwait. Construction Management and Economics, 23(3), 285-294.
Lee, J. K., (2008). Cost overrun and cause in Korean social overhead capital Projects: Roads, rails, airports and ports. J. Urban Planning. Dev., 2(134), 59-62.
Love, P. E. D., Raymond, Y. C. T. & David, J. E., (2005), Time-Cost Relations in Australia Building Construction Projects; ASCE Journal of Construction Engineering and Management, 2(131), 187-194.
Mitzi (Maritza), P. T., (2008), Structural Equation Modeling Approach to Factors that Contribute to the impact MYMATHLAB has on Commitment and Integration of Technology, 65-71.
Rational Choice Theory (2016). Retrieved from https://www.investopedia.com/terms/r/rational-choice-theory.asp.
Rational Choice Theory (10th November, 2016). Retrieved from https://en.m.wikipedia.org/wiki/Rational_choice_theory.
Rosenfield. Y., (2013), “Root Cause Analysis of Construction Cost Overruns,” Journal of Construction Engineering and Management, 140.
Shreenaath. A, Arunmozhi. S. & Sivagamasundari, R., (2015), “Prediction of Construction Cost Overrun in Tamil Nadu- A Statistical Fuzzy Approach”, International Journal of Engineering and Technical Research, 3(3), 267-275.
Sriprasert, E., (2000). Assessment of Cost Control System: A Case Study of Thai Construction Organizations. Asian Institute of Technology, Bangkok.