Cost Escalation Management In Tertiary Institutions Using Partial Least Squares and Fuzzy Inference System

  • Ayeni Omini Abam Department of Mathematics, Federal University Lafia, Nigeria.
  • Edwin Frank Nsien Department of Statistics, University of Uyo, Uyo, Nigeria
Keywords: Cost, Fuzzy, Institutions, Equation, Modelling

Abstract

Escalation of costs of projects is an integral part of the construction industry that is a vital sector in any economy. The contribution of the construction industry in the Gross National Product aids development. Cost Escalation generates into projects financial loss to both contractors and owners. It stands as the major challenge facing tertiary institutions. Desiring to solve these management problems in Nigerian Institutions, this paper comparatively assesses the escalation of project costs in Tertiary Institutions in Lafia Metropolis using Partial Least Squares-Structural Equation Modelling (PLS-SEM) and Fuzzy Inference System (FIS). The results show for PLS and FIS respectively, that contractors site management related factors has 97.6% and 67% effect on cost overrun, followed by non-human resource related factors with an effect of 94.4% and 67% on cost overrun. The least was information and communication technology related factors having 75.7% and 65% effect on cost overrun. Both fluctuation in price of materials and inadequate monitoring and control has 67.4% effect on cost overrun while delay in preparation and approval of drawings has an effect of 57% on cost overrun. The findings reveal that PLS-SEM is a model that evaluates a data as a collective entity while the FIS does not.

References

Abam, A. O., Ogbonna, E. N., Nsien, E. & Nzeako, G. Project Cost Overrun Management in Universities Using Partial Least Squares-Structural Equation Modelling. Applied Mathematics , 5(4), 108- 113, (2017).

Chitkara, K. K., Construction Project Management-Planning, Scheduling and Controlling, American Journal of
ed.), Tata McGraw Hills. (Chapter 2), (2011).

Love, P. E. D., Raymond, Y. C. T. & David, J. E. Time-Cost relations in Australia Building Construction Projects;
ASCE Journal of Construction Engineering and Management , 2(131), 187-194, (2005).

Choudhury, I., & Phatak, O. 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, (2004).

Al-Najjar, J. M. the Gaza Strip : Factors Influencing Time and Cost Overruns on Construction Projects in Masters Thesis: The Islamic University of Gaza, (2002),
Shreenaath.A, Arunmozhi. S. & Sivagamasundari. R. Prediction of Construction Cost Overrun in Tamil Nadu- A Statistical Fuzzy Approach,
Technical Research, 3(3), 267-275, (2015).
Chin W. Partial Least Squares for Researchers: An Overview and Presentation of Recent Advances Using the PLS Approach. Retrieved from http://disc-nt.cba.uh.edu/chin/indx.html. (2000).

Azhar, N., Farooqui, R. U. & Ahmed, S. M. Cost Overrun Factors in Construction Industry . Proceeding of First International in Pakistan
Countries Conference on Construction in Developing (ICCIDE-1), Karachi, Pakistan, (2008, August).

Kaliba, C., Muya, M. & Mumba, K. Cost Escalation and Schedule Delay in Road Construction Projects in Zambia, International Journal of
Project Management, 5(27 ), 522-531, (2009).

Koushki, P. A., Al-Rashid, K., & Kartam, N. Delays and cost increases in the construction of private residential projects in Kuwait.
Construction Management and Economics , 23(3), 285-294, (2005).

Bubshait, A. A. & Al-Juwait, Y. A. Factors Contributing to Construction Costs in Saudi Arabia. Cost Engineering , 44(5), 30, (2002).

Le - Hoai, L., Lee, Y.D., & Jun, Y. L. Delay and Cost Overruns in Vietnam Large Construction Projects: A Comparison with Other Selected Countries.
KSCE Journal of Civil Engineering, 367-377, (2008).

Sriprasert, E.. Assessment of Cost Control System: Organizations. A Case Study of Thai Construction
Asian Institute of Technology , Bangkok , (2000).

Sharma, S. & Goyal, P. K. Cost Overrun Assessment Model in Fuzzy Environment. Journal of Engineering Research (AJER), 3(7): American
44-53, (2014).

Mitzi (Maritza), P. T. Structural Equation Modeling Approach to Factors that Contribute to the impact MYMATHLAB has on Commitment and Integration of Technology, 65-71, (2008).
Published
2020-02-24
How to Cite
Abam , A. O., & Nsien , E. F. (2020). Cost Escalation Management In Tertiary Institutions Using Partial Least Squares and Fuzzy Inference System. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 2019(2), 631 - 643. Retrieved from http://ijmso.unilag.edu.ng/article/view/597
Section
Articles