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
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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
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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.
Cost, Overrun, Management, Project, Site
To cite this article
Abam Ayeni Omini, Ogbonna Eric Nnamdi, Nsien Edwin, Nzeako Gladys, 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. doi: 10.11648/j.ajam.20170504.12
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