Sensitivity Analysis of Key Cost Performance Determinants Using Extreme Bound Analysis Method
Publication: Journal of Legal Affairs and Dispute Resolution in Engineering and Construction
Volume 15, Issue 1
Abstract
The complex nature of construction projects makes achieving positive outcomes challenging, and cost overruns, which frequently occur in all three construction phases, are one of the major impediments to success. When indicators of cost overruns are determined early in a project, however, strategies for reducing or eliminating them can be adopted. Therefore, this study aimed to identify primary cost performance indicators (CPIs) and assess their robustness during the engineering, procurement, and construction (EPC) phases of heavy industrial projects. To accomplish this, an extensive survey was designed and distributed to experienced construction professionals to gather information on tried and true cost performance indicators they had successfully employed. The chi-square test, two-sample -test, and the Kruskal-Wallis test were used to evaluate their responses, and a final list of cost performance indicators was developed using the all-possible combination regression analysis approach. The robustness or fragility of the indicators was investigated using extreme bounds analysis (EBA), and the results were analyzed using Sala-i-Martin and Leamer’s EBA methods. Because Leamer’s approach concentrates exclusively on the indicators’ extreme boundaries and Sala-i-Martin’s approach considers the entire distribution of the variables, the conclusions were drawn using the Sala-i-Martin method. The results revealed that the three determinants of cost performance indicators in all three construction phases are a project’s alignment, effective management strategies, and the staff turnover rate. Two more robust indicators in all three phases were the fundamental essence of a project and the number of designer/engineering organizations. The study findings will help project managers of construction projects effectively allocate their financial, human, and machinery resources.
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Data Availability Statement
All data generated or analyzed during the study are available from the corresponding author by request.
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Published In
Journal of Legal Affairs and Dispute Resolution in Engineering and Construction
Volume 15 • Issue 1 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 18, 2022
Accepted: Jul 21, 2022
Published online: Sep 26, 2022
Published in print: Feb 1, 2023
Discussion open until: Feb 26, 2023
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