A semi-systematic literature review on supplier selection in construction projects

Abstract

It is commonly acknowledged that the competition is very fierce in the construction industry. The business continuity of contractors is mainly dependent on the success -of the completed projects. The success criteria of construction projects can be described as finishing the construction work on time, within the budget and meeting the desired quality level. Since the cost of materials constitutes nearly 40% of the overall project budget, delivery of the right amount of materials on the right time and with the desired quality is crucial for the overall project performance. In this context, selecting the right supplier is one of the most important decisions in the construction management field. Therefore, supplier selection has attracted considerable attention in construction. The previous studies that deal with the supplier selection problem in construction projects can be categorized into two main groups, which are; 1) the studies that identify either the supplier selection criteria or their importance levels, and 2) the studies propose various multi-criteria-decision-making (MCDM) techniques for solving the supplier selection problem. All these studies have substantially contributed to the construction supply chain management body of knowledge. However, there were no studies that simultaneously investigated how the studies, which focus on the supplier selection problem, evolved in terms of both the considered supplier selection criteria and the employed MCDM techniques over the years. In order to fulfill this knowledge gap, this study reviews the previous studies on supplier selection in construction projects from this perspective. It was found that although cost, time and quality have been considered to be the primary supplier selection criteria, the remaining criteria are specific to project/company/case in question and they are specified by the experts, who are responsible for the selection process. Also, in recent studies, the MCDM methods extended with fuzzy numbers, grey numbers, rough numbers, etc. have been preferred in order to cope with the uncertainty and vagueness in the preferences of the decision makers.