Development of a pre-qualification and selection framework for construction projects’ contractors in Saudi Arabia

Abstract

ABSTRACT In the kingdom of Saudi Arabia almost 60% of the construction projects were delayed in the recent decade. Contractor selection is the critical decision for the success of any construction project. The typical method of contractor selection in Saudi Arabian projects is generally based on prioritizing the lowest bid price, irrespective of experience, quality, and other factors without investigating in-depth the pre-qualification of contractors. This often leads to disputes and project delays. In this regard, the main goal of the presented research work is the development of a framework that can help decision-makers in both government and private sector to investigate the pre-qualification, and then to select the most suitable contractors for the proposed projects. The presented framework was developed based on a detailed literature review, market analysis, information collection from stakeholders and decision-makers along with collaboration with industry-academia experts. Forty criterion-based selection framework was developed in the presented research work with each criterion possessing a relative weightage developed in comparison with ones obtained using smart techniques. The main categories of the selection criteria are project value, financial capability, reputation, management structure, technical capability and performance, organizational culture, along with safety and environmental health. Through detailed survey and analysis, the main criterion for contractor selection was identified as quality assurance and control with the least important being the Current/Past Joint Venture(s). The presented framework model was validated using a case study where three construction contractors were evaluated using Multi-Attribute Utility Theory Score (MAUT). The framework was deemed reliable and valuable for contractor selection in construction projects for adding the increased selection criterion and insight into the selection evaluation.