Ahmed Khalafallah is an Assistant Professor at the Department of Civil Engieering, Kuwait University, Kuwait. Prior to joining Kuwait University, he was the Coordinator of the Construction Management program at Western Kentucky University. He holds a PhD degree in Civil Engineering with Computational Science and Engineering option from the University of Illinois. His research interests are in the areas of computational intelligence, risk management, sustainable construction optimization, quality control, and maintenance of infrastructure projects. He accumulated more than 16 years of experience at a number of leading institutes, including the University of Illinois, the University of Central Florida, and Cairo University.
The selection of a competent contractor for a construction project is a critical process to its success, and is usually based on competitive bidding or negotiated contracts. The evaluation of contractor safety performance is not a typical criterion in the selection process, although evidence suggests that such negligence can lead to increased accident rates, productivity losses, and significant cost overruns. This paper presents a framework for an automated decision support system that is designed to aid owners in evaluating contractor safety performance as one of the criteria for contractor selection. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance and their metrics; (2) soliciting the input of experts regarding the indicators, their metrics, and relative significance; and (3) designing a relational database model to integrate the metrics of the identified indicators into a system that rates the safety performance of a contractor. The envisioned system should prove useful to owners and decision makers in selecting safety-conscious contractors, and can lead to significant safety improvements in an industry rife with hazards and accidents.