A Framework for an Automated Decision Support System for Selecting Safety-Conscious Contractors

Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

Abstract:

Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: Construction safety, contractor selection, decision support system, relational database.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126417

References:

[1] Bureau of Labor Statistics (BLS). (2015). “Number and rate of fatal occupational injuries, by industry sector, 2013.” (April 2015).
[2] Jackson, B. (2006), Construction management jumpstart, John Wiley & Sons.
[3] Hislop, R. (1999), Construction site safety: A guide for managing contractors, Chelsea, Michigan, U.S.A: Lewis Pub.
[4] Kartam, N., Flood, I., and Koushki, P. (2000). “Construction safety in Kuwait: issues, procedures, problems, and recommendations.” Safety Science, 36(2000), 163-184.
[5] Lamm, F., Massey, C., and Perry, M. (2006). “Is there a link between workplace health & safety & firm performance & productivity?” New Zealand Journal of Employment Relations, 32(1), 75-90.
[6] Thomas, S., Skitmore, M., and Cheng, K. (2005). “A framework for evaluating the safety performance of construction contractors.” Building and Environment, 40(10), 1347-1355.
[7] Priyadarshani, K., Karunasena, G., and Jayasuriya, S. (2013). “Construction safety assessment framework for developing countries: A case study in Sri Lanka.” Journal of Construction in Developing Countries, 18(1), 33-51.
[8] Mahmoudi, S., Ghasemi, F., Mohammadfam I., and Soleimmani, E. (2014). “Framework for continuous assessment and improvement of occupational health and safety issues in construction companies.” Safety and Health at Work, 5(2014), 125-130.
[9] Al-Tabtabai, H. (2002). “Analyzing construction site accidents in Kuwait.” Kuwait J. Sci. Eng, 29(2), 213-238.
[10] Assaf, S.A., Al Khalil, M., and Al Hazmi, M. (1995). “Causes of delay in large building construction projects.” Journal of Management in Engineering, 11(2), 45-50.