IAHP/DEA Model for Contractor Assessment in Construction Industries in the Presence of Imprecise Data

One of the most important issues, which project-oriented organizations face with, is the outsourcing of sub-projects in order to focus on integrated management of them. This is the case for construction industries due to their nature and having a wide range of activities. Contractor selection based on the lowest price not only has failed to reduce the risks facing stockholders and investors in this industry, but also, despite of developing prequalification methods, it is one of the main factors of project failure and escalation of risks in investment on this scope. In this paper, a non-parametric data envelopment analysis (DEA) is used to solve the problem of the selection and re-evaluation of construction project contractors. Tendency of employers to employ a large number of assessment criteria in comparison with a few contractors in executive bids, due to the specialized nature of the work, will increase the number of contractors on the efficiency frontier. Therefore, to resolve this problem, an integrated model by using the interval analytic hierarchy process (IAHP), because of imprecise data in the experts’ judgment, and data envelopment analysis (DEA) methods have been developed. The results show high strength of discrimination for the proposed model.