Decision making framework for tender evaluation and contractor selection in public organizations with risk considerations

Abstract

Selecting the best construction contractor plays a critical role in the success of any construction project. Moreover, in the public sector, the traditional lowest bid method is still broadly used and contracts are often awarded based on the lowest price. However, this method has been criticized by many researchers because even if it might guarantee the lowest cost for a project, it does not guarantee the maximum value in terms of time and quality. More particularly, the risk exposure during the tendering process is usually very high and the success of the construction project is strongly related to managing this risk in an appropriate way. Therefore, the selection of the most appropriate contractor should be based on a set of criteria such as technical capability, financial stability, risk, safety, etc., in addition to cost in order to avoid problems that may happen after the contract is awarded. This study aims therefore to develop a decision making framework (DMF) to assist the public organizations in selecting the most appropriate construction contractor(s). The proposed DMF uses a combination of multi-criteria decision making (MCDM) tools and fuzzy logic theory and consists of three stages. In the first stage, data envelopment analysis (DEA) is used to reduce the number of contractors, based on multiple criteria, such that only efficient contractors are considered. In the second stage, the risk factors that are related to each efficient contractor are identified and assessed using a fuzzy logic based approach. Finally, in the third stage, a bi-objective mixed integer linear programming (MILP) model is developed to select the best contractor(s) based on cost and risk and to determine the optimal quantity of work to be assigned to each selected contractor. Indeed, the proposed approach considers the multiple award contract case in which more than one contractor can be selected to share the amount of work to be performed. We assume that prior to using the proposed DMF, a pre-qualification study is conducted using multiple criteria chosen by the public organization, and only pre-qualified contractors are included in the first stage of the proposed DMF. Moreover, a case study inspired from the contractor selection process in a public organization in the United Arab Emirates (UAE) is used to show the effectiveness of the proposed approach.