An advanced decision-support system for ranking unbalanced bids

Abstract

Awarding a contract to a bidder who has unbalanced the bid may cost more money to the owner. An owner who determines that a bid has been unbalanced has the legal right to reject the bid. Although several models have been developed to detect unbalanced bids, some researchers still assert that the number of cases in which owners mistakenly identify balanced bids as unbalanced is too great to ignore. One of the reasons of this failure is the use of an inappropriate benchmark against which the offered unit prices are compared. In this paper it is argued that the use of the geometric mean of the unit prices provided by the bidders as a benchmark helps to obtain robust solutions and an advanced decision-making model is proposed in which the Information Entropy and VIKOR methods are used to detect unbalanced bids. The results obtained from an example project drawn from the literature demonstrate how owners may be misled if they use an inappropriate benchmark in detecting unbalanced bids. This study contributes to the body of knowledge by highlighting the negative impacts of using flawed benchmarks in this process, an area of research that is mostly ignored in the unbalanced bidding literature.