Winner determination for risk aversion buyers in multi-attribute reverse auction

Multiattribute reverse auction has become prevalent for the procurement of goods and services in recent days. In such an auction, a group of potential suppliers bid to win the contract that has been defined in multiple attributes by the buyer for providing goods or services. A corresponding winner determination problem provides important decisions for the buyer to select its best supplier. Considering the buyer with risk aversion behavior and suppliers with positive and negative attributes described by a combination of crisp data, interval numbers and linguistic variables in a multiattribute reverse auction setting, we incorporate the prospect theory (PT) into the ‘benefits, opportunities, costs and risks’ (BOCR) framework to propose a novel PT-BOCR solution method. The effectiveness and distinct advantage of our method on dealing with the buyer's risk averse attitude are demonstrated in comparison with other known methods. Computational results indicate that the PT-BOCR method is robust with respect to the variance of suppliers' attributes and the level of reference points. An interesting result reveals that when suppliers' attributes vary a lot, the degree of risk aversion increases or decreases depending on the reference point is low or high. The PT-BOCR method could be a useful tool for risk aversion buyers to avoid losses and for suppliers to win the bids by improving their attributes.