An experimental analysis of multi-attribute auctions
Decision Support Systems
Bidding in sealed-bid and English multi-attribute auctions
Decision Support Systems
Extending electronic sourcing theory: An exploratory study of electronic reverse auction outcomes
Electronic Commerce Research and Applications
Solving a sealed-bid reverse auction problem by multiple-criterion decision-making methods
Computers & Mathematics with Applications
Multiple Sourcing and Procurement Process Selection with Bidding Events
Management Science
Bidding behavior in dynamic auction settings: An empirical analysis of eBay
Electronic Commerce Research and Applications
Supplier behavior modeling and winner determination using parallel MDP
Expert Systems with Applications: An International Journal
An efficient reverse auction mechanism for limited supplier base
Electronic Commerce Research and Applications
IEEE Transactions on Information Theory
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Multi-attribute reverse auction-based procurement has been widely used by large organizations. The attributes of the auctioned objects are usually divided into two groups: technical and business attributes. They are reviewed and scored by technical and business experts who act as referees in the bid evaluation process. To analyze their bid evaluation behavior, we built a model for a multi-attribute reverse auction. With correlations between the bid evaluations of the different referee groups across the attributes, the bid evaluation problem is not the usual multi-attribute decision-making problem. We assess the cause-effect relationship that is present, and show that antagonism between referee groups tends to grow over time. We tested how this works with data from simulated auctions. To diminish the potential for antagonism between the two referee groups, we propose a modified bid evaluation mechanism. We also conducted role-playing experiments involving the referee behaviors as a means for assessing the proposed mechanism. Our results suggest that the modified bid evaluation mechanism is beneficial.