Reverse auctions are fast becoming the standard for many procurement activities. In the past, the majority of such auctions have been solely price based, but increasingly attributes other than price affect the auction outcome. Specifically, the buyer uses a scoring function to compare bids and the bid with the highest score wins. We investigate two mechanisms commonly used for procurement in business-to-business markets, in a setting in which buyers' welfare is affected by exogenous nonprice attributes such as the quality, service, and past relationships. Under both mechanisms, bidders bid based on price, but in the “buyer-determined” mechanism, the buyer is free to select the bid that maximizes her surplus while in the “price-based” mechanism, the buyer commits to awarding the contract to the low price bidder. We find, both in theory and in the laboratory, that the “buyer-determined” mechanism increases the buyer's welfare only as long as enough suppliers compete. If the number of suppliers is small and the correlation between cost and quality is low, the buyer is better off with the “price-based” mechanism. These findings are intended to help procurement managers make better decisions in designing procurement mechanisms for a variety of settings.bidding, procurement, reverse auctions, multiattribute auctions, behavioral game theory, experimental economics
We investigate the effect of regret-related feedback information on bidding behavior in sealed-bid first-price auctions. Two types of regret are possible in this auction format. A winner of the auction may regret paying too much relative to the second highest bid, and a loser may regret missing an opportunity to win at a favorable price. In theory, under very general conditions, being sensitive to winning and paying too much should result in lower average bids, and being sensitive to missing opportunities to win at a favorable price should result in higher bids. For example, the U.S. Government's policy of revealing losing bids may cause regret-sensitive bidders to anticipate regret and bid conservatively, decreasing the government's revenue. We test these predictions in the laboratory and find strong support for both.auctions, competitive bidding, regret, learning, experimental economics
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