The performance of reverse auctions versus request for quotes when procuring goods with quality differences

The use of dynamic auctions is a major component in many enterprises' e-procurement initiatives. In the case where suppliers offer goods and services of inherently different quality the traditional mechanism has been the request for quote. In a request for quote, suppliers submit a sealed bid and the fixed quality of their offering and then the buyer selects the seller who offers the greatest difference between quality and price. The winning seller receives a price equal to his submitted bid. The reverse auction has immerged as the most commonly adopted dynamic auction for this setting. In a reverse auction, suppliers first submit the qualities of their goods and then the suppliers participate in an auction with the same message space as an open outcry English auction (descending because this is a procurement auction.) However, the auction is only used to set each suppliers price. The last price a supplier submits in the auction becomes their actual submitted price. After, the auction the buyer selects the winning seller who offers the greatest difference between quality and actual submitted price. We provide a game theoretic analysis of both mechanisms. We also provide extensive experimental evaluation of the two mechanisms as wellReverse Auction, Request for Quote, procurement

Learning about Learning in Games through Experimental Control of Strategic Interdependence

We conduct experiments in which humans repeatedly play one of two games against a computer decision maker that follows either Roth and Erev's reinforcement learning algorithm or Camerer and Ho's EWA algorithm. The human/algorithm interaction provides results that can't be obtained from the analysis of pure human interactions or model simulations. The learning algorithms are more sensitive than humans in calculating exploitable opponent play. Learning algorithms respond to these calculated opportunities systematically; however, the magnitude of these responses are too weak to improve the algorithm's payoffs. Human play against various decision maker types does not significantly vary. These results demonstrate that humans and currently proposed models of their behavior differ in that humans do not adjust payoff assessments by smooth transition functions and that when humans detect exploitable play they are more likely to choose the best response to this belief.

Procurement Auctions for Differentiated Goods

We consider two mechanisms to procure differentiated goods: a request for quote and an English auction with bidding credits. In the request for quote, each seller submits a price and the inherent quality of his good. Then the buyer selects the seller who offers the greatest difference in quality and price. In the English auction with bidding credits, the buyer assigns a bidding credit to each seller conditional upon the quality of the seller’s good. Then the sellers compete in an English auction with the winner receiving the auction price and his bidding credit. Game theoretic models predict the request for quote is socially efficient but the English auction with bidding credits is not. The optimal bidding credit assignment under compensates for quality advantages, creating a market distortion in which the buyer captures surplus at the expense of the seller’s profit and social efficiency. In experiments, the request for quote is less efficient than the English auctions with bidding credits. Moreover, both the buyer and seller receive more surplus in the English auction with bidding credits.

Do We Detect and Exploit Mixed Strategy Play by Opponents?

We conducted an experiment in which each subject repeatedly played a game with a unique Nash equilibrium in mixed strategies against some computer-implemented mixed strategy. The results indicate subjects are successful at detecting and exploiting deviations from Nash equilibrium. However, there is heterogeneity in subject behavior and performance. We present a one variable model of dynamic random belief formation which rationalizes observed heterogeneity and other features of the data.best response correspondence, mixed strategy

An Experimental Investigation of Auctions and Bargaining in Procurement

In reverse auctions, buyers often retain the right to bargain further concessions from the winners. The optimal form of such procurement is an English auction followed by an auctioneer's option to engage in ultimatum bargaining with the winners. We study behavior and performance in this procurement format using a laboratory experiment. Sellers closely follow the equilibrium strategy of exiting the auction at their costs and then accepting strictly profitable offers. Buyers generally exercise their option to bargain according to their equilibrium strategy, but their take-it-or-leave-it offers vary positively with auction prices when they should be invariant. We explain this deviation by modeling buyers' subjective posteriors regarding the winners' costs as distortions of the Bayesian posteriors, calculated using a formulation similar to a commonly used probability weighting function. We further test the robustness of the experimental results and the subjective posterior explanation with three additional experimental treatments

Individual Rationality and Market Efficiency

Smith’s (1962) demonstration that prices and allocations quickly converge to the competitive equilibrium in the continuous double auction (CDA) remains one of the most important results in experimental economics. Market experiments and exchange models have added considerably to our knowledge of how markets reach equilibrium, and how they respond to disruptions. Perhaps the best-known model of exchange in CDA market experiments is the random behavior “zero-intelligence” (ZI) model by Gode and Sunder (1993). They argue that the CDA generates efficient allocations and “convergence of transaction prices to the proximity of the theoretical equilibrium price,” provided only that agents meet their budget constraints. We demonstrate that prices do not converge in their simulations. Their budget constraint requires that a buyer’s currency never exceeds her commodity value, which is an unnatural restriction. Their conclusion that market efficiency results from the structure of the CDA independent of traders’ profit seeking behavior rests on their claim that the constraints that they impose are a part of the market institution. We show that actually they impose individual rationality. Misinterpretation of this behavioural constraint has lead to unproductive debate on market adjustment processes

Learning about learning in games through experimental control of strategic independence

We conduct experiments in which humans repeatedly play one of two games against a computer decision maker that follows either a reinforcement learning algorithm or an Experience Weighted Attraction algorithm. The human/algorithm interaction provides results that can’t be obtained from the analysis of pure human interactions or model simulations. These learning algorithms are more sensitive than humans to exploitable opponent play. Learning algorithms respond to these calculated opportunities systematically; however, the magnitude of these responses are too weak to improve the algorithm’s payoffs. Human play against various decision maker types does not vary significantly. These results demonstrate that humans and current models of their behavior differ in that humans do not adjust payoff assessments by smooth transition functions but when humans do detect exploitable play they are more likely to choose Identifying how humans respond and adapt their behavior in repeated strategic decision making tasks has emerged as a core, but difficult to answer, question in the social sciences

Trust and Trustworthiness in Procurement Contracts with Retainage

When product quality is unverifiable by third parties, enforceable contracts that condition price upon quality are not feasible. If higher quality is also costly to deliver, moral hazard by sellers flourishes, particularly when procurement is via a competitive auction process. Retainage is a contractual mechanism that presents a solution to the third-party unverifiability problem, by setting aside a portion of the purchase price. After delivery, the buyer has sole discretion over the amount of retainage money that is released to the seller. While generally a feasible contract form to implement, retainage introduces a moral hazard for the buyer. We use laboratory experiments to investigate how and when retainage might be successfully used to facilitate trust and trustworthiness in procurement contracts. We observe that retainage induces a significant improvement in product quality when there are some trustworthy buyers in the population, consistent with a model of fair payment norms that we develop. This improvement is realized at the cost of increased buyer-seller profit inequalities. We also observe that at high levels of retainage, there is a welfare-decreasing market unraveling in which sellers do not bid on contracts. Our results imply that retainage incentives can mitigate the tension between competition and cooperation arising from reverse auctions, but only at appropriate levels of retainage