Effects of Information-Revelation Policies Under Market-Structure Uncertainty

Geographically dispersed sellers in electronic reverse-marketplaces such as those hosted by Freemarkets are uncertain about the number of others sellers in any given market session. Over the course of several market sessions, they learn about the competitive structure of their market. How sellers learn to reduce the level of market structure uncertainty, is dependent on the market transparency scheme (revelation policy) adopted. The revelation policies differ in terms of the level of competitive information revealed. Thus, they determine what sellers learn, how they bid in future, and, in general how the consumer surplus generated changes. In this paper, using game-theory, we compare a set of revelation policies commonly used in electronic reverse marketplaces on consumer surplus. Based on our analysis, we find that the policy that generates the least amount of market structure uncertainty for the sellers should be chosen to maximize consumer surplus. This contradicts the traditional view that under uncertainty sellers are worse off and the buyer better off. This paper provides insights into this apparently anomalous outcome. Acknowledgements: This work was funded in part by NSF CISE/IIS/KDI 9873005.