Electronic reverse-markets such as those hosted by Freemarkets involve geographically dispersed sellers. By the very nature of the market, sellers in any given market-session are uncertain both about the number of opponents they face and their cost-structure. Over the course of several market sessions, sellers can learn about the competitive structure of the market. Their ability to learn i.e., their ability to reduce the level of uncertainty is dependent on the revelation policy adopted. The extent to which competitive information is revealed under each revelation policy determines what sellers learn, how they bid in future and thus, the consumer surplus generated. This paper compares a set of revelation policies commonly used in electronic reverse marketplaces, using consumer surplus as our metric. Game-theoretic models are employed to focus on the effect of revelation policies when firms are uncertain about their opponent’s cost. Based on the analysis, this paper provide intuitions as to why under certain conditions, one setting is better than the other.
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