Reputation, Trust, and Rebates: How Online Auction Markets Can Improve Their Feedback Mechanisms

Abstract

Reputation systems constitute an important institution, helping sustain trust in online auction markets. However, only half of buyers leave feedback after transactions, and nearly all feedback is positive. In this paper, I propose a mechanism whereby sellers can provide rebates (not necessarily in monetary form) to buyers contingent upon buyers' provision of reports. Using a game theoretical model, I show how the mechanism can increase unbiased reporting. There exists a pooling equilibrium where both good and bad sellers choose the rebate option, even though their true types are revealed through feedback. The mechanism also induces bad sellers to improve the quality of the contract.