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Money Talks? An Experimental Study of Rebate in Reputation System Design

By Lingfang (Ivy) Li and Erte Xiao


Reputation systems that rely on feedback from traders are important institutions for helping sustain trust in markets, while feedback information is usually considered a public good. We apply both theoretical models and experiments to study how raters' feedback behavior responds to different reporting costs and how to improve market efficiency by introducing a pre-commitment device for sellers in reputation systems. In particular, the pre-commitment device we study here allows sellers to provide rebates to cover buyers' reporting costs before buyers make purchasing decisions. Using a buyer-seller trust game with a unilateral feedback scheme, we find that a buyer’s propensity to leave feedback is more sensitive to reporting costs when the seller cooperates than when the seller defects. The seller’s decision on whether to provide a rebate significantly affects the buyer’s decision to leave feedback by compensating for the feedback costs. More importantly, the rebate decision has a significant impact on the buyer's purchasing decision via signaling the seller's cooperative type. The experimental results show that the rebate mechanism improves the market efficiency.

Topics: D03 - Behavioral Economics; Underlying Principles, D02 - Institutions: Design, Formation, and Operations, H41 - Public Goods, D82 - Asymmetric and Private Information; Mechanism Design, L86 - Information and Internet Services; Computer Software, C91 - Laboratory, Individual Behavior
Year: 2010
DOI identifier: 10.2139/ssrn.1597764
OAI identifier: oai:mpra.ub.uni-muenchen.de:22401

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