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Buying Reputation: Evidence from Taobao’s Rebate-for-Feedback Mechanism

Date: Monday, June 20th, 15:30

Location: 1211, Ge Zhi Building, Liu Lin Campus

The public lecture

Given by

Associate Professor: Li Lingfang

Fudan University


Reputation is critical to foster trust in online marketplaces, yet leaving feedback is a public good that can be under-provided unless buyers are rewarded for it. Signaling theory implies that only high quality sellers would reward truthful buyers for feedback but if buyers reciprocate with exaggerated feedback then lower quality sellers will also reward feedback. Studying a “reward-for-feedback” mechanism we find that items with rewards receive more detailed feedback that is not positively biased, with sales that are nearly 30% higher. This suggests that it is beneficial to allow sellers to use rewards to build reputations and signal high quality.

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