An Economic Analysis of Rebates Conditional on Positive Reviews
Jianqing Chen, Zhiling Guo, Jian Huang
The University of Texas at Dallas Singapore Management University Nanjing University of Finance and Economics
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摘要与影响
In the prevailing e-commerce environment, conditional rebates have emerged as a common business practice on leading online platforms such as Taobao. Because rebates are only offered to purchasing consumers who post positive online reviews, a key concern is that it can easily induce fake reviews that might harm consumers. We theoretically analyze the seller’s optimal conditional-rebate strategies based on heterogeneous consumers’ online-review-posting behavior and derive three practically important findings. First, it is not always profitable for strategic sellers to pursue the conditional-rebate strategy. Blindly offering incentives may not help achieve the goal of review manipulation. Second, the conditional-rebate strategy does not necessarily result in fake reviews. Fake reviews occur only if consumers’ moral cost is low and the review-posting cost is not too high. Third, under certain conditions, offering conditional rebates can even increase consumer surplus and social welfare. Platform owners or policy designers can help reduce social losses by offering transparent sales information and by appropriately controlling the platform review-posting cost to induce quality reviews. Our study offers new insights into the fake-review phenomenon induced by conditional rebates and sheds new light on the policy debate about whether platforms should completely ban incentivized reviews.
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社会科学Digital Marketing and Social Media
Consumer Market Behavior and Pricing · Auction Theory and Applications
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