The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Money Talks: Rebate Mechanisms in Reputation System Design
Abstract
Reputation systems that rely on voluntary feedback from traders are important in creating and sustaining trust in markets. Feedback nevertheless is a public good, and providing it is often costly. We combine theory with a laboratory experiment to study the effect of a seller precommitment mechanism: Sellers have an option to commit by providing a rebate to reduce the buyer's feedback reporting cost before making purchasing decisions. Our theory predicts that this mechanism induces noncooperative sellers to cooperate in the listed-price market. Using a buyer–seller trust game with a unilateral feedback scheme, we find that the seller's rebate decision has a significant impact on the buyer's purchasing decision via signaling the seller's cooperative type. More importantly, market efficiency under the precommitment mechanism increases with the probability that sellers will provide a rebate. Compared with the no rebate mechanism market, more efficient trades can be achieved when the sellers offer a rebate to the buyers in the market with the rebate mechanism, even when the rebate does not cover the full cost of feedback reporting. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1848 . This paper was accepted by Teck-Hua Ho, behavioral economics.
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“Additionally, given the research design lacks a fear of retaliation, reports are negatively biased.”
From Reputation and Feedback Systems in Online Platform Markets (2016) · cites this paper as Li & Xiao (2014)
In the citing paper
“The lab results suggest that higher reporting costs decrease buyers' willingness to provide reviews on sellers, leading to a decrease in buyers' trust and sellers' trustworthiness, but these results are not statistically significant.”
From Reputation and Feedback Systems in Online Platform Markets (2016) · cites this paper as Li & Xiao (2014)
Citations
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The value of reputation on eBay: A controlled experiment
Resnick, P., Zeckhauser, R., Swanson, J., & Lockwood, K. (2006) · Experimental Economics · doi:10.1007/s10683-006-4309-2 · Cited by 1,118
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Sorted by citations
Reputation and Feedback Systems in Online Platform Markets
Tadelis, S. (2016) · Annual Review of Economics · doi:10.1146/annurev-economics-080315-015325 · Cited by 524
Metadata
- Authors
- Li, L. (., & Xiao, E.
- Affiliations
- Fudan University (CN)
- Carnegie Mellon University (US)
- Venue
- Management Science
- Published
- 2014-08
- Volume
- 60
- Issue
- 8
- Pages
- 2054-2072
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W3123751120
- Cited by
- 65
- References
- 3
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 4 · 2023: 9 · 2022: 8 · 2021: 4 · 2020: 10 · 2019: 7 · 2018: 4 · 2017: 2 · 2016: 3 · 2015: 1 · 2014: 2
- FWCI
- 7.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Management Science (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Auction Theory and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Keywords
- reputation systems, market trust, cooperation, signaling, market efficiency, public goods, online marketplaces
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