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

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  • Li, Lingfang (Ivy)
  • Xiao, Erte

Abstract

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.

Suggested Citation

  • Li, Lingfang (Ivy) & Xiao, Erte, 2010. "Money Talks? An Experimental Study of Rebate in Reputation System Design," MPRA Paper 22401, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:22401
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    File URL: https://mpra.ub.uni-muenchen.de/22401/1/MPRA_paper_22401.pdf
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    References listed on IDEAS

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    Cited by:

    1. repec:kap:expeco:v:20:y:2017:i:2:d:10.1007_s10683-016-9485-0 is not listed on IDEAS
    2. Li, Lingfang (Ivy), 2010. "What is the cost of venting? Evidence from eBay," Economics Letters, Elsevier, vol. 108(2), pages 215-218, August.
    3. Xiaofei Pan & Daniel Houser, 2017. "Social approval, competition and cooperation," Experimental Economics, Springer;Economic Science Association, vol. 20(2), pages 309-332, June.
    4. Lafky, Jonathan, 2014. "Why do people rate? Theory and evidence on online ratings," Games and Economic Behavior, Elsevier, vol. 87(C), pages 554-570.
    5. Lumeau, Marianne & Masclet, David & Penard, Thierry, 2015. "Reputation and social (dis)approval in feedback mechanisms: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 127-140.
    6. Robert Gazzale & Tapan Khopkar, 2011. "Remain silent and ye shall suffer: seller exploitation of reticent buyers in an experimental reputation system," Experimental Economics, Springer;Economic Science Association, vol. 14(2), pages 273-285, May.
    7. Luís Cabral & Lingfang (Ivy) Li, 2015. "A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay," Management Science, INFORMS, vol. 61(9), pages 2052-2063, September.
    8. David Masclet & Thierry Pénard, 2012. "Do reputation feedback systems really improve trust among anonymous traders? An experimental study," Applied Economics, Taylor & Francis Journals, vol. 44(35), pages 4553-4573, December.
    9. José Canals-Cerdá, 2012. "The value of a good reputation online: an application to art auctions," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(1), pages 67-85, February.

    More about this item

    Keywords

    reputation; trust; feedback mechanism; asymmetric information; public goods; experimental economics;

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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