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Buyers pay for and sellers invest in a good reputation: More evidence from eBay

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  • Przepiorka, Wojtek

Abstract

This article contributes to the research on trust and reputation formation in anonymous online markets. I first give a formal account of the reputation mechanism in anonymous online markets and derive testable hypotheses. Based on the analysis of a large set of process data (N≈176,000), I corroborate a statistically and economically significant seller reputation effect on the probability of sale and the selling price both in auctions and fixed price offers. Moreover, my analysis shows that sellers making fixed price offers invest in a good reputation to a similar extent as buyers pay for it in auctions. Finally, I obtain repeated observations on a considerable subset of the buyer population by including highest non-winning bids in the analysis and show that buyers trade off sellers’ reputations and prices within the set of offered items they choose to bid on. My findings provide further evidence that reputation systems solve trust problems and reduce transaction costs in anonymous online markets by providing incentives for traders’ cooperative behavior.

Suggested Citation

  • Przepiorka, Wojtek, 2013. "Buyers pay for and sellers invest in a good reputation: More evidence from eBay," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 42(C), pages 31-42.
    • Handle: RePEc:eee:soceco:v:42:y:2013:i:c:p:31-42
    DOI: 10.1016/j.socec.2012.11.004
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    References listed on IDEAS

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    1. Ben Jann, 2007. "Making regression tables simplified," Stata Journal, StataCorp LP, vol. 7(2), pages 227-244, June.
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    8. Wojtek Przepiorka, 2012. "Ethnic discrimination and signals of trustworthiness in an online market: Evidence from two field experiments," Discussion Papers 2012002, University of Oxford, Nuffield College.
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    Citations

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    Cited by:

    1. Peng Zou & Jingwen Liu, 2019. "How nutrition information influences online food sales," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1132-1150, November.
    2. Dirk Helbing, 2013. "Economics 2.0: The Natural Step towards A Self-Regulating, Participatory Market Society," Papers 1305.4078, arXiv.org, revised Jun 2013.
    3. Schneck, Andreas & Przepiorka, Wojtek, 2023. "Meta-dominance analysis - A tool for the assessment of the quality of digital behavioural data," SocArXiv cy3wj, Center for Open Science.
    4. Rense Corten & Judith Kas & Timm Teubner & Martijn Arets, 2023. "The role of contextual and contentual signals for online trust: Evidence from a crowd work experiment," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    5. Emma von Essen & Jonas Karlsson, 2019. "The effect of competition on discrimination in online markets—Anonymity and selection," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-18, August.
    6. Ruohuang Jiao & Wojtek Przepiorka & Vincent Buskens, 2022. "Moderators of reputation effects in peer-to-peer online markets: a meta-analytic model selection approach," Journal of Computational Social Science, Springer, vol. 5(1), pages 1041-1067, May.
    7. Vincenz Frey, 2017. "Boosting trust by facilitating communication: A model of trustee investments in information sharing," Rationality and Society, , vol. 29(4), pages 471-503, November.
    8. Przepiorka, Wojtek, 2014. "Reputation in offline and online markets: Solutions to trust problems in social and economic exchange," economic sociology. perspectives and conversations, Max Planck Institute for the Study of Societies, vol. 16(1), pages 4-10.
    9. Wojtek Przepiorka, 2012. "Ethnic discrimination and signals of trustworthiness in an online market: Evidence from two field experiments," Discussion Papers 2012002, University of Oxford, Nuffield College.

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    More about this item

    Keywords

    Trust; Trustworthiness; Uncertainty; Reputation; Online markets;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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