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Reputation and Uncertainty in Online Markets: An Experimental Study

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  • Sarah C. Rice

    (School of Business, University of Connecticut, Storrs, Connecticut 06269)

Abstract

This paper employs a modified investment game to study how online reputation ratings are assigned, and thus how electronic reputations are formed in transactions where buyers and sellers interact anonymously. Of particular interest are the important questions of how online reputations evolve and how specific reputation information is interpreted by market participants. We vary the level of uncertainty in the transaction environment, and measure the effects of this manipulation on buyers' trust and their subsequent rating behaviors. We distinguish between a reputation mechanism and specific reputation information, finding the former has an association with the overall decision of whether to transact in the marketplace, while the latter shows significance in purchase decisions regarding specific sellers. We also find that aggregate reputation information is weighted differently than singular reputation information. Finally, we show that when reputations are increasingly noisy, buyers are less likely to react negatively to poor ratings and are more likely to give sellers the benefit of the doubt when seemingly uncooperative outcomes occur.

Suggested Citation

  • Sarah C. Rice, 2012. "Reputation and Uncertainty in Online Markets: An Experimental Study," Information Systems Research, INFORMS, vol. 23(2), pages 436-452, June.
  • Handle: RePEc:inm:orisre:v:23:y:2012:i:2:p:436-452
    DOI: 10.1287/isre.1110.0362
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    References listed on IDEAS

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    Cited by:

    1. Gary E. Bolton & David J. Kusterer & Johannes Mans, 2015. "Inflated reputations: Uncertainty, leniency & moral wiggle room in trader feedback systems," Cologne Graduate School Working Paper Series 06-04, Cologne Graduate School in Management, Economics and Social Sciences, revised 29 Jul 2016.
    2. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    3. Dominik Gutt & Jürgen Neumann & Wael Jabr & Dennis Kundisch, 2020. "The Fate of the App: Economic Implications of Updating under Reputation Resetting," Working Papers Dissertations 76, Paderborn University, Faculty of Business Administration and Economics.
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    6. Kusterer, David & Sliwka, Dirk, 2022. "Social Preferences and Rating Biases in Subjective Performance Evaluations," IZA Discussion Papers 15496, Institute of Labor Economics (IZA).
    7. Behnud Mir Djawadi & René Fahr & Claus-Jochen Haake & Sonja Recker, 2018. "Maintaining vs. milking good reputation when customer feedback is inaccurate," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-23, November.
    8. Sandeep Khurana & Liangfei Qiu & Subodha Kumar, 2019. "When a Doctor Knows, It Shows: An Empirical Analysis of Doctors’ Responses in a Q&A Forum of an Online Healthcare Portal," Information Systems Research, INFORMS, vol. 30(3), pages 872-891, September.
    9. Yang, Zhengliang & Du, Xiaoxue & Hatzenbuehler, Patrick & Lu, Liang & Reardon, Thomas & Tian, Guang, 2021. "Agri-Food Products Live Streaming: Fad or a New Marketing Channel?," 2021 Conference, August 17-31, 2021, Virtual 315334, International Association of Agricultural Economists.
    10. Sonja Brangewitz & Behnud Djawadi & Rene Fahr & Claus-Jochen Haake, 2014. "Quality Choices and Reputation Systems in Online Markets - An Experimental Study," Working Papers CIE 85, Paderborn University, CIE Center for International Economics.
    11. Heng Tang & Xiaowan Lin, 2019. "Curbing shopping cart abandonment in C2C markets — an uncertainty reduction approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(3), pages 533-552, September.
    12. Liangfei Qiu & Asoo Vakharia & Arunima Chhikara, 2019. "Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Working Papers 19-01, NET Institute.
    13. Ravi Bapna & Liangfei Qiu & Sarah Rice, 2014. "Repeated Interactions vs. Social Ties: Quantifying the Economic Value of Trust, Forgiveness, and Reputation Using a Field Experiment," Working Papers 14-07, NET Institute.
    14. Ke Rong & Di Zhou & Xinwei Shi & Wei Huang, 2022. "Social Information Disclosure of Friends in Common in an E‐commerce Platform Ecosystem: An Online Experiment," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 984-1005, March.
    15. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    16. Gary E. Bolton & David J. Kusterer & Johannes Mans, 2019. "Inflated Reputations: Uncertainty, Leniency, and Moral Wiggle Room in Trader Feedback Systems," Management Science, INFORMS, vol. 65(11), pages 5371-5391, November.
    17. Tamara Dinev & Allen R. McConnell & H. Jeff Smith, 2015. "Research Commentary—Informing Privacy Research Through Information Systems, Psychology, and Behavioral Economics: Thinking Outside the “APCO” Box," Information Systems Research, INFORMS, vol. 26(4), pages 639-655, December.
    18. Qingfeng Zeng & Wei Zhuang & Qian Guo & Weiguo Fan, 2022. "What factors influence grassroots knowledge supplier performance in online knowledge platforms? Evidence from a paid Q&A service," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2507-2523, December.

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