IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v19y2019i1d10.1007_s10660-017-9280-9.html
   My bibliography  Save this article

A reputation management mechanism that incorporates accountability in online ratings

Author

Listed:
  • Subhasis Thakur

    (National University of Ireland)

Abstract

Online reputation has a strong impact on the success of a seller in an e-marketplace. Also, buyers use it to choose an appropriate seller among a set of alternatives. The standard practice of determining the reputation of a seller is the aggregation of the feedbacks or the ratings reported by its buyers. Such a model of reputation formulation is vulnerable to misleading and unfair feedbacks. A seller may collude with a set of buyers to report good feedbacks while the quality of its product is poor. Also the buyers can report unfair feedbacks being irrational, malicious or competitors. A robust reputation management mechanism is the one which can not be manipulated by these unfair feedbacks. The existing reputation management models are either reactive or proactive. The reactive solutions intend to identify the unfair feedbacks and the proactive solutions propose incentive to the buyers to encourage them to report fair feedbacks. In this paper, we propose an incentive system that encourages the buyers to report fair feedbacks. We associate a buyer’s reputation with a seller’s reputation if the buyer has expressed its feedback about the seller. If the reputation of the seller decreases then the reputation of all buyers who had endorsed it (provided positive feedbacks) also decreases and vice versa. This means a buyer risks its own reputation by providing the feedback about a seller. In this paper, we show that such a mechanism is incentive compatible, i.e., it encourages the buyers to provide fair feedbacks. Using analytical and experimental analysis, we show the correctness of this reputation management system.

Suggested Citation

  • Subhasis Thakur, 2019. "A reputation management mechanism that incorporates accountability in online ratings," Electronic Commerce Research, Springer, vol. 19(1), pages 23-57, March.
  • Handle: RePEc:spr:elcore:v:19:y:2019:i:1:d:10.1007_s10660-017-9280-9
    DOI: 10.1007/s10660-017-9280-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-017-9280-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10660-017-9280-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    3. Daniel Houser & John Wooders, 2006. "Reputation in Auctions: Theory, and Evidence from eBay," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 15(2), pages 353-369, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Mengqi & Liang, Ke & Perera, Sandun & Huang, Rui & Ghose, Sanjoy, 2022. "Game theoretical analysis of service effort timing scheme strategies in dual-channel supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    2. Xu, Man & Tang, Wansheng & Zhao, Ruiqing, 2023. "Should reputable e-retailers undertake service activities along with sales?," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    3. Guo Li & Hong Zheng & Mengqi Liu, 2020. "Reselling or drop shipping: Strategic analysis of E-commerce dual-channel structures," Electronic Commerce Research, Springer, vol. 20(3), pages 475-508, September.
    4. Cuixia Jiang & Jun Zhu & Qifa Xu, 2022. "Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression," Electronic Commerce Research, Springer, vol. 22(1), pages 157-176, March.
    5. Xueke Du & Rui Dong & Wenli Li & Yibo Jia & Lirong Chen, 2019. "Online Reviews Matter: How Can Platforms Benefit from Online Reviews?," Sustainability, MDPI, vol. 11(22), pages 1-20, November.
    6. Eugenia Y. Huang & Shu-Chiung Lin & I-Ting Hsieh, 2023. "Online marketplace sellers’ influence on rating scores and comment orientation," Electronic Commerce Research, Springer, vol. 23(2), pages 1241-1270, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tobias Gesche, 2022. "Reference‐price shifts and customer antagonism: Evidence from reviews for online auctions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(3), pages 558-578, August.
    2. Judy E. Scott & Dawn G. Gregg & Jae Hoon Choi, 2015. "Lemon complaints: When online auctions go sour," Information Systems Frontiers, Springer, vol. 17(1), pages 177-191, February.
    3. Andrew W. Bausch, 2014. "Evolving intergroup cooperation," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 369-393, December.
    4. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    5. Gesche, Tobias, 2018. "Reference Price Shifts and Customer Antagonism: Evidence from Reviews for Online Auctions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181650, Verein für Socialpolitik / German Economic Association.
    6. Jolivet, Grégory & Jullien, Bruno & Postel-Vinay, Fabien, 2016. "Reputation and prices on the e-market: Evidence from a major French platform," International Journal of Industrial Organization, Elsevier, vol. 45(C), pages 59-75.
    7. Mo Xiao & Jiandong Ju & Ying Fan, 2013. "Losing to Win: Reputation Management of Online Sellers," 2013 Meeting Papers 192, Society for Economic Dynamics.
    8. 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.
    9. Alberto Bracci & Jorn Boehnke & Abeer ElBahrawy & Nicola Perra & Alexander Teytelboym & Andrea Baronchelli, 2021. "Macroscopic properties of buyer-seller networks in online marketplaces," Papers 2112.09065, arXiv.org, revised Apr 2022.
    10. David Masclet & Thierry Pénard, 2008. "Is the ebay feedback system really efficient ? an experimental study," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 200803, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    11. Paul A. Pavlou & Angelika Dimoka, 2006. "The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation," Information Systems Research, INFORMS, vol. 17(4), pages 392-414, December.
    12. Jiaying Deng & Hossein Ghasemkhani & Yong Tan & Arvind K Tripathi, 2023. "Actions speak louder than words: Imputing users’ reputation from transaction history," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1096-1111, April.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Onur, Ilke & Velamuri, Malathi, 2014. "Competition, endogeneity and the winning bid: An empirical analysis of eBay auctions," Information Economics and Policy, Elsevier, vol. 26(C), pages 68-74.
    18. Anya Samek, 2012. "An Experimental Study of Reputation with Heterogeneous Goods," Artefactual Field Experiments 00439, The Field Experiments Website.
    19. Maarten Ter Huurne & Amber Ronteltap & Chenhui Guo & Rense Corten & Vincent Buskens, 2018. "Reputation Effects in Socially Driven Sharing Economy Transactions," Sustainability, MDPI, vol. 10(8), pages 1-19, July.
    20. Fan, Ying & Ju, Jiandong & Xiao, Mo, 2016. "Reputation premium and reputation management: Evidence from the largest e-commerce platform in China," International Journal of Industrial Organization, Elsevier, vol. 46(C), pages 63-76.

    More about this item

    Keywords

    Reputation; e-marketplace; Trust;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:elcore:v:19:y:2019:i:1:d:10.1007_s10660-017-9280-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.