IDEAS home Printed from https://ideas.repec.org/p/bon/boncrc/crctr224_2022_267v2.html

When and Why Do Buyers Rate in Online Markets?

Author

Listed:
  • Xiang Hui
  • Tobias J. Klein
  • Konrad Stahl

Abstract

Anonymous markets would be very difficult to successfully operate without the possibility that buyers rate the seller. Yet many empirical results yield that ratings are non-random and concentrate on extreme experiences. We develop a model of rating decisions in which the buyer is willing to share publicly her opinion about a transaction, if its realized quality differs much from the quality expected by her, where expected quality is influenced by an aggregate of the seller’s past ratings. We demonstrate our results empirically using raw data from eBay. In spite of the non-randomness of responses, unweighted rating aggregates appear to rather well reflect reported buyer experience as long as expectations are not extreme.

Suggested Citation

  • Xiang Hui & Tobias J. Klein & Konrad Stahl, 2022. "When and Why Do Buyers Rate in Online Markets?," CRC TR 224 Discussion Paper Series crctr224_2022_267v2, University of Bonn and University of Mannheim, Germany.
    • Handle: RePEc:bon:boncrc:crctr224_2022_267v2
    as

    Download full text from publisher

    File URL: https://www.crctr224.de/research/discussion-papers/archive/dp267
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Andrey Fradkin & David Holtz, 2023. "Do Incentives to Review Help the Market? Evidence from a Field Experiment on Airbnb," Marketing Science, INFORMS, vol. 42(5), pages 853-865, September.
    2. Martin, Simon & Shelegia, Sandro, 2021. "Underpromise and overdeliver? - Online product reviews and firm pricing," International Journal of Industrial Organization, Elsevier, vol. 79(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bon:boncrc:crctr224_2022_267v2. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CRC Office (email available below). General contact details of provider: https://www.crctr224.de .

    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.