[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/18021.html
   My bibliography  Save this paper

Harvesting Ratings

Author

Listed:
  • Johnen, Johannes
  • Ng, Robin
Abstract
Evidence suggests lower prices lead to better ratings, but better ratings induce firms to charge higher prices in the future. We model that consumers are only willing to make the effort to rate a seller if this seller provides a sufficient value-for-money. Using this model, we explore how firms use prices to impact their own ratings. We show that firms harvest ratings: they offer lower prices in early periods to trigger consumers to leave a good rating in order to earn larger profits in the future. Because especially low-quality firms harvest ratings, harvesting makes ratings less-informative about quality. Based on this mechanism, (i) we argue that rating harvesting causes rating inflation; (ii) we show that a marketplace that facilitates ratings (e.g. through reminders, one-click ratings etc.) may get more ratings, but also less-informative ratings; (iii) a marketplace that screens the quality of sellers makes ratings less-informative if the screening is insufficient. Counter to the conventional wisdom that consumers benefit from ratings via the information they transmit, we show that consumers prefer somewhat, but never fully informative ratings. Nonetheless consumers prefer more-informative ratings than average sellers. We apply these results to characterise when a two-sided platform wants to facilitate ratings. Our results suggest that efforts of major platforms to facilitate ratings may have lead to less-informative ratings, and possibly also shifted surplus from consumers to sellers.

Suggested Citation

  • Johnen, Johannes & Ng, Robin, 2023. "Harvesting Ratings," CEPR Discussion Papers 18021, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18021
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP18021
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Yan Chen & F. Maxwell Harper & Joseph Konstan & Sherry Xin Li, 2010. "Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens," American Economic Review, American Economic Association, vol. 100(4), pages 1358-1398, September.
    3. Paul Resnick & Richard Zeckhauser & John Swanson & Kate Lockwood, 2006. "The value of reputation on eBay: A controlled experiment," Experimental Economics, Springer;Economic Science Association, vol. 9(2), pages 79-101, June.
    4. Luis M.B. Cabral, 2000. "Stretching Firm and Brand Reputation," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 658-673, Winter.
    5. Johnen, Johannes & Leung, Benson Tsz Kin, 2022. "Distracted from Comparison: Product Design and Advertisement with Limited Attention," CEPR Discussion Papers 17234, C.E.P.R. Discussion Papers.
    6. Cho, In-Koo & Sobel, Joel, 1990. "Strategic stability and uniqueness in signaling games," Journal of Economic Theory, Elsevier, vol. 50(2), pages 381-413, April.
    7. Chris Nosko & Steven Tadelis, 2015. "The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment," NBER Working Papers 20830, National Bureau of Economic Research, Inc.
    8. Nelson Granados & Alok Gupta & Robert J. Kauffman, 2012. "Online and Offline Demand and Price Elasticities: Evidence from the Air Travel Industry," Information Systems Research, INFORMS, vol. 23(1), pages 164-181, March.
    9. Devesh Raval, 2020. "Whose Voice Do We Hear in the Marketplace? Evidence from Consumer Complaining Behavior," Marketing Science, INFORMS, vol. 39(1), pages 168-187, January.
    10. Apostolos Filippas & John J. Horton & Joseph M. Golden, 2022. "Reputation Inflation," Marketing Science, INFORMS, vol. 41(4), pages 733-745, July.
    11. Cai, Hongbin & Jin, Ginger Zhe & Liu, Chong & Zhou, Li-an, 2014. "Seller reputation: From word-of-mouth to centralized feedback," International Journal of Industrial Organization, Elsevier, vol. 34(C), pages 51-65.
    12. Casner, Ben, 2020. "Seller curation in platforms," International Journal of Industrial Organization, Elsevier, vol. 72(C).
    13. Andrei Hagiu & Bruno Jullien, 2011. "Why do intermediaries divert search?," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 337-362, June.
    Full references (including those not matched with items on IDEAS)

    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. Johnen, Johannes & Ng, Robin, 2023. "Ratings and Reciprocity," LIDAM Discussion Papers CORE 2023006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. 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.
    3. 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.
    4. 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.
    5. Paul Belleflamme & Martin Peitz, 2018. "Inside the Engine Room of Digital Platforms: Reviews, Ratings, and Recommendations," Working Papers halshs-01714549, HAL.
    6. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    7. Xiang Hui & Meng Liu & Tat Chan, 2023. "Targeted incentives, broad impacts: Evidence from an E-commerce platform," Quantitative Marketing and Economics (QME), Springer, vol. 21(4), pages 493-517, December.
    8. Xiang Hui & Meng Liu & Tat Chan, 2022. "Targeted Incentives, Broad Impacts: Evidence from an E-commerce Platform," CESifo Working Paper Series 9894, CESifo.
    9. Foster, Joshua, 2022. "How rating mechanisms shape user search, quality inference and engagement in online platforms: Experimental evidence," Journal of Business Research, Elsevier, vol. 142(C), pages 791-807.
    10. Anya Savikhin & Roman Sheremeta, 2010. "Visibility of Contributions and Cost of Information: An Experiment on Public Goods," Working Papers 10-22, Chapman University, Economic Science Institute.
    11. Lingfang (Ivy) Li & Steven Tadelis & Xiaolan Zhou, 2020. "Buying reputation as a signal of quality: Evidence from an online marketplace," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 965-988, December.
    12. Weijia (Daisy) Dai & Ginger Jin & Jungmin Lee & Michael Luca, 2018. "Aggregation of consumer ratings: an application to Yelp.com," Quantitative Marketing and Economics (QME), Springer, vol. 16(3), pages 289-339, September.
    13. Solimine, Philip & Isaac, R. Mark, 2023. "Reputation and market structure in experimental platforms," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 528-559.
    14. Zvika Neeman & Aniko Öry & Jungju Yu, 2019. "The benefit of collective reputation," RAND Journal of Economics, RAND Corporation, vol. 50(4), pages 787-821, December.
    15. repec:cep:stieop:56 is not listed on IDEAS
    16. Martin Peitz, 2024. "The Economic Theory of Two-Sided Platforms," CRC TR 224 Discussion Paper Series crctr224_2024_584, University of Bonn and University of Mannheim, Germany.
    17. Luís Cabral & Ali Hortacsu, 2004. "The Dynamics of Seller Reputation: Theory and Evidence from eBay," Working Papers 04-05, New York University, Leonard N. Stern School of Business, Department of Economics.
    18. Hortacsu, Ali, 2005. "Trust and Reputation on eBay: Micro and Macro Perspectives," Department of Economics, Working Paper Series qt8vj7d50q, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    19. Lingfang (Ivy) Li & Erte Xiao, 2014. "Money Talks: Rebate Mechanisms in Reputation System Design," Management Science, INFORMS, vol. 60(8), pages 2054-2072, August.
    20. Andreas J. Steur & Mischa Seiter, 2021. "Properties of feedback mechanisms on digital platforms: an exploratory study," Journal of Business Economics, Springer, vol. 91(4), pages 479-526, May.
    21. Anya Savikhin Samek & Roman Sheremeta, 2014. "Recognizing contributors: an experiment on public goods," Experimental Economics, Springer;Economic Science Association, vol. 17(4), pages 673-690, December.

    More about this item

    Keywords

    Reputation; Ratings; Ratings inflation; Seller reputation;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General

    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:cpr:ceprdp:18021. 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    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.