IDEAS home Printed from https://ideas.repec.org/p/cer/papers/wp586.html
   My bibliography  Save this paper

Manipulation of Cursed Beliefs in Online Reviews

Author

Listed:
  • Ludmila Matyskova
  • Jan Sipek

Abstract

Consumer reviews may have perverse effects, including delays of adoption in new products of unknown quality when consumers are boundedly rational. When consumers fail to take into account that past reviewers self-select to purchases, a monopolist may manipulate the posterior beliefs of consumers who observe the reviews, because the product price determines the self-selection bias. The monopolist will charge a relatively high price because the positive selection of the early adopters increases the quality reported in the reviews.

Suggested Citation

  • Ludmila Matyskova & Jan Sipek, 2017. "Manipulation of Cursed Beliefs in Online Reviews," CERGE-EI Working Papers wp586, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    • Handle: RePEc:cer:papers:wp586
    as

    Download full text from publisher

    File URL: http://www.cerge-ei.cz/pdf/wp/Wp586.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    2. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    3. Subir Bose & Gerhard Orosel & Marco Ottaviani & Lise Vesterlund, 2006. "Dynamic monopoly pricing and herding," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 910-928, December.
    4. Subir Bose & Gerhard Orosel & Marco Ottaviani & Lise Vesterlund, 2008. "Monopoly pricing in the binary herding model," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 37(2), pages 203-241, November.
    5. Alexander L. Brown & Colin F. Camerer & Dan Lovallo, 2012. "To Review or Not to Review? Limited Strategic Thinking at the Movie Box Office," American Economic Journal: Microeconomics, American Economic Association, vol. 4(2), pages 1-26, May.
    6. Manaswini Bhalla, 2013. "Waterfall Versus Sprinkler Product Launch Strategy: Influencing the Herd," Journal of Industrial Economics, Wiley Blackwell, vol. 61(1), pages 138-165, March.
    7. Ting Liu & Pasquale Schiraldi, 2012. "New product launch: herd seeking or herd preventing?," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(3), pages 627-648, November.
    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. Alexei Parakhonyak & Nick Vikander, 2019. "Optimal Sales Schemes for Network Goods," Management Science, INFORMS, vol. 65(2), pages 819-841, February.
    2. Nicolás Figueroa & Carla Guadalupi, 2017. "Convincing early adopters: Price signals and Information transmission," Documentos de Trabajo 486, Instituto de Economia. Pontificia Universidad Católica de Chile..
    3. Aleksei Smirnov & Egor Starkov, 2022. "Bad News Turned Good: Reversal under Censorship," American Economic Journal: Microeconomics, American Economic Association, vol. 14(2), pages 506-560, May.
    4. Ting Liu & Pasquale Schiraldi, 2012. "New product launch: herd seeking or herd preventing?," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(3), pages 627-648, November.
    5. Alexei Parahonyak & Nick Vikander, 2024. "Strategic Use of Product Delays to Shape Word-of-Mouth Communication," Economics Series Working Papers 1032, University of Oxford, Department of Economics.
    6. James D. Campbell, 2015. "Localized price promotions as a quality signal in a publicly observable network," Quantitative Marketing and Economics (QME), Springer, vol. 13(1), pages 27-57, March.
    7. Tristan Gagnon-Bartsch & Antonio Rosato, 2024. "Quality Is in the Eye of the Beholder: Taste Projection in Markets with Observational Learning," American Economic Review, American Economic Association, vol. 114(11), pages 3746-3787, November.
    8. Parakhonyak, Alexei & Vikander, Nick, 2023. "Information design through scarcity and social learning," Journal of Economic Theory, Elsevier, vol. 207(C).
    9. Aoyagi, Masaki & Bhalla, Manaswini & Gunay, Hikmet, 2016. "Social learning and delay in a dynamic model of price competition," Journal of Economic Theory, Elsevier, vol. 165(C), pages 565-600.
    10. Gill, David & Sgroi, Daniel, 2008. "The Optimal Choice of Pre-launch Reviewer : How Best to Transmit Information using Tests and Conditional Pricing," The Warwick Economics Research Paper Series (TWERPS) 877, University of Warwick, Department of Economics.
    11. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    12. Hikmet Gunay, 2014. "Waiting for Signaling Quality," Southern Economic Journal, John Wiley & Sons, vol. 81(2), pages 364-386, October.
    13. Thaís L. D. Souza & Marislei Nishijima & Ana C. P. Fava, 2019. "Do consumer and expert reviews affect the length of time a film is kept on screens in the USA?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 145-171, March.
    14. Gill, David & Sgroi, Daniel, 2012. "The optimal choice of pre-launch reviewer," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1247-1260.
    15. Philipp Kircher & Andrew Postlewaite, 2008. "Strategic Firms and Endogenous Consumer Emulation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 621-661.
    16. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    17. Arieli, Itai & Koren, Moran & Smorodinsky, Rann, 2022. "The implications of pricing on social learning," Theoretical Economics, Econometric Society, vol. 17(4), November.
    18. Dipankar Das, 2022. "Measurement of Trustworthiness of the Online Reviews," Papers 2210.00815, arXiv.org, revised Nov 2023.
    19. Xitong Li, 2018. "Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold," Information Systems Research, INFORMS, vol. 29(3), pages 739-754, September.
    20. Yang, Wenjuan & Zhang, Jiantong & Yan, Hong, 2022. "Promotions of online reviews from a channel perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

    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:cer:papers:wp586. 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: Lucie Vasiljevova (email available below). General contact details of provider: https://edirc.repec.org/data/eiacacz.html .

    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.