IDEAS home Printed from https://ideas.repec.org/a/bla/jindec/v71y2023i3p883-923.html
   My bibliography  Save this article

Shopping for Information: Implications of Consumer Learning for Optimal Pricing and Product Design

Author

Listed:
  • Marilyn Pease

Abstract

I study a seller's pricing problem where consumers perform costly product research about value before purchase. They buy the product when sufficiently optimistic about value and cease research when sufficiently pessimistic. I find that the seller encourages product research when prior belief about value is high, even though he could sell immediately for a high price. The prior affects both expected value and how additional information changes consumers' beliefs. I show that an increase in research cost affects equilibrium price nonmonotonically. Finally, when the seller chooses price and product value dispersion, the optimal level of dispersion need not be extremal.

Suggested Citation

  • Marilyn Pease, 2023. "Shopping for Information: Implications of Consumer Learning for Optimal Pricing and Product Design," Journal of Industrial Economics, Wiley Blackwell, vol. 71(3), pages 883-923, September.
    • Handle: RePEc:bla:jindec:v:71:y:2023:i:3:p:883-923
    DOI: 10.1111/joie.12333
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/joie.12333
    Download Restriction: no
    File URL: https://libkey.io/10.1111/joie.12333?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
    ---><---

    References listed on IDEAS

    as
    1. Yiangos Papanastasiou & Nicos Savva, 2017. "Dynamic Pricing in the Presence of Social Learning and Strategic Consumers," Management Science, INFORMS, vol. 63(4), pages 919-939, April.
    2. Lang, Ruitian, 2019. "Try before you buy: A theory of dynamic information acquisition," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1057-1093.
    3. Fernando Branco & Monic Sun & J. Miguel Villas-Boas, 2016. "Too Much Information? Information Provision and Search Costs," Marketing Science, INFORMS, vol. 35(4), pages 605-618, July.
    4. Dina Mayzlin & Jiwoong Shin, 2011. "Uninformative Advertising as an Invitation to Search," Marketing Science, INFORMS, vol. 30(4), pages 666-685, July.
    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. Mohsen Foroughifar & David Soberman, 2021. "Is More Precise Word of Mouth Better for a High Quality Firm? ... Not Always," Papers 2105.01040, arXiv.org, revised Apr 2022.
    2. Monic Sun & Rajeev K. Tyagi, 2020. "Product Fit Uncertainty and Information Provision in a Distribution Channel," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2381-2402, October.
    3. Yue Wu & Tansev Geylani, 2020. "Regulating Deceptive Advertising: False Claims and Skeptical Consumers," Marketing Science, INFORMS, vol. 39(4), pages 788-806, July.
    4. Yuetao Gao & Yue Wu, 2023. "Regulating Probabilistic Selling of Counterfeits," Management Science, INFORMS, vol. 69(8), pages 4498-4517, August.
    5. Yi Zhu & Anthony Dukes, 2017. "Prominent Attributes Under Limited Attention," Marketing Science, INFORMS, vol. 36(5), pages 683-698, September.
    6. Liang Guo & Yue Wu, 2016. "Consumer deliberation and quality signaling," Quantitative Marketing and Economics (QME), Springer, vol. 14(3), pages 233-269, September.
    7. Vasudha Jain & Mark Whitmeyer, 2021. "Search and Competition with Flexible Investigations," Papers 2104.13159, arXiv.org.
    8. Alexandre de Corniere, 2013. "Search Advertising," Economics Series Working Papers 649, University of Oxford, Department of Economics.
    9. Pedro M. Gardete & Liang Guo, 2021. "Prepurchase Information Acquisition and Credible Advertising," Management Science, INFORMS, vol. 67(3), pages 1696-1717, March.
    10. T. Tony Ke & Jiwoong Shin & Jungju Yu, 2023. "A Model of Product Portfolio Design: Guiding Consumer Search Through Brand Positioning," Marketing Science, INFORMS, vol. 42(6), pages 1101-1124, November.
    11. Randall Lewis & Dan Nguyen, 2015. "Display advertising’s competitive spillovers to consumer search," Quantitative Marketing and Economics (QME), Springer, vol. 13(2), pages 93-115, June.
    12. Davide Crapis & Bar Ifrach & Costis Maglaras & Marco Scarsini, 2017. "Monopoly Pricing in the Presence of Social Learning," Management Science, INFORMS, vol. 63(11), pages 3586-3608, November.
    13. Yi Qian & Qiang Gong & Yuxin Chen, 2015. "Untangling Searchable and Experiential Quality Responses to Counterfeits," Marketing Science, INFORMS, vol. 34(4), pages 522-538, July.
    14. Caldieraro, Fabio & Cunha, Marcus, 2022. "Consumers’ response to weak unique selling propositions: Implications for optimal product recommendation strategy," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 724-744.
    15. Figueroa, Nicolás & Guadalupi, Carla, 2021. "Testing the sender: When signaling is not enough," Journal of Economic Theory, Elsevier, vol. 197(C).
    16. Liang Guo, 2022. "Strategic Communication Before Price Haggling: A Tale of Two Orientations," Marketing Science, INFORMS, vol. 41(5), pages 922-940, September.
    17. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
    18. Baojun Jiang & Kinshuk Jerath & Kannan Srinivasan, 2011. "Firm Strategies in the "Mid Tail" of Platform-Based Retailing," Marketing Science, INFORMS, vol. 30(5), pages 757-775, September.
    19. Jungju Yu, 2021. "A Model of Brand Architecture Choice: A House of Brands vs. A Branded House," Marketing Science, INFORMS, vol. 40(1), pages 147-167, January.
    20. Ivan A. Guitart & Guillaume Hervet & Sarah Gelper, 2020. "Competitive advertising strategies for programmatic television," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 753-775, July.

    More about this item

    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:bla:jindec:v:71:y:2023:i:3:p:883-923. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0022-1821 .

    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.