IDEAS home Printed from https://ideas.repec.org/p/cmf/wpaper/wp2017_1716.html
   My bibliography  Save this paper

To Glance or to Peruse: Observational and Active Learning from Peer Consumers

Author

Listed:

Abstract

This paper examines consumer social learning patterns in decision making. I propose a novel model that decomposes the learning process into two stages: observational learning, where a consumer quickly updates the belief about a product after observing its salient social-based characteristics (such as popularity), and time-consuming active learning through descriptive information content (such as consumer reviews). By demonstrating the interplay between the two stages, the model brings together previous literature that studies these separately. I characterize the optimal learning time, and provide comparative statics which show that an increase in the discount rate or in the product’s economic value drives consumers to rely more on observational learning. I test this model using unique transaction-level data for air purifiers sold on a Chinese online platform from January to March 2014. Exploiting an unexpected air pollution crisis in late February 2014, I find that past sales have greater weight as a reference for comparison among products during the pollution crisis than in regular times. I also document that, after the episode, consumers rely less on observational learning compared to periods before the crisis, which is consistent with the model’s predictions as sales made during the crisis convey less information.

Suggested Citation

  • Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2017_1716, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2017_1716
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
    2. Mira Frick & Yuhta Ishii, 2015. "Innovation Adoption by Forward-Looking Social Learners," Cowles Foundation Discussion Papers 1877, Cowles Foundation for Research in Economics, Yale University.
    3. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    4. Kenneth Hendricks & Alan Sorensen & Thomas Wiseman, 2012. "Observational Learning and Demand for Search Goods," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 1-31, February.
    5. Bogaçhan Çelen & Shachar Kariv, 2004. "Distinguishing Informational Cascades from Herd Behavior in the Laboratory," American Economic Review, American Economic Association, vol. 94(3), pages 484-498, June.
    6. Uri Simonsohn & Dan Ariely, 2008. "When Rational Sellers Face Nonrational Buyers: Evidence from Herding on eBay," Management Science, INFORMS, vol. 54(9), pages 1624-1637, September.
    7. , & ,, 2010. "Strategic experimentation with Poisson bandits," Theoretical Economics, Econometric Society, vol. 5(2), May.
    8. Ramon Caminal & Xavier Vives, 1996. "Why Market Shares Matter: An Information-Based Theory," RAND Journal of Economics, The RAND Corporation, vol. 27(2), pages 221-239, Summer.
    9. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    10. Asher Wolinsky, 1986. "True Monopolistic Competition as a Result of Imperfect Information," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(3), pages 493-511.
    11. Manuel Mueller-Frank & Mallesh M. Pai, 2016. "Social Learning with Costly Search," American Economic Journal: Microeconomics, American Economic Association, vol. 8(1), pages 83-109, February.
    12. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    13. Simon P. Anderson & Regis Renault, 1999. "Pricing, Product Diversity, and Search Costs: A Bertrand-Chamberlin-Diamond Model," RAND Journal of Economics, The RAND Corporation, vol. 30(4), pages 719-735, Winter.
    14. Herrera, Helios & Hörner, Johannes, 2013. "Biased social learning," Games and Economic Behavior, Elsevier, vol. 80(C), pages 131-146.
    15. Hongbin Cai & Yuyu Chen & Hanming Fang, 2009. "Observational Learning: Evidence from a Randomized Natural Field Experiment," American Economic Review, American Economic Association, vol. 99(3), pages 864-882, June.
    16. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    17. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
    18. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    19. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    20. Juanjuan Zhang, 2010. "The Sound of Silence: Observational Learning in the U.S. Kidney Market," Marketing Science, INFORMS, vol. 29(2), pages 315-335, 03-04.
    21. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    22. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    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. Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2018_1716, CEMFI.
    2. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    3. Liangfei Qiu & Arunima Chhikara & Asoo Vakharia, 2021. "Multidimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Information Systems Research, INFORMS, vol. 32(3), pages 876-894, September.
    4. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    5. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    6. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    7. Shijie Lu & Dai Yao & Xingyu Chen & Rajdeep Grewal, 2021. "Do Larger Audiences Generate Greater Revenues Under Pay What You Want? Evidence from a Live Streaming Platform," Marketing Science, INFORMS, vol. 40(5), pages 964-984, September.
    8. Liangfei Qiu & Zhan (Michael) Shi & Andrew B. Whinston, 2018. "Learning from Your Friends’ Check-Ins: An Empirical Study of Location-Based Social Networks," Information Systems Research, INFORMS, vol. 29(4), pages 1044-1061, December.
    9. Yang Liu & Juan Feng & Xiuwu Liao, 2017. "When Online Reviews Meet Sales Volume Information: Is More or Accurate Information Always Better?," Information Systems Research, INFORMS, vol. 28(4), pages 723-743, December.
    10. Mina Ameri & Elisabeth Honka & Ying Xie, 2019. "Word of Mouth, Observed Adoptions, and Anime-Watching Decisions: The Role of the Personal vs. the Community Network," Marketing Science, INFORMS, vol. 38(4), pages 567-583, July.
    11. Zachary Mahone & Filippo Rebessi, 2019. "Consumer Learning and Firm Dynamics," Department of Economics Working Papers 2019-08, McMaster University.
    12. Engström, Per & Forsell, Eskil, 2018. "Demand effects of consumers’ stated and revealed preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 43-61.
    13. Stephanie De Mel & Kaivan Munshi & Soenje Reiche & Hamid Sabourian, 2021. "Herding with Heterogeneous Ability: An Application to Organ Transplantation," Cowles Foundation Discussion Papers 2308, Cowles Foundation for Research in Economics, Yale University.
    14. Anna K. Edenbrandt & Christian Gamborg & Bo Jellesmark Thorsen, 2020. "Observational learning in food choices: The effect of product familiarity and closeness of peers," Agribusiness, John Wiley & Sons, Ltd., vol. 36(3), pages 482-498, June.
    15. Chan, C.S. Richard & Parhankangas, Annaleena & Sahaym, Arvin & Oo, Pyayt, 2020. "Bellwether and the herd? Unpacking the u-shaped relationship between prior funding and subsequent contributions in reward-based crowdfunding," Journal of Business Venturing, Elsevier, vol. 35(2).
    16. Bobkova, Nina & Mass, Helene, 2022. "Two-dimensional information acquisition in social learning," Journal of Economic Theory, Elsevier, vol. 202(C).
    17. Jurui Zhang & Yong Liu & Yubo Chen, 2015. "Social Learning in Networks of Friends versus Strangers," Marketing Science, INFORMS, vol. 34(4), pages 573-589, July.
    18. Ali, S. Nageeb, 2018. "Herding with costly information," Journal of Economic Theory, Elsevier, vol. 175(C), pages 713-729.
    19. Thomas Stebro & Manuel Fernnndez Sierra & Stefano Lovo & Nir Vulkan, 2017. "Herding in Equity Crowdfunding," Working Papers hal-01970724, HAL.
    20. Amy Wenxuan Ding & Shibo Li, 2019. "Herding in the consumption and purchase of digital goods and moderators of the herding bias," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 460-478, May.

    More about this item

    Keywords

    Social learning; observational learning; word of mouth; consumer decision making.;
    All these keywords.

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    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:cmf:wpaper:wp2017_1716. 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: Araceli Requerey (email available below). General contact details of provider: https://edirc.repec.org/data/cemfies.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.