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Consumer search with observational learning

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  • Daniel Garcia
  • Sandro Shelegia

Abstract

This article studies observational learning in a consumer search environment. Consumers observe the purchasing decision of a predecessor with similar preferences. Consumers rationally emulate by initiating their search at the firm from which their predecessor purchased, free†riding on search effort, and reacting less to price changes. Prices are nonmonotone in search costs and may be as low as marginal costs. We discuss several extensions and show that the effect of emulation on prices is stronger when (i) the number of firms increases, (ii) consumers' first visits are more elastic with respect to market shares, and (iii) prices are adjusted more frequently.

Suggested Citation

  • Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    • Handle: RePEc:bla:randje:v:49:y:2018:i:1:p:224-253
    DOI: 10.1111/1756-2171.12224
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    Citations

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    Cited by:

    1. Daniel Garcia, 2017. "Dynamic Pricing with Search Frictions," Vienna Economics Papers vie1703, University of Vienna, Department of Economics.
    2. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    3. Marcel Preuss, 2023. "Search, learning, and tracking," RAND Journal of Economics, RAND Corporation, vol. 54(1), pages 54-82, March.
    4. Haan, Marco A. & Moraga-González, José L. & Petrikaitė, Vaiva, 2018. "A model of directed consumer search," International Journal of Industrial Organization, Elsevier, vol. 61(C), pages 223-255.
    5. Zachary Mahone & Filippo Rebessi, 2019. "Consumer Learning and Firm Dynamics," Department of Economics Working Papers 2019-08, McMaster University.
    6. Atayev, Atabek & Janssen, Maarten C. W., 2021. "Information acquisition and diffusion in markets," ZEW Discussion Papers 21-091, ZEW - Leibniz Centre for European Economic Research.
    7. Honka, Elisabeth & Seiler, Stephan & Ursu, Raluca, 2024. "Consumer search: What can we learn from pre-purchase data?," Journal of Retailing, Elsevier, vol. 100(1), pages 114-129.
    8. Ding, Yucheng & Zhang, Tianle, 2018. "Price-directed consumer search," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 106-135.
    9. Carlo Reggiani & Alejandro Saporiti & Lois Simanjuntak, 2018. "Social Information and Consumer Heterogeneity," Economics Discussion Paper Series 1813, Economics, The University of Manchester.
    10. Martin Obradovits & Philipp Plaickner, 2023. "Price-Directed Search, Product Differentiation and Competition," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 63(3), pages 317-348, November.
    11. Janssen, Maarten & Williams, Cole, 2021. "Influencing Search," CEPR Discussion Papers 15811, C.E.P.R. Discussion Papers.
    12. Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2018_1716, CEMFI.
    13. Atabek Atayev & Maarten Janssen, 2021. "Information Acquisition and Diffusion in Markets," Papers 2109.15288, arXiv.org.
    14. 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.
    15. T. Tony Ke & Song Lin, 2020. "Informational Complementarity," Management Science, INFORMS, vol. 66(8), pages 3699-3716, August.
    16. Gamp, Tobias & Krähmer, Daniel, 2022. "Biased Beliefs in Search Markets," Rationality and Competition Discussion Paper Series 365, CRC TRR 190 Rationality and Competition.
    17. Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2017_1716, CEMFI.
    18. Gagnon-Bartsch, Tristan & Rosato, Antonio, 2022. "Quality is in the eye of the beholder: taste projection in markets with observational learning," MPRA Paper 115426, University Library of Munich, Germany.
    19. Daniel Garcia, 2017. "Dynamic Pricing with Search Frictions," CESifo Working Paper Series 6765, CESifo.

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    More about this item

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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