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Empirical Models of Learning Dynamics: A Survey of Recent Developments

In: Handbook of Marketing Decision Models

Author

Listed:
  • Andrew T. Ching

    (University of Toronto)

  • Tülin Erdem

    (New York University)

  • Michael P. Keane

    (University of Oxford)

Abstract

There is now a very large literature on dynamic learning modelsDynamic models in marketing. Learning dynamics can be broadly defined as encompassing any process whereby the prior history of a consumer or market affects current utility evaluations (e.g., social learning, search, correlated learning, information spillover, etc.). In the present chapter, we focus on discussing this rapidly growing literature that deals with this broader view of learning dynamics.

Suggested Citation

  • Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2017. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," International Series in Operations Research & Management Science, in: Berend Wierenga & Ralf van der Lans (ed.), Handbook of Marketing Decision Models, edition 2, chapter 0, pages 223-257, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-56941-3_8
    DOI: 10.1007/978-3-319-56941-3_8
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    Cited by:

    1. Guofang Huang & Hong Luo & Jing Xia, 2019. "Invest in Information or Wing It? A Model of Dynamic Pricing with Seller Learning," Management Science, INFORMS, vol. 65(12), pages 5556-5583, December.
    2. Victor Aguirregabiria & Jihye Jeon, 2020. "Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(2), pages 203-235, March.
    3. Arjen van Lin & Els Gijsbrechts, 2019. "“Hello Jumbo!” The Spatio-Temporal Rollout and Traffic to a New Grocery Chain After Acquisition," Management Science, INFORMS, vol. 67(5), pages 2388-2411, May.
    4. Haijing Hao & Rema Padman & Baohong Sun & Rahul Telang, 2019. "Modeling social learning on consumers’ long-term usage of a mobile technology: a Bayesian estimation of a Bayesian learning model," Electronic Commerce Research, Springer, vol. 19(1), pages 1-21, March.
    5. Mandy Mantian Hu & Sha Yang & Daniel Yi Xu, 2019. "Understanding the Social Learning Effect in Contagious Switching Behavior," Management Science, INFORMS, vol. 65(10), pages 4771-4794, October.
    6. Yanhao Max Wei, 2020. "The Similarity Network of Motion Pictures," Management Science, INFORMS, vol. 66(4), pages 1647-1671, April.
    7. van Ewijk, Bernadette J. & Gijsbrechts, Els & Steenkamp, Jan-Benedict E.M., 2022. "The dark side of innovation: How new SKUs affect brand choice in the presence of consumer uncertainty and learning," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 967-987.
    8. Limin Fang, 2022. "The Effects of Online Review Platforms on Restaurant Revenue, Consumer Learning, and Welfare," Management Science, INFORMS, vol. 68(11), pages 8116-8143, November.
    9. Andrew T. Ching & Hyunwoo Lim, 2020. "A Structural Model of Correlated Learning and Late-Mover Advantages: The Case of Statins," Management Science, INFORMS, vol. 66(3), pages 1095-1123, March.
    10. Abhijit Banerjee & Esther Duflo & Daniel Keniston & Nina Singh, 2019. "The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India," NBER Working Papers 26224, National Bureau of Economic Research, Inc.
    11. Shunyao Yan & Klaus M. Miller & Bernd Skiera, 2020. "How Does the Adoption of Ad Blockers Affect News Consumption?," Papers 2005.06840, arXiv.org, revised Aug 2021.
    12. Hu, Yingyao, 2017. "The Econometrics of Unobservables -- Latent Variable and Measurement Error Models and Their Applications in Empirical Industrial Organization and Labor Economics [The Econometrics of Unobservables]," Economics Working Paper Archive 64578, The Johns Hopkins University,Department of Economics, revised 2021.
    13. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2020. "How much do consumers know about the quality of products? Evidence from the diaper market," The Japanese Economic Review, Springer, vol. 71(4), pages 541-569, October.

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