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Adaptive Learning Models of Consumer Behaviour (first version)

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Abstract

This paper applies recent advances in the theory of learning to the analysis of consumer behaviour. The working assumption is that while sellers are rational in the traditional sense, consumers are boundedly rational. The differences in outcomes for search goods and experience goods are investigated. In the latter case, if consumers fail to take into account that information is only partial, they can become locked into the habit of purchasing inferior goods. Surprisingly, however, prices are lower than when information is complete. Firms have an incentive to offer lower prices to prevent consumers becoming locked into their rival's product.

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  • Ed Hopkins, 2002. "Adaptive Learning Models of Consumer Behaviour (first version)," Edinburgh School of Economics Discussion Paper Series 80, Edinburgh School of Economics, University of Edinburgh.
  • Handle: RePEc:edn:esedps:80
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    References listed on IDEAS

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    1. Fishman, Arthur & Rob, Rafael, 1998. "Experimentation and Competition," Journal of Economic Theory, Elsevier, vol. 78(2), pages 299-320, February.
    2. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    3. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    4. Ed Hopkins & Robert M. Seymour, 2002. "The Stability of Price Dispersion under Seller and Consumer Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1157-1190, November.
    5. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November.
    6. Rustichini, Aldo, 1999. "Optimal Properties of Stimulus--Response Learning Models," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 244-273, October.
    7. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Imperfect Competition: On the Existence of Equilibrium," Econometrica, Econometric Society, vol. 59(1), pages 25-59, January.
    8. C. Monica Capra & Jacob K Goeree & Rosario Gomez & Charles A Holt, 2002. "Learning and Noisy Equilibrium Behavior in an Experimental Study of Imperfect Price Competition," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(3), pages 613-636, August.
    9. Kyle Bagwell & Garey Ramey, 1994. "Advertising and Coordination," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(1), pages 153-171.
    10. Borgers, Tilman & Sarin, Rajiv, 2000. "Naive Reinforcement Learning with Endogenous Aspirations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 921-950, November.
    11. Hopkins, Ed, 1999. "Learning, Matching, and Aggregation," Games and Economic Behavior, Elsevier, vol. 26(1), pages 79-110, January.
    12. Pradeep K. Chintagunta & Vithala R. Rao, 1996. "Pricing Strategies in a Dynamic Duopoly: A Differential Game Model," Management Science, INFORMS, vol. 42(11), pages 1501-1514, November.
    13. Erdem, Tulin & Broniarczyk, Susan & Charavarti, Dipankar & Kapferer, Jean-Noel & Keane, Michael & Roberts, John & Steenkamp, Jan-Benedict & Swait, Joffre & Zettelmeyer, Florian, 1999. "Brand Equity, Consumer Learning and Choice," MPRA Paper 53022, University Library of Munich, Germany.
    14. Chen, Yongmin & Rosenthal, Robert W., 1996. "Dynamic duopoly with slowly changing customer loyalties," International Journal of Industrial Organization, Elsevier, vol. 14(3), pages 269-296, May.
    15. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    16. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
    17. Sarin, Rajiv & Vahid, Farshid, 1999. "Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice," Games and Economic Behavior, Elsevier, vol. 28(2), pages 294-309, August.
    18. To, Theodore, 1996. "Multi-period Competition with Switching Costs: An Overlapping Generations Formulation," Journal of Industrial Economics, Wiley Blackwell, vol. 44(1), pages 81-87, March.
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