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Learning About Computers: An Analysis of Information Search and Technology Choice

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  • Tülin Erdem

    ()

  • Michael Keane

    ()

  • T. Öncü

    ()

  • Judi Strebel

    ()

Abstract

We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs). To estimate the model, we use a panel data set that contains the search and purchase behavior of a set of consumers who were in the market for a PC. The data includes the information sources visited each period, search durations, as well as measures of price expectations and stated attitudes toward the alternatives during the search process. Our model extends recent work on estimation of Bayesian learning models of consumer choice behavior in environments characterized by uncertainty by estimating a model of active learning—i.e., a model in which consumers make optimal sequential decisions about how much information to gather prior to making a purchase. Also, following the suggestion of Manski (2003), we use our data on price expectations to model consumers’ price expectation process, and, following the suggestion of McFadden (1989a), we incorporate the stated brand quality information into our likelihood function, rather than modeling only revealed preference data. Our analysis sheds light on how consumer forward-looking price expectations and the process of learning about quality influence the consumer choice process. A key finding is that estimates of dynamic price elasticities of demand exceed estimates that ignore the expectations effect by roughly 50%. This occurs because our estimated expectations formation process implies that consumers expect mean reversion in price changes. This enhances the impact of a temporary price cut. Finally, while our work focuses specifically on the PC market, the modeling approach we develop here may be useful for studying a wide range of high-tech, high-involvement durable goods markets where active learning is important. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 207-247, September.
  • Handle: RePEc:kap:qmktec:v:3:y:2005:i:3:p:207-247
    DOI: 10.1007/s11129-005-0269-7
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    References listed on IDEAS

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    Cited by:

    1. Hai Che & Tülin Erdem & T. Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    2. Lou, Weifang & Prentice, David & Yin, Xiangkang, 2008. "The Effects of Product Ageing on Demand: The Case of Digital Cameras," MPRA Paper 13407, University Library of Munich, Germany.
    3. Anindya Ghose & Sang Pil Han, 2009. "A Dynamic Structural Model of User Learning in Mobile Media Content," Working Papers 09-24, NET Institute, revised Oct 2009.
    4. Tao Chen & Baohong Sun & Vishal Singh, 2009. "An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift," Marketing Science, INFORMS, vol. 28(4), pages 740-758, 07-08.
    5. Caspar G. Chorus & Benedict G. C. Dellaert, 2012. "Travel Choice Inertia: The Joint Role of Risk Aversion and Learning," Journal of Transport Economics and Policy, University of Bath, vol. 46(1), pages 139-155, January.
    6. Michael P. Keane, 2011. "Labor Supply and Taxes: A Survey," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 961-1075, December.
    7. Adeline Delavande & Hans-Peter Kohler, 2009. "Subjective expectations in the context of HIV/AIDS in Malawi," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 20(31), pages 817-875, June.
    8. Tülin Erdem & Kannan Srinivasan & Wilfred Amaldoss & Patrick Bajari & Hai Che & Teck Ho & Wes Hutchinson & Michael Katz & Michael Keane & Robert Meyer & Peter Reiss, 2005. "Theory-Driven Choice Models," Marketing Letters, Springer, vol. 16(3), pages 225-237, December.
    9. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    10. Erik Maier & Robert Wilken & Florian Dost, 2015. "The double benefits of consumer certainty: combining risk and range effects," Marketing Letters, Springer, vol. 26(4), pages 473-488, December.
    11. Keane, Michael, 2010. "The Tax-Transfer System and Labour Supply," MPRA Paper 55167, University Library of Munich, Germany.
    12. Oded Netzer & Olivier Toubia & Eric Bradlow & Ely Dahan & Theodoros Evgeniou & Fred Feinberg & Eleanor Feit & Sam Hui & Joseph Johnson & John Liechty & James Orlin & Vithala Rao, 2008. "Beyond conjoint analysis: Advances in preference measurement," Marketing Letters, Springer, vol. 19(3), pages 337-354, December.
    13. Gerald Häubl & Benedict G. C. Dellaert & Bas Donkers, 2010. "Tunnel Vision: Local Behavioral Influences on Consumer Decisions in Product Search," Marketing Science, INFORMS, vol. 29(3), pages 438-455, 05-06.
    14. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    15. Brian Blackburn & Aprajit Mahajan & Alessandro Tarozzi & Joanne Yoong, 2009. "Bednets, Information and Malaria in Orissa," Discussion Papers 08-025, Stanford Institute for Economic Policy Research.
    16. S. Sriram & Pradeep K. Chintagunta & Manoj K. Agarwal, 2010. "Investigating Consumer Purchase Behavior in Related Technology Product Categories," Marketing Science, INFORMS, vol. 29(2), pages 291-314, 03-04.
    17. Yan Liu & Subramanian Balachander, 2014. "How long has it been since the last deal? Consumer promotion timing expectations and promotional response," Quantitative Marketing and Economics (QME), Springer, vol. 12(1), pages 85-126, March.
    18. Marcoul, Philippe & Weninger, Quinn, 2008. "Search and active learning with correlated information: Empirical evidence from mid-Atlantic clam fishermen," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1921-1948, June.
    19. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    20. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 325-349, December.
    21. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    22. Matthew Osborne, 2011. "Consumer learning, switching costs, and heterogeneity: A structural examination," Quantitative Marketing and Economics (QME), Springer, vol. 9(1), pages 25-70, March.
    23. Pamela Giustinelli, 2011. "Group Decision Making with Uncertain Outcomes: Unpacking Child-Parent Choices of High School Tracks," Working Papers 2011-030, Human Capital and Economic Opportunity Working Group.
    24. Praveen K. Kopalle & Yacheng Sun & Scott A. Neslin & Baohong Sun & Vanitha Swaminathan, 2012. "The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs," Marketing Science, INFORMS, vol. 31(2), pages 216-235, March.

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