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2004), "Learning About Computers: An Analysis of Information Search and Technology Choice," Working Paper

By Tülin Erdem, Michael P. Keane, Sabri Öncü and Judi Strebel

Abstract

We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs), with an emphasis on the choice between the IBM/Compatible and Apple/Macintosh technologies. To estimate the model we use a unique panel data set collected in collaboration with a major U.S. PC manufacturer. The data contain a wealth of information on the search behavior of a set of consumers who were in the market for a PC, and who were interviewed at 7-week intervals over a 10-month period. The data record the information sources visited each period, search durations, brand purchased and price paid, 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 about brand attributes. Specifically, while several authors have recently estimated models of passive learning about brand attributes, the present paper is, to our knowledge, the first attempt to estimate a model of active learning – i.e., a model in which consumers make optimal sequential decisions about ho

Topics: Acknowledgements, We thank seminar participants at Harvard, MIT, Northwestern, the
Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.416.9332
Provided by: CiteSeerX
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