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Testing Models of Consumer Search Using Data on Web Browsing Behavior

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Abstract

Using a large data set on consumers' web browsing and purchasing behavior we contrast various classical search models. We find that the benchmark model of sequential search with a known distributions of prices can be rejected based on the recall patterns we observe in the data. Moreover, we show that even if consumers are initially unaware of the price distribution and have to learn the price distribution, observed search behavior for given consumers over time is more consistent with non-sequential search than sequential search with learning. Our findings suggest non-sequential search provides a more accurate description of observed consumer search behavior. We then utilize the non-sequential search model to estimate the price elasticities and markups of online book retailers.

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File URL: http://www.netinst.org/DelosSantos_Hortacsu_Wildenbeest_09-23.pdf
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Bibliographic Info

Paper provided by NET Institute in its series Working Papers with number 09-23.

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Length: 34 pages
Date of creation: Aug 2009
Date of revision: Aug 2009
Handle: RePEc:net:wpaper:0923

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Web page: http://www.NETinst.org/

Related research

Keywords: search costs; sequential search; fixed-sample search; non-sequential search; online browsing; online book industry; consumer search;

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