Consumer search in the U.S. auto industry: The role of dealership visits

Dan Yavorsky (), Elisabeth Honka () and Keith Chen ()
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Dan Yavorsky: University of California, Los Angeles
Elisabeth Honka: University of California, Los Angeles
Keith Chen: University of California, Los Angeles

Quantitative Marketing and Economics (QME), 2021, vol. 19, issue 1, No 1, 52 pages

Abstract: Abstract In many markets, consumers visit stores and physically inspect products before making purchase decisions. We view the inspection of a product at a retail location as a search for product fit. We quantify the cost and benefit from searching for product fit using a discrete choice model of demand with optimal sequential search. In these models, the benefit of searching is measured by the standard deviation of the product fit and has, heretofore, been fixed to one in estimation. We show that, with an exogenous search cost shifter, both the cost and benefit of searching can be separately estimated. Our empirical setting is the U.S. automotive market. We assemble a unique data set containing individual-level smartphone geolocation data that inform us about dealership visits. We also obtain information on new vehicle purchases from proprietary DMV registration data. Our exogenous cost shifter is the distance a consumer must travel to visit a dealership. Our results show that the benefit provided by dealerships to consumers is substantial. Within our empirical context, failure to estimate the standard deviation of the product fit leads to biased search cost and consumer surplus estimates and to inaccurate predictions regarding consumers’ number of searches and effects of at-home test drive programs.

Keywords: Consumer search; Automotive industry (search for similar items in EconPapers)
JEL-codes: D83 L62 M31 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11129-020-09229-4

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