Search Duration

Abstract

This paper develops and estimates a model of sequential search that accounts for the full set of decisions consumers make while searching (which products to search, search longevity, sequence of purchases, and whether to purchase).

The Importance of Price Beliefs in Consumer Search

“…Compared with previous literature, in which high search costs can be attributed to whether individuals make decisions on the basis of marginal or total returns (Kogut 1990;Sonnemans 1998), observed partial or incomplete search history (Bronnenberg, Kim, and Mela 2016), assumed search method (Honka and Chintagunta 2017), heuristic rules (Camerer 1995;Zwick et al 2003), or how paid search (Blake, Nosko, and Tadelis 2015) or recommendations (Dellaert and Häubl 2012) are accounted for, we show that ignoring heterogeneity in prior beliefs can result in overestimating search costs even in the absence of paid search or recommendations and when the complete search history and search method are known. Our results, thus, lend support to the more recent literature in marketing that estimates and allows for heterogeneity in prior beliefs (Ursu, Wang, and Chintagunta 2020;Zhang, Ursu, and Erdem 2020).…”

“…Previous literature assumes either that consumers have rational expectations and do not learn about the price distribution (Honka 2014; Honka and Chintagunta 2017; Mehta, Rajiv, and Srinivasan 2003; Zwick et al 2003) or that consumers update their beliefs, which can explain revisits to previously searched information (Bronnenberg, Kim, and Mela 2016; Dang, Ursu, and Chintagunta 2020). The empirical literature allowing for learning assumes that consumers engage in Bayesian updating with either normally distributed priors (Chick and Frazier 2012; Ursu, Wang, and Chintagunta 2020; Zhang, Ursu, and Erdem 2020), Dirichlet priors (Hu, Dang, and Chintagunta 2019; Koulayev 2013; Wu 2017), or Dirichlet process priors (De los Santos, Hortacsu, and Wildenbeest 2017; Häubl, Dellaert, and Donkers 2010).…”

“…While previous research assumes that consumers have an informative prior (De los Santos, Hortacsu, and Wildenbeest 2017; Koulayev 2013), such that the expected value of the realizations from the process that generates prior beliefs corresponds to the true distribution of prices, more recent research attempts to estimate prior beliefs from observational data (Hu, Dang, and Chintagunta 2019; Ursu, Wang, and Chintagunta 2020; Zhang, Ursu, and Erdem 2020). Hu, Dang, and Chintagunta (2019) use relative variation in clicking and purchase to estimate Dirichlet prior beliefs that are homogeneous across consumers.…”

“…Hu, Dang, and Chintagunta (2019) use relative variation in clicking and purchase to estimate Dirichlet prior beliefs that are homogeneous across consumers. By contrast, Ursu, Wang, and Chintagunta (2020) and Zhang, Ursu, and Erdem (2020) estimate heterogeneous prior uncertainty either as latent segments or as a function of the prior consumer experience using eye-tracking data, respectively. Zhang, Ursu, and Erdem also model heterogeneous expected beliefs as a function of prior ownership.…”

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

“…Note that some of the average parameter estimates are not within two standard errors of their true values. This is not uncommon for search models estimated using SMLE (see, e.g., Honka 2014 ; Ursu 2018 ; Ursu et al 2020 ). 21…”