Search Revisits

Dang, Chu; Ursu, Raluca

doi:10.2139/ssrn.3626451

Cited by 4 publications

(1 citation statement)

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“…Researchers typically do not observe a consumer’s price beliefs (prior or posterior), which necessitates an assumption about the learning process and prior beliefs. 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).…”

Section: Related Literaturementioning

confidence: 99%

The Importance of Price Beliefs in Consumer Search

Jindal¹,

Aribarg²

2021

Journal of Marketing Research

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A consumer’s decision to engage in search depends on the beliefs the consumer has about an unknown product characteristic such as price. Given beliefs are rarely observed, researchers typically assume that consumers have rational expectations or update beliefs consistent with Bayesian updating. These assumptions are not only restrictive, but additionally, do not afford the researcher, or the retailer, an opportunity to price discriminate among consumers based on heterogeneity in beliefs. We first show, through Monte Carlo experiments, how these assumptions impact estimates of search cost. Next, we design an incentive-aligned online study where subjects search over the price of a homogeneous good, and we elicit distributions of price beliefs before and after each search. Based on data collected from a nationally representative panel, we find substantial heterogeneity in prior price beliefs. We find that subjects update their beliefs in response to search outcomes, but they deviate from Bayesian updating in that they under-react to new information. Importantly, we show that (i) assuming Bayesian updating does not significantly bias search cost estimates at the aggregate level provided the researcher accounts for heterogeneous prior beliefs, (ii) eliciting heterogeneity in prior expected prices is much more important than eliciting heterogeneity in prior price uncertainty, and (iii) a retailer can increase profits through third-degree price discrimination by recognizing the heterogeneity in prior beliefs.

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