Abstract

PurposeWhile prior research has investigated factors that predict consumers’ information search behaviors as they relate to automobiles, such studies were conducted prior to the COVID-19 pandemic. Given that the pandemic has necessitated lockdowns, social distancing, business closures and other disruptions to normal shopping activities, consumer information search behaviors have also been substantially altered as the psychological distance between consumers and marketers has increased. Thus, this study aims to examine these changes and identify patterns of search behavior for a major durable product: automobiles.Design/methodology/approachUsing survey data from before and during the pandemic, the study implements Finite Mixture Modeling to unveil latent segments of U.S. consumers’ search behaviors and choices for Japanese automobiles. This analytic method enables capturing consumer unobserved heterogeneity through mixing probabilities guided by individual characteristics. These segments are determined based on consumers’ information search for online and offline marketer-controlled and nonmarketer-controlled sources.FindingsThe study identifies that two segments of consumers emerge both prior to the pandemic and during the pandemic. These empirically validated findings indicate that the pandemic has led to shifts in consumers’ information search behaviors for Japanese automobiles by relying more on nonmarketer-controlled sources of information.Originality/valueThis work is among the first comprehensive empirical analyses of consumer search for a major durable product by comparing pre- and during pandemic patterns. Using analytics and econometrics, the first-hand analysis findings offer meaningful implications for marketers and product managers in the automotive industry.

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