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—Dynamic Structural Consumer Models and Current Marketing Issues

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  • Baohong Sun

    (Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213)

Abstract

Structural models integrate behavioral and psychological decision theory into economics models and are more aligned with the true underlying economic primitives of the consumers. This allows researchers to investigate more behavior-driven and process-oriented customer decision processes such as learning of product attributes, formation of a consideration sets, stockpiling, and flexible consumption that cannot be easily handled by traditional marketing models. Chintagunta et al. (2006) gives an excellent review on the development and applications of structural models in marketing for modeling both consumer demand and firm competition. Recent interests in consumer research have diversified from frequently purchased packaged goods to services, high-tech, Internet, and information industries. Consumers are observed to be more sophisticated, long-term oriented, risk averse, and rational when making purchase and consumption decisions in these product categories. Structural models are better choices to capture the nature of the sophisticated decision process under the new marketing environment and engineering. Given the thorough review of Chintagunta et al. (2006), I will focus only on the dynamic structural demand models that have the components of information processing, rational expectation, and/or endogenous decisions to trade off current and future utilities, and I discuss some current marketing issues that can be most appropriately addressed by these models.

Suggested Citation

  • Baohong Sun, 2006. "—Dynamic Structural Consumer Models and Current Marketing Issues," Marketing Science, INFORMS, vol. 25(6), pages 625-628, 11-12.
  • Handle: RePEc:inm:ormksc:v:25:y:2006:i:6:p:625-628
    DOI: 10.1287/mksc.1050.0190
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    References listed on IDEAS

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    1. Pedro M. Gardete & Carlos D. Santos, 2020. "No data? No problem! A Search-based Recommendation System with Cold Starts," Papers 2010.03455, arXiv.org.
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