Marketing Science
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MARKETING SCIENCE
Vol. 25, No. 6, November-December 2006, pp. 625-628
DOI: 10.1287/mksc.1050.0190
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Invited Commentary—Dynamic Structural Consumer Models and Current Marketing Issues

Baohong Sun

Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213
bsun{at}andrew.cmu.edu

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.

Key Words: structural model; information processing; rational expectations; optimal decision; hyperbolic discounting; information asymmetry; signaling; searching; learning; e-commerce; dynamic and interactive marketing intervention; decision support system






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