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—Commentary on Structural Modeling in Marketing: Review and Assessment

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  • Tat Y. Chan

    (John M. Olin School of Business, Washington University, St. Louis, Missouri 63130)

Abstract

Chintagunta, Erdem, Rossi, and Wedel (2006) (CERW) discuss many different issues related to the use of structural models in marketing. They use examples of structural models that involve both consumer demand and supply-side competition to provide a critical assessment of the strengths and weaknesses of structural modeling and its future in marketing. While they have done a very nice job, the purpose of this commentary is to provide additional discussion of the three issues raised in their paper.

Suggested Citation

  • Tat Y. Chan, 2006. "—Commentary on Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 633-634, 11-12.
    • Handle: RePEc:inm:ormksc:v:25:y:2006:i:6:p:633-634
    DOI: 10.1287/mksc.1060.0232
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    References listed on IDEAS

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    1. Ariel Pakes, 2003. "Common Sense and Simplicity in Empirical Industrial Organization," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 23(3), pages 193-215, December.
    2. Patrick Bajari & Ali Hortacsu, 2005. "Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data," Journal of Political Economy, University of Chicago Press, vol. 113(4), pages 703-741, August.
    3. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    4. Jean-Pierre Dubé, 2004. "Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks," Marketing Science, INFORMS, vol. 23(1), pages 66-81, September.
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    Cited by:

    1. Leigh McAlister, 2016. "Rigor versus method imperialism," Journal of the Academy of Marketing Science, Springer, vol. 44(5), pages 565-567, September.
    2. Xiaojing Dong & Pradeep Chintagunta & Puneet Manchanda, 2011. "A new multivariate count data model to study multi-category physician prescription behavior," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 301-337, September.
    3. Kevin Chung, 2020. "Incorporating a “Better” Behavioral Bias for Both Consumers and Firms in Rebate Programs," Management Science, INFORMS, vol. 66(4), pages 1627-1646, April.

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