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Testing Competitive Market Structures


Author Info

  • Glen L. Urban

    (Massachusetts Institute of Technology)

  • Philip L. Johnson

    (Management Decision Systems, Inc.)

  • John R. Hauser

    (Massachusetts Institute of Technology)


An accurate understanding of the structure of competition is important in the formulation of many marketing strategies. For example, in new product launch, product reformulation, or positioning decisions, the strategist wants to know which of his competitors will be most affected and hence most likely to respond. Many marketing science models have been proposed to identify market structure. In this paper we examine the managerial problem and propose a criterion by which to judge an identified market structure. Basically, our criterion is a quantification of the intuitive managerial criterion that a “submarket” is a useful conceptualization if it identifies which products are most likely to be affected by “our” marketing strategies. We formalize this criterion within the structure of classical hypothesis testing so that a marketing scientist can use statistical statements to evaluate a market structure identified by: (1) behavioral hypotheses, (2) managerial intuition, or (3) market structure identification algorithms. Mathematically, our criterion is based on probabilities of switching to products in the situation where an individual's most preferred product is not available. ‘Submarkets' are said to exist when consumers are statistically more likely to buy again in that ‘submarket' than would be predicted based on an aggregate “constant ratio” model. For example, product attributes (e.g., brand, form, size), use situations (e.g., coffee in the morning versus coffee at dinner), and user characteristics (e.g., heavy versus light users) are specified as hypotheses for testing alternate competitive structures. Measurement and estimation procedures are described and a convergent approach is illustrated. An application of the methodology to the coffee market is presented and managerial implications of six other applications are described briefly.

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Bibliographic Info

Article provided by INFORMS in its journal Marketing Science.

Volume (Year): 3 (1984)
Issue (Month): 2 ()
Pages: 83-112

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Handle: RePEc:inm:ormksc:v:3:y:1984:i:2:p:83-112

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Related research

Keywords: market structure; competitive strategy; product line; entry opportunities;


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Cited by:
  1. Sri Duvvuri & Thomas Gruca, 2010. "A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities Across Categories," Psychometrika, Springer, vol. 75(3), pages 558-578, September.
  2. Park, Sehoon & Jain, Dipak & Krishnamurthi, Lakshman, 1998. "A hierarchical elimination modeling approach for market structure analysis," European Journal of Operational Research, Elsevier, vol. 111(2), pages 328-350, December.
  3. A. Prinzie & D. Van Den Poel, 2005. "Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/292, Ghent University, Faculty of Economics and Business Administration.
  4. Siebert, Ralph Bernd, 2010. "Learning-by-Doing and Cannibalization Effects at Multi-Vintage Firms: Evidence from the Semiconductor Industry," MPRA Paper 24008, University Library of Munich, Germany.
  5. Park, Namgyoo K. & Cho, Dong-Sung, 1997. "The effect of strategic alliance on performance," Journal of Air Transport Management, Elsevier, vol. 3(3), pages 155-164.
  6. Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(1), pages 91-107, February.
  7. Urban, Glen L. & Hulland, John S. & Weinberg, Bruce., 1990. "Modeling, categorization, elimination, and consideration for new product forecasting of consumer durables," Working papers 3206-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  8. Krishnamurthi, Lakshman & Raj, S. P. & Sivakumar, K., 1995. "Unique inter-brand effects of price on brand choice," Journal of Business Research, Elsevier, vol. 34(1), pages 47-56, September.
  9. Kannan, P. K. & Yim, Chi Kin (Bennett), 2001. "An investigation of the impact of promotions on across-submarket competition," Journal of Business Research, Elsevier, vol. 53(3), pages 137-149, September.


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