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Application of the “Defender” Consumer Model

Author

Listed:
  • John R. Hauser

    (Massachusetts Institute of Technology)

  • Steven P. Gaskin

    (Management Decision Systems Inc.)

Abstract

This paper examines the feasibility, practicality, and predictive ability of the consumer model which was proposed by Hauser and Shugan (Hauser, J. R., S. M. Shugan. 1983. Defensive marketing strategies. (4, Fall) 319–360). We report results in two product categories, each representing over $100 million in annual sales. We develop “per dollar” perceptual maps and empirical consumer “taste” distributions. As a first test of the model, we compare the predictive ability of the consumer model in one category to (1) pretest market laboratory measurement models, (2) traditional perceptual mapping procedures, (3) a hybrid model using price as an attribute, and (4) actual market shares in test market cities. In the second product category, we illustrate the application of the quantitative model to augment managerial judgment. Besides developing an empirical version of the “Defender” consumer model, our analyses raise a number of behavioral hypotheses worth further investigation.

Suggested Citation

  • John R. Hauser & Steven P. Gaskin, 1984. "Application of the “Defender” Consumer Model," Marketing Science, INFORMS, vol. 3(4), pages 327-351.
    • Handle: RePEc:inm:ormksc:v:3:y:1984:i:4:p:327-351
    DOI: 10.1287/mksc.3.4.327
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    Cited by:

    1. Cascetta, Ennio & Papola, Andrea, 2009. "Dominance among alternatives in random utility models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 170-179, February.
    2. Kostas Axarloglou, 2008. "Product line extensions: causes and effects," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 9-21.
    3. Wayne DeSarbo & Donald Lehmann & Gregory Carpenter & Indrajit Sinha, 1996. "A stochastic multidimensional unfolding approach for representing phased decision outcomes," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 485-508, September.
    4. Olivier Toubia & Duncan I. Simester & John R. Hauser & Ely Dahan, 2003. "Fast Polyhedral Adaptive Conjoint Estimation," Marketing Science, INFORMS, vol. 22(3), pages 273-303.
    5. Wesson, Tom & De Figueiredo, Joao Neiva, 2001. "The importance of focus to market entrants: A study of microbrewery performance," Journal of Business Venturing, Elsevier, vol. 16(4), pages 377-403, July.
    6. John H. Roberts & Charles J. Nelson & Pamela D. Morrison, 2005. "A Prelaunch Diffusion Model for Evaluating Market Defense Strategies," Marketing Science, INFORMS, vol. 24(1), pages 150-164, August.
    7. Christian Jaag & Helmut Dietl & Urs Trinkner & Oliver Furst, 2012. "Defending Mail Markets Against New Entrants: An Application of the Defender Model," Chapters, in: Michael A. Crew & Paul R. Kleindorfer (ed.), Multi-Modal Competition and the Future of Mail, chapter 17, Edward Elgar Publishing.
    8. Barry L. Bayus & William P. Putsis, Jr., 1999. "Product Proliferation: An Empirical Analysis of Product Line Determinants and Market Outcomes," Marketing Science, INFORMS, vol. 18(2), pages 137-153.
    9. Gallego, Guillermo & Li, Anran & Truong, Van-Anh & Wang, Xinshang, 2020. "Approximation algorithms for product framing and pricing," LSE Research Online Documents on Economics 101983, London School of Economics and Political Science, LSE Library.
    10. Suman Basuroy & Dung Nguyen, 1998. "Multinomial Logit Market Share Models: Equilibrium Characteristics and Strategic Implications," Management Science, INFORMS, vol. 44(10), pages 1396-1408, October.
    11. Guillermo Gallego & Anran Li & Van-Anh Truong & Xinshang Wang, 2020. "Approximation Algorithms for Product Framing and Pricing," Operations Research, INFORMS, vol. 68(1), pages 134-160, January.

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