IDEAS home Printed from
   My bibliography  Save this article

A Probabilistic Model For Testing Hypothesized Hierarchical Market Structures


  • Rajiv Grover

    (Pennsylvania State University)

  • William R. Dillon

    (City University of New York)


In this paper a methodology for hierarchical market structure analysis is derived and illustrated. A probabilistic model is developed which provides a general, flexible framework which can be used to test hypothesized hierarchical market structures. Because the general probabilistic model can be translated in terms of a it can be easily implemented. Among its other benefits, the proposed methodology, utilizing panel data, tracks households over a number of switches, furnishes explicit statistical tests for alternative hypothesized tree structures, as well as individual parameters, and can potentially identify clusters of households who structure the market in similar ways.

Suggested Citation

  • Rajiv Grover & William R. Dillon, 1985. "A Probabilistic Model For Testing Hypothesized Hierarchical Market Structures," Marketing Science, INFORMS, vol. 4(4), pages 312-335.
  • Handle: RePEc:inm:ormksc:v:4:y:1985:i:4:p:312-335

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Sri Duvvuri & Thomas Gruca, 2010. "A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities Across Categories," Psychometrika, Springer;The Psychometric Society, vol. 75(3), pages 558-578, September.
    2. 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;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    3. A. Gürhan Kök & Yi Xu, 2011. "Optimal and Competitive Assortments with Endogenous Pricing Under Hierarchical Consumer Choice Models," Management Science, INFORMS, vol. 57(9), pages 1546-1563, February.
    4. 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.
    5. Andrews, Rick L. & Manrai, Ajay K., 1998. "Feature-based elimination: Model and empirical comparison," European Journal of Operational Research, Elsevier, vol. 111(2), pages 248-267, December.
    6. 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.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:4:y:1985:i:4:p:312-335. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.