Advanced Search
MyIDEAS: Login to save this article or follow this journal

A Probabilistic Model For Testing Hypothesized Hierarchical Market Structures

Contents:

Author Info

  • Rajiv Grover

    (Pennsylvania State University)

  • William R. Dillon

    (City University of New York)

Registered author(s):

    Abstract

    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.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://dx.doi.org/10.1287/mksc.4.4.312
    Download Restriction: no

    Bibliographic Info

    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 4 (1985)
    Issue (Month): 4 ()
    Pages: 312-335

    as in new window
    Handle: RePEc:inm:ormksc:v:4:y:1985:i:4:p:312-335

    Contact details of provider:
    Postal: 7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA
    Phone: +1-443-757-3500
    Fax: 443-757-3515
    Email:
    Web page: http://www.informs.org/
    More information through EDIRC

    Related research

    Keywords: hierarchical market structures; latent class models;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

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

    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. 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.
    4. 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.
    5. 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.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    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).

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.