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A new stochastic ultrametric tree unfolding methodology for assessing competitive market structure and deriving market segments

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  • W. S. Desarbo
  • G. de Soete
  • J. D. Carroll
  • V. Ramaswamy

Abstract

We present a new methodology for simultaneously assessing competitive market structure and deriving market segments. A hierarchical or ultrametric tree representation is estimated in a maximum likelihood framework from collected paired‐comparison choice data. The derived tree portrays both brands and consumers/households/segments as terminal nodes, where the ‘closer’ a brand is to a particular consumer/household/segment in the tree, the higher the predicted probability of that consumer/household/segment choosing that particular brand. This paper initially presents an introduction to the problem of market structure assessment. We review the extensive marketing literature on market structure and survey several competing methodologies. The proposed stochastic ultrametric tree unfolding methodology is technically described and several program options are indicated. An illustration of the proposed methodology is presented with respect to paired comparison choice data collected from a convenience sample involving the over‐the‐counter analgesics market. Finally, several areas for future research are identified.

Suggested Citation

  • W. S. Desarbo & G. de Soete & J. D. Carroll & V. Ramaswamy, 1988. "A new stochastic ultrametric tree unfolding methodology for assessing competitive market structure and deriving market segments," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 4(3), pages 185-204, September.
    • Handle: RePEc:wly:apsmda:v:4:y:1988:i:3:p:185-204
    DOI: 10.1002/asm.3150040306
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    Cited by:

    1. Junghyun Park & Minki Kim & Pradeep K Chintagunta, 2022. "Mapping Consumers’ Context-Dependent Consumption Preferences: A Multidimensional Unfolding Approach [An Empirical Comparison of Logit Choice Models with Discrete versus Continuous Representations o," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 202-228.
    2. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    3. Wayne DeSarbo & Kamel Jedidi & Joel Steckel, 1991. "A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 279-307, June.
    4. Martin Young & Wayne DeSarbo, 1995. "A parametric procedure for ultrametric tree estimation from conditional rank order proximity data," Psychometrika, Springer;The Psychometric Society, vol. 60(1), pages 47-75, March.

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