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

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

Research output: Contribution to journalArticle

11 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)185-204
Number of pages20
JournalApplied Stochastic Models and Data Analysis
Issue number3
Publication statusPublished - Sep 1988


All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Management of Technology and Innovation

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