Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups

Wayne Desarbo, Kamel Jedidi, Karel Cool, Dan Schendel

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

This paper develops a maximum likelihood based methodology for simultaneously performing multidimensional unfolding and cluster analysis on two-way dominance or profile data. This new procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of stimulus coordinates and K ideal points, one for each cluster or group, in a T-dimensional space. The conditional mixture, maximum likelihood methodology is introduced together with an E-M algorithm utilized for parameter estimation. A marketing strategy application is provided with an analysis of PIMS data for a set of firms drawn from the same competitive industry to determine strategic groups, while simultaneously depicting strategy-performance relationships.

Original languageEnglish (US)
Pages (from-to)129-146
Number of pages18
JournalMarketing Letters
Volume2
Issue number2
DOIs
StatePublished - Apr 1 1991

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Economics and Econometrics
  • Marketing

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