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

Wayne Desarbo, Kamel Jedidi, Karel Cool, Dan Schendel

Research output: Contribution to journalArticle

33 Citations (Scopus)

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

Fingerprint

Cluster analysis
Methodology
Maximum likelihood
Strategic groups
EM algorithm
Parameter estimation
Normal distribution
Marketing strategy
Industry

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Economics and Econometrics
  • Marketing

Cite this

Desarbo, Wayne ; Jedidi, Kamel ; Cool, Karel ; Schendel, Dan. / Simultaneous multidimensional unfolding and cluster analysis : An investigation of strategic groups. In: Marketing Letters. 1991 ; Vol. 2, No. 2. pp. 129-146.
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Simultaneous multidimensional unfolding and cluster analysis : An investigation of strategic groups. / Desarbo, Wayne; Jedidi, Kamel; Cool, Karel; Schendel, Dan.

In: Marketing Letters, Vol. 2, No. 2, 01.04.1991, p. 129-146.

Research output: Contribution to journalArticle

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