Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups |
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| Authors: | Wayne Desarbo Kamel Jedidi Karel Cool Dan Schendel |
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| Institution: | (1) Marketing Department, University of Michigan, School of Business Administration, 48109-1234 Ann Arbor, MI, USA;(2) Statistics Department, University of Michigan, School of Business Administration, 48109-1234 Ann Arbor, MI, USA;(3) Columbia University, Columbia, USA;(4) Purdue University, USA |
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| 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.INSEAD |
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| Keywords: | Marketing Strategy Multidimensional Scaling Cluster Analysis Strategic Groups |
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