A Clusterwise Bilinear Multidimensional Scaling Methodology for Simultaneous Segmentation and Positioning Analyses

Wayne S. Desarbo, Rajdeep Grewal, Crystal J. Scott

Journal of Marketing Research · 2008 · Volume 45 · Issue 3

Abstract

The segmentation–targeting–positioning conceptual framework has been the traditional foundation and genesis of marketing strategy formulation. The authors propose a general clusterwise bilinear spatial model that simultaneously estimates market segments, their composition, a brand space, and preference/utility vectors per market segment; that is, the model performs segmentation and positioning simultaneously. After a review of related methodological research in the marketing, psychometrics, and classification literature streams, the authors present the technical details of the proposed two-way clusterwise bilinear spatial model. They develop an efficient alternating least squares procedure that estimates conditional globally optimum estimates of the model parameters within each iteration through analytic closed-form expressions. The authors present various model options. They provide a conceptual and empirical comparison with latent-class multidimensional scaling. They use an illustration of the new bilinear multidimensional scaling methodology with an actual commercial study sponsored by a large U.S. automotive manufacturer to examine buying/consideration intentions for small sport-utility vehicles. The authors conclude by summarizing the contributions of this research, discussing the marketing implications for managers, and providing several directions for further research.

Keywords

market segmentation, positioning, clusterwise analyses, bilinear spatial models, sport-utility vehicles

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