Nonmetric Unfolding of Marketing Data: Degeneracy and Stability

Michel van de Velden, Alain de Beuckelaer, Patrick Groenen () and Frank Busing

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

Abstract: Nonmetric unfolding is a powerful (nonparametric) analytical tool generating a preference-based joint display of subjects (e.g., customers) and objects (e.g., brands or products). Systematic patterns in customers’ preferences can be directly inferred from this display, and may provide valuable input for making important marketing decisions such as deciding what new product to launch. Unfortunately, nonmetric unfolding frequently produces degenerate unfolding solutions (i.e., unfolding solutions showing close-to-perfect model fit irrespective of the data analyzed). As a degenerated display shows ill-positioned customers and brands/products, the chance of making an incorrect marketing decision (e.g., launching the wrong product) is very high. To solve this problem adequately, we combine bootstrapping with penalized nonmetric unfolding (Prefscal) to obtain an accurate, nondegenerate and stable unfolding solution.

Keywords: bootstrap analysis; customer preference modeling; nonmetric multidimensional unfolding; perceptual mapping (search for similar items in EconPapers)
JEL-codes: C44 M M31 (search for similar items in EconPapers)
Date: 2011-03-11
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Citations: View citations in EconPapers (1)

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