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Estimating multiple consumer segment ideal points from context-dependent survey data
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DOI：10.1086/529534.png)
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Abstract
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Previous research in marketing and consumer research has shown that consumers/households often possess multiple ideal points in a given product/service category. In such cases, traditional segmentation and positioning models that estimate a single ideal point per individual/segment may render an inaccurate portrayal of the true underlying utility functions of such consumers/segments and the resulting market structure. We propose a new clusterwise multiple-ideal-point spatial methodology that estimates multiple ideal points at the market segment level while simultaneously determining the market segments' composition of consumers, as well as the corresponding joint space.
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