Estimating Multiple Consumer Segment Ideal Points from Context-Dependent Survey Data

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