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.