Psychometrica: The heterogeneous p-median problem for categorization based clustering

October 1, 2012

Blanchard, S. J., Aloise, D., & DeSarbo, W. S. (2012). The heterogeneous p-median problem for categorization based clustering. Psychometrika, 77(4), 741-762.

The p-median offers an alternative to centroid-based clustering algorithms for identifying unobserved categories. However, existing p-median formulations typically require data aggregation into a single proximity matrix, resulting in masked respondent heterogeneity. A proposed three-way formulation of the p-median problem explicitly considers heterogeneity by identifying groups of individual respondents that perceive similar category structures. Three proposed heuristics for the heterogeneous p-median (HPM) are developed and then illustrated in a consumer psychology context using a sample of undergraduate students who performed a sorting task of major U.S. retailers, as well as a through Monte Carlo analysis


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