The Heterogeneous P-Median for Categorization Based Clustering
Simon J. Blanchard
Georgetown University - Robert Emmett McDonough School of Business
Universidade Federal do Rio Grande do Norte
Wayne S. DeSarbo
Pennsylvania State University
March 29, 2012
Georgetown McDonough School of Business Research Paper No 2012-11
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 through a Monte Carlo analysis.
Number of Pages in PDF File: 48
Keywords: p-median, heterogeneity, sorting task, categorization, clustering, consumer psychology
JEL Classification: C6, C60, M31, M30Accepted Paper Series
Date posted: March 31, 2012 ; Last revised: November 1, 2012
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