The Heterogeneous P-Median Problem for Categorization Based Clustering

Simon Blanchard, Daniel Aloise () and Wayne DeSarbo ()

Psychometrika, 2012, vol. 77, issue 4, 762 pages

Abstract: 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. Copyright The Psychometric Society 2012

Keywords: p-median; heterogeneity; sorting task; categorization; clustering; consumer psychology (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s11336-012-9283-3

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