The Heterogeneous P-Median Problem for Categorization Based Clustering

Autor/inn/en	Blanchard, Simon J.; Aloise, Daniel; DeSarbo, Wayne S.
Titel	The Heterogeneous P-Median Problem for Categorization Based Clustering
Quelle	In: Psychometrika, 77 (2012) 4, S.741-762 (22 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-012-9283-3
Schlagwörter	Matrices; Undergraduate Students; Heuristics; Psychology; Classification; Psychometrics; Consumer Economics; Monte Carlo Methods; Mathematics; Data Analysis + Suchen Sie Ihr Suchwort? Matrizenrechnung; Heuristik; Psychologie; Classification system; Klassifikation; Klassifikationssystem; Psychometry; Psychometrie; Konsumökonomie; Monte-Carlo-Methode; Mathematik; Auswertung
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. (Contains 5 tables, 3 figures, and 4 footnotes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10