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.
Original language | English (US) |
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Pages (from-to) | 741-762 |
Number of pages | 22 |
Journal | Psychometrika |
Volume | 77 |
Issue number | 4 |
DOIs | |
State | Published - Oct 1 2012 |
All Science Journal Classification (ASJC) codes
- Psychology(all)
- Applied Mathematics