CONSTRUCTING JOB FAMILIES: AN ANALYSIS OF QUANTITATIVE TECHNIQUES USED FOR GROUPING JOBS
- 1 September 1995
- journal article
- Published by Wiley in Personnel Psychology
- Vol. 48 (3) , 563-586
- https://doi.org/10.1111/j.1744-6570.1995.tb01771.x
Abstract
A Monte Carlo study was conducted to examine the performance of several quantitative grouping strategies for the purpose of grouping jobs into job families. Two factors were found to substantially affect the accuracy of these grouping strategies in terms of identifying the correct number of families, and accurately classifying jobs into those families. Through simulation of job analysis data sets designed to reflect various underlying structures among a set of jobs, it was found that techniques based on the commonly used hierarchical cluster analysis model were relatively inaccurate when applied to data containing measurement error or overlap between job families. Alternatively, Q‐type factor analysis and hybrid techniques involving a combination of factor and cluster analysis proved to be viable and robust grouping strategies for job classification research.Keywords
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