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THE USE OF MODERATED REGRESSION IN JOB REDESIGN DECISIONS *
Author(s) -
Peters William S.,
Champoux Joseph E.
Publication year - 1979
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1979.tb00009.x
Subject(s) - regression analysis , job characteristic theory , regression , job analysis , job design , computer science , meta regression , job enrichment , econometrics , job performance , job satisfaction , psychology , statistics , mathematics , social psychology , machine learning , medicine , meta analysis
This paper describes the use of moderated regression in job redesign decisions. The procedures outlined are intended to augment the job redesign strategy described by Hackman and his colleagues. Different regression models based on a theory of job design are shown to lead to different job redesign decisions. Comparisons are also made between the moderated regression procedures and the more commonly used subgroups analysis.