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MEASURING SUBUNIT EFFECTIVENESS
Author(s) -
Hitt Michael A.,
Ireland R. Duane,
Keats Barbara W.,
Vianna Antonio
Publication year - 1983
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.1540-5915.1983.tb00171.x
Subject(s) - predictive power , similarity (geometry) , multivariate statistics , computer science , econometrics , operations research , artificial intelligence , mathematics , machine learning , philosophy , epistemology , image (mathematics)
The literature suggests that a multivariate approach to the measurement of effectiveness is preferred. The present study uses a policy‐capturing methodology to examine effectiveness criteria and their importance weightings for various subunits in a manufacturing organization. Effectiveness criteria and their weightings were found to vary across individual subunits. The models developed for major groupings of subunits were found to have reasonable predictive power. Finally, the predictive power of these general models varied with the degree of goal similarity among the subunits in the grouping. Useful applications of the results for managerial decisions are explored.