How to better identify the true managerial performance: State of the art using DEA

How to better identify the true managerial performance: State of the art using DEA

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Article ID: iaor20091455
Country: United Kingdom
Volume: 36
Issue: 2
Start Page Number: 317
End Page Number: 324
Publication Date: Apr 2008
Journal: OMEGA
Authors: ,
Keywords: management, performance, programming: linear
Abstract:

Our motivation is to detail a potential improvement on the three-stage analysis published by Fried et al. that can distinguish true performers from those that may be advantaged by favourable environments or measurement errors. The method starts with data envelopment analysis (DEA), and continues with stochastic frontier analysis to explain the variation in organisational performance in terms of the operating environment, statistical noise and managerial efficiency. It concludes with DEA again using adjusted data to reveal a measure of performance based on management efficiency only. Our proposed contributions include (i) a comprehensive approach where total input and output slacks are identified simultaneously for non-radial inefficiencies before levelling the playing field, (ii) identifying percent adjustments attributable to the environment and statistical noise, and (iii) using a fully units-invariant DEA model.

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