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

Our motivation is to detail a potential improvement on the three-stage analysis published by Fried et al. [Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis 2002;17:157–74] that can distinguish true performers from those that ma...

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Bibliographic Details
Published in:Omega (Oxford) 2008-04, Vol.36 (2), p.317-324
Main Authors: Avkiran, Necmi K., Rowlands, Terry
Format: Article
Language:English
Subjects:
Applied sciences
Data envelopment analysis
DEA
Efficiency
Evaluation
Exact sciences and technology
Firm modelling
Inventory control, production control. Distribution
Management
Management DEA LP Efficiency
Management techniques
Managers
Mathematics
Nonparametric inference
Operational research and scientific management
Operational research. Management science
Probability and statistics
Psychological aspects
Sciences and techniques of general use
Statistics
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Summary:Our motivation is to detail a potential improvement on the three-stage analysis published by Fried et al. [Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis 2002;17:157–74] 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.
ISSN:0305-0483
1873-5274
DOI:10.1016/j.omega.2006.01.002