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Common benchmarking and ranking of units with DEA
Institution:1. Department of Mathematics, College of Sciences, Shiraz University, Shiraz 71454, Iran;2. Xavier Institute of Management, Xavier University, Bhubaneswar 751 013, India;3. Department of Accounting and Finance, The University of Auckland, Auckland, New Zealand;4. Department of Mathematics, Semnan Branch, Islamic Azad University, Semnan, Iran;1. Department of Systems Engineering, Faculty of Economics, VŠB-Technical University of Ostrava, Sokolska třída 33, 702 00, Ostrava, Czech Republic;2. Department of Mathematics, Islamic Azad University, Sirjan Branch, Sirjan, Iran;3. Department of Strategic Management and Marketing, Leicester Business School, De Montfort University, Hugh Aston Building, The Gateway, LE1 9BH Leicester, UK\n;1. Department of Computer''s Sciences, Technical School of Computer Engineering, Rey Juan Carlos University, Madrid, Spain;2. University Institute of Health Care Evaluation, School of Medicine, Universidad Complutense de Madrid, Madrid 28040, Spain;3. Department of Statistics and Operations Research, School of Statistics Studies, Universidad Complutense de Madrid, Madrid 28040, Spain
Abstract:This paper develops a common framework for benchmarking and ranking units with DEA. In many DEA applications, decision making units (DMUs) experience similar circumstances, so benchmarking analyses in those situations should identify common best practices in their management plans. We propose a DEA-based approach for the benchmarking to be used when there is no need (nor wish) to allow for individual circumstances of the DMUs. This approach identifies a common best practice frontier as the facet of the DEA efficient frontier spanned by the technically efficient DMUs in a common reference group. The common reference group is selected as that which provides the closest targets. A model is developed which allows us to deal not only with the setting of targets but also with the measurement of efficiency, because we can define efficiency scores of the DMUs by using the common set of weights (CSW) it provides. Since these weights are common to all the DMUs, the resulting efficiency scores can be used to derive a ranking of units. We discuss the existence of alternative optimal solutions for the CSW and find the range of possible rankings for each DMU which would result from considering all these alternate optima. These ranking ranges allow us to gain insight into the robustness of the rankings.
Keywords:Benchmarking  Target setting  Efficiency measurement  Ranking  DEA
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