A note on simulating weights restrictions in DEA: an improvement of Thanassoulis and Allen's method |
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| Affiliation: | 1. Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, P.O. Box 1137 Blindern, 0318 Oslo, Norway;2. Biotechnology Centre, University of Oslo, P.O. Box 1125 Blindern, 0317 Oslo, Norway;3. Department of Gastrointestinal Surgery, Oslo University Hospital, P.O. Box 4956 Nydalen, 0424 Oslo, Norway;4. Department of Infectious Diseases, Oslo University Hospital, P.O. Box 4956 Nydalen, 0424 Oslo, Norway;5. K.G. Jebsen Centre for Cancer Immunotherapy, Biotechnology Centre, University of Oslo, P.O. Box 1125 Blindern, 0317 Oslo, Norway;6. K.G. Jebsen Inflammation Research Centre, Centre for Molecular Medicine Norway, University of Oslo, P.O. Box 1137 Blindern, 0318 Oslo, Norway;1. Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, G61 1QH, Scotland, UK;2. Department of Psychosomatic Medicine, Division of Surgery and Clinical Neuroscience, Oslo University Hospital – Rikshospitalet, Oslo, Norway;3. Norwegian School of Veterinary Science, P.O. Box 8146 Dep., 0033 Oslo, Norway;1. Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands;2. Department of Industrial Engineering, Middle East Technical University, 06800 Ankara, Turkey |
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| Abstract: | Data envelopment analysis (DEA) is a nonparametric technique for measuring and assessing the comparative efficiencies of decision making units (DMUs). Weights restrictions are often imposed on these assessments and create many problems in interpretations of results. This paper focuses on one of those and reviews unobserved DMUs method, introduced by Thanassoulis and Allen, to overcome this problem. This paper clarifies the method proposed by them for specifying full set of unobserved DMUs (FSUD) and reduced set of unobserved DMUs (RSUD) as two sets of unobserved DMUs, too. It is indicated that this method is not suitable for some cases and a simple approach is introduced to identify and eliminate redundant unobserved DMUs and specify a new RSUD convenient for all cases. |
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