Two-level DEA approaches in research evaluation |
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Authors: | Wei Meng Daqun Zhang Li Qi Wenbin Liu |
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Institution: | aInstitute of Policy and Management, Chinese Academy of Sciences, 100080 Beijing, China;bKent Business School, University of Kent, CT2 7PE Canterbury, Kent, UK |
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Abstract: | It is well known that the discrimination power of data envelopment analysis (DEA) models will be much weakened if too many input or output indicators are used. It is a dilemma if decision makers wish to select comprehensive indicators, which often have some hierarchical structures, to present a relatively holistic evaluation using DEA. In this paper we show that it is possible to develop DEA models that utilize hierarchical structures of input–output data so that they are able to handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in the Chinese Academy of Sciences using the DEA models. |
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Keywords: | Hierarchical structures Discrimination power DEA Research evaluation |
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