Journal
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
Volume 36, Issue 6, Pages 950-957Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2007.12.005
Keywords
hierarchical structures; discrimination power; DEA; research evaluation
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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. (C) 2008 Elsevier Ltd. All rights reserved.
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