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Dealing with Interval DEA Based on Error Propagation and Entropy: A Case Study of Energy Efficiency of Regions in China Considering Environmental Factors
Journal of Systems Science and Information
AbstractThe conventional data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) consuming multiple inputs to produce multiple outputs under the assumption that all the data are exact. In the real world, however, it is possible to obtain interval data rather than exact data because of various limitations, such as statistical errors and incomplete information, et al. To overcome those limitations, researchers have proposed kinds of approaches dealing withdoi:10.1515/jssi-2015-0538 fatcat:3fygh6ccibhnxpafq5ezr55zsa