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Sustainability 2017, 9(12), 2080; doi:10.3390/su9122080

Analysis of Interval Data Envelopment Efficiency Model Considering Different Distribution Characteristics—Based on Environmental Performance Evaluation of the Manufacturing Industry

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Economics and Management, China Institute for Manufacture Developing, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Received: 7 October 2017 / Revised: 31 October 2017 / Accepted: 6 November 2017 / Published: 27 November 2017
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Abstract

This study utilizes the Data Envelopment Efficiency (DEA) model to assess input–output efficiency from two perspectives. First, not considering the distribution of interval data, we introduce an adjusted parameter to transform interval data to determination data. Second, by contrast, we take into account the distribution characteristics of interval data and test the DEA model with interval data based on linear uniform distribution and normal distribution with uncertainty. Based on the normal distribution DEA evaluation model, this paper aims to evaluate the input–output performance of the manufacturing industry with the constraint of environmental pollution in the Yangtze River Delta (YRD) region, China. Research has shown that the optimal solution of the normal distribution model is better than that of linear distribution. Therefore, it is imperative to adopt an appropriate method to evaluate the energy and environmental efficiency of this region. View Full-Text
Keywords: energy efficiency; interval DEA model; linear uniform distribution energy efficiency; interval DEA model; linear uniform distribution
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Gong, Z.; Chen, X. Analysis of Interval Data Envelopment Efficiency Model Considering Different Distribution Characteristics—Based on Environmental Performance Evaluation of the Manufacturing Industry. Sustainability 2017, 9, 2080.

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