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Sustainability 2017, 9(4), 661;

Eco-Efficiency Evaluation Considering Environmental Stringency

Korea E-Trade Research Institute, Chung-Ang University, Seoul 06974, Korea
School of Business Administration, College of Business and Economics, Chung-Ang University, Seoul 06974, Korea
Author to whom correspondence should be addressed.
Academic Editors: Gwo-Hshiung Tzeng and Kao-Yi Shen
Received: 22 February 2017 / Revised: 3 April 2017 / Accepted: 13 April 2017 / Published: 21 April 2017
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This paper proposes an extended data envelopment analysis (DEA) model for deriving eco-efficiency. In order to derive eco-efficiency, the proposed model utilizes the concepts of operational efficiency and environmental efficiency. Since DEA can separately measure operational efficiency and environmental efficiency, the treatment for constructing the unified indicator is required to ultimately evaluate eco-efficiency through balancing operational and environmental concerns. To achieve this goal, we define the environmental stringency as the business condition reflecting the degree of enforcing environmental regulations across the firms or particular industries in different countries. The proposed model provides flexibility, as required by the pollution-intensity of industry, in that it allows the decision maker to evaluate DMU’s (decision-making unit) eco-efficiency appropriately depending on the business environment. We present a case of agricultural production systems to help readers understand what eco-efficiency becomes when we vary the stringency conditions. Through the illustrative example, this paper presents the potential application by which different environmental stringencies can successively be incorporated in DEA. View Full-Text
Keywords: eco-efficiency; operational efficiency; environmental efficiency; data envelopment analysis (DEA) eco-efficiency; operational efficiency; environmental efficiency; data envelopment analysis (DEA)

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Lee, P.; Park, Y.-J. Eco-Efficiency Evaluation Considering Environmental Stringency. Sustainability 2017, 9, 661.

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