Environmental Efficiency Evaluation of Electricity Industry in China-An Application of Two-Stage Network DEA with Shared Resources

碩士 === 國立雲林科技大學 === 財務金融系 === 106 === In recent years, people have paid more and more attention to the issue of air pollution. Under the rapid of industry development, China has caused environmental pollution hazards. Therefore, how to realize the power growth and to consider the environmental prote...

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Bibliographic Details
Main Authors: HO, PEI-CHEN, 何珮甄
Other Authors: CHENG, CHENG-PING
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/b39ab4
Description
Summary:碩士 === 國立雲林科技大學 === 財務金融系 === 106 === In recent years, people have paid more and more attention to the issue of air pollution. Under the rapid of industry development, China has caused environmental pollution hazards. Therefore, how to realize the power growth and to consider the environmental protection is an issue that deserves our attention and discussion. This study discusses the environmental efficiency of the electricity industry of 31 provinces in China between 2011 and 2015. Based on Tone & Tsutsui's (2007) Network Data Envelopment Analysis (NDEA), this paper derives a shared two-stage NDEA model for the efficiency of the power industry environment. The power system is divided into the generation process and the power distribution process, and adding the environmental pollution caused by the electric power industry to the model. In addition to the overall efficiency under the two-stage NDEA, this study also analyzes the power generation efficiency and distribution efficiency. The empirical results of this paper show that: (1) The top three provinces with the highest efficiency are Guangdong, Shandong and Jiangsu. While the top three lowest efficient provinces are Chongqing, Qinghai, and Hainan; (2) In the most provinces as overall electricity, the industrial environment is inefficient, which is related to the low value of distribution efficiency. Finally, by comparing the results of the BCC model and the Bad Output model (without considering the intermediate process), it is found that the two-stage DEA model with shared of this study is more reliable and accurate.