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MES-DEA modelling for analysing anti-industrial pollution efficiency and its application in Anhui province of China

Author

Listed:
  • Liang Liang
  • Desheng Wu
  • Zhongsheng Hua

Abstract

This paper chooses a Data Envelopment Analysis (DEA) model for different areas to identify the difference in solving the industrial pollution problem by comparing their levels of efficiency. Generally, the industrial pollution problem calls for within-area treatments, although these affect areas beyond their limits. Following this fact, a Maximal Efficiency Sum (MES) DEA Model is used to estimate the anti-industrial pollution efficiency of different cities in Anhui province of China.

Suggested Citation

  • Liang Liang & Desheng Wu & Zhongsheng Hua, 2004. "MES-DEA modelling for analysing anti-industrial pollution efficiency and its application in Anhui province of China," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 22(2/3/4), pages 88-98.
  • Handle: RePEc:ids:ijgeni:v:22:y:2004:i:2/3/4:p:88-98
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    1. repec:spr:nathaz:v:90:y:2018:i:1:d:10.1007_s11069-017-3105-y is not listed on IDEAS
    2. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "DEA environmental assessment in time horizon: Radial approach for Malmquist index measurement on petroleum companies," Energy Economics, Elsevier, vol. 51(C), pages 329-345.
    3. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1742-1753, December.
    4. Sueyoshi, Toshiyuki & Goto, Mika & Sugiyama, Manabu, 2013. "DEA window analysis for environmental assessment in a dynamic time shift: Performance assessment of U.S. coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 845-857.
    5. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "DEA radial measurement for environmental assessment: A comparative study between Japanese chemical and pharmaceutical firms," Applied Energy, Elsevier, vol. 115(C), pages 502-513.
    6. Sanz-Díaz, María Teresa & Velasco-Morente, Francisco & Yñiguez, Rocío & Díaz-Calleja, Emilio, 2017. "An analysis of Spain's global and environmental efficiency from a European Union perspective," Energy Policy, Elsevier, vol. 104(C), pages 183-193.
    7. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    8. repec:gam:jsusta:v:9:y:2017:i:4:p:661-:d:96486 is not listed on IDEAS
    9. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations," Energy Economics, Elsevier, vol. 40(C), pages 370-382.
    10. Wei, Chu & Ni, Jinlan & Du, Limin, 2012. "Regional allocation of carbon dioxide abatement in China," China Economic Review, Elsevier, vol. 23(3), pages 552-565.
    11. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Investment strategy for sustainable society by development of regional economies and prevention of industrial pollutions in Japanese manufacturing sectors," Energy Economics, Elsevier, vol. 42(C), pages 299-312.
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "Returns to scale vs. damages to scale in data envelopment analysis: An impact of U.S. clean air act on coal-fired power plants," Omega, Elsevier, vol. 41(2), pages 164-175.

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