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Data Envelopment Analysis for Measuring Environmental Performance

In: Handbook of Operations Analytics Using Data Envelopment Analysis

Author

Listed:
  • Peng Zhou

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics)

  • Kim Leng Poh

    (National University of Singapore)

  • Beng Wah Ang

    (National University of Singapore)

Abstract

Environmental performance measurement provides an analytical foundation for environmental policy analysis and decision making. As a popular performance evaluation tool, Data Envelopment Analysis (DEA) has been applied to construct environmental performance index in different ways, where modeling undesirable outputs and the choice/construction of efficiency measures are the main steps. This chapter gives an introductory text on applications of DEA to environmental performance measurement by describing the formulation of environmental DEA technologies as well as radial and non-radial DEA models for constructing pure environmental efficiency/productivity index. A case study on measuring the environmental performance of OECD countries is presented. Future directions of DEA applications to environmental modeling are discussed with reference to several recent developments in this area.

Suggested Citation

  • Peng Zhou & Kim Leng Poh & Beng Wah Ang, 2016. "Data Envelopment Analysis for Measuring Environmental Performance," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 31-49, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7705-2_2
    DOI: 10.1007/978-1-4899-7705-2_2
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    Citations

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    Cited by:

    1. Christina Bampatsou & George Halkos, 2021. "Non-Parametric Computational Measures for the Analysis of Resource Productivity," Energies, MDPI, vol. 14(11), pages 1-14, May.
    2. Patrick Gasser & Marco Cinelli & Anna Labijak & Matteo Spada & Peter Burgherr & Miłosz Kadziński & Božidar Stojadinović, 2020. "Quantifying Electricity Supply Resilience of Countries with Robust Efficiency Analysis," Energies, MDPI, vol. 13(7), pages 1-35, March.
    3. Adenuga, A. & Davis, J. & Hutchinson, G. & Donnellan, T. & Patton, M., 2018. "Valuing Agricultural Externalities: Nitrogen Surplus in the Dairy Sector on the Island of Ireland," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277434, International Association of Agricultural Economists.
    4. Wasim Sultan & José Crispim, 2016. "Evaluating the Productive Efficiency of Jordanian Public Hospitals," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(1), pages 1-68, December.
    5. Adewale Henry Adenuga & John Davis & George Hutchinson & Trevor Donnellan & Myles Patton, 2019. "Environmental Efficiency and Pollution Costs of Nitrogen Surplus in Dairy Farms: A Parametric Hyperbolic Technology Distance Function Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1273-1298, November.
    6. Izhar Hussain Shah & Hung‐Suck Park, 2021. "Chronological change of resource metabolism and decarbonization patterns in Pakistan: Perspectives from a typical developing country," Journal of Industrial Ecology, Yale University, vol. 25(1), pages 144-161, February.
    7. Payam Rashidi & Masoud Homayounifar & Taghi Ebrahimi Salari & Modjtaba Rouhani, 2017. "Measuring Economic and Environmental Performance of Energy Resources in ISIC codes: Evidence from Iran’s Industry Sector," Modern Applied Science, Canadian Center of Science and Education, vol. 11(12), pages 109-109, December.
    8. Jianting Lin & Changxin Xu, 2017. "The Impact of Environmental Regulation on Total Factor Energy Efficiency: A Cross-Region Analysis in China," Energies, MDPI, vol. 10(10), pages 1-17, October.
    9. Kuhn, Lena & Balezentis, Tomas & Hou, Lingling & Wang, Dan, 2020. "Technical and environmental efficiency of livestock farms in China: A slacks-based DEA approach," China Economic Review, Elsevier, vol. 62(C).
    10. Zhao, Linlin & Zha, Yong & Zhuang, Yuliang & Liang, Liang, 2019. "Data envelopment analysis for sustainability evaluation in China: Tackling the economic, environmental, and social dimensions," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1083-1095.
    11. Seyed Ali Rakhshan, 2017. "Efficiency ranking of decision making units in data envelopment analysis by using TOPSIS-DEA method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 906-918, August.

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