IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v5y2017i5p473-488n7.html
   My bibliography  Save this article

An Integrated DEA Model Allowing Decomposition of Eco-Efficiency: A Case Study of China

Author

Listed:
  • Pan Wanbin

    (School of Management, University of Science and Technology of China, Hefei, 230026, China)

  • Huang Lei

    (School of Management, University of Science and Technology of China, Hefei, 230026, China)

  • Zhao Linlin

    (School of Management Science and Engineering, Nanjing Audit University, Nanjing, 211815, China)

Abstract

A common feature of previous studies about the application of data envelopment analysis (DEA) to determine environmental and economic efficiencies is that the two were analyzed in separate models or frameworks. The purpose of this paper is to analyze the economic efficiency and environmental efficiency with a single model. This paper proposes an integrated DEA model, based on a modification of the directional distance function, which allows us to decompose the eco-efficiency (EE) into the economic efficiency (ECE) and environmental efficiency (ENE). The ECE characterizes the ability of gaining economic benefits while the ENE characterizes the ability to control pollutant emissions in production activities. Identification of ECE and ENE can help decision makers of different regions detect what kind of factor (economic inefficiency or environmental inefficiency) is the main source of eco-inefficiency. This can help decision makers more targeted to improve EE. To illustrate the feasibility of our approach, a case study of 30 regions in China is presented. The empirical results show that almost all regions have very high economic efficiencies. The environmental inefficiency is the main source of eco-inefficiency. The differences of environmental efficiencies lead to the differences of eco-efficiencies in the east, central and west areas, while the economic efficiencies do not have significant differences among these areas. The economic efficiencies showed an opposite “V” shape and the environmental efficiencies showed a decreasing trend during the period 2010–2014.

Suggested Citation

  • Pan Wanbin & Huang Lei & Zhao Linlin, 2017. "An Integrated DEA Model Allowing Decomposition of Eco-Efficiency: A Case Study of China," Journal of Systems Science and Information, De Gruyter, vol. 5(5), pages 473-488, October.
  • Handle: RePEc:bpj:jossai:v:5:y:2017:i:5:p:473-488:n:7
    DOI: 10.21078/JSSI-2017-473-16
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2017-473-16
    Download Restriction: no

    File URL: https://libkey.io/10.21078/JSSI-2017-473-16?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Simar, Léopold & Vanhems, Anne, 2012. "Probabilistic characterization of directional distances and their robust versions," Journal of Econometrics, Elsevier, vol. 166(2), pages 342-354.
    2. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    3. Chih-Ching Yang, 2014. "An enhanced DEA model for decomposition of technical efficiency in banking," Annals of Operations Research, Springer, vol. 214(1), pages 167-185, March.
    4. Clara Dismuke & Vania Sena, 2001. "Is there a Trade-Off between Quality and Productivity? The Case of Diagnostic Technologies in Portugal," Annals of Operations Research, Springer, vol. 107(1), pages 101-116, October.
    5. Aparicio, Juan & Pastor, Jesus T. & Zofio, Jose L., 2015. "How to properly decompose economic efficiency using technical and allocative criteria with non-homothetic DEA technologies," European Journal of Operational Research, Elsevier, vol. 240(3), pages 882-891.
    6. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    7. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    8. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    9. Watanabe, Michio & Tanaka, Katsuya, 2007. "Efficiency analysis of Chinese industry: A directional distance function approach," Energy Policy, Elsevier, vol. 35(12), pages 6323-6331, December.
    10. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    11. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    12. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    13. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    14. Guo, Xiao-Dan & Zhu, Lei & Fan, Ying & Xie, Bai-Chen, 2011. "Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA," Energy Policy, Elsevier, vol. 39(5), pages 2352-2360, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    3. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    4. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    5. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    6. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    7. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    8. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    9. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    10. George Halkos & George Papageorgiou, 2016. "Spatial environmental efficiency indicators in regional waste generation: a nonparametric approach," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(1), pages 62-78, January.
    11. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    12. Jianglong Li & Boqiang Lin, 2016. "Green Economy Performance and Green Productivity Growth in China’s Cities: Measures and Policy Implication," Sustainability, MDPI, vol. 8(9), pages 1-21, September.
    13. Jie Wu & Qingyuan Zhu & Pengzhen Yin & Malin Song, 2017. "Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices," Operational Research, Springer, vol. 17(3), pages 715-735, October.
    14. Monastyrenko, Evgenii, 2017. "Eco-efficiency outcomes of mergers and acquisitions in the European electricity industry," Energy Policy, Elsevier, vol. 107(C), pages 258-277.
    15. Zhang, Ning & Wei, Xiao, 2015. "Dynamic total factor carbon emissions performance changes in the Chinese transportation industry," Applied Energy, Elsevier, vol. 146(C), pages 409-420.
    16. Molinos-Senante, María & Hernández-Sancho, Francesc & Mocholí-Arce, Manuel & Sala-Garrido, Ramón, 2014. "Economic and environmental performance of wastewater treatment plants: Potential reductions in greenhouse gases emissions," Resource and Energy Economics, Elsevier, vol. 38(C), pages 125-140.
    17. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    18. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    19. Zhang, Ning & Wang, Bing & Chen, Zhongfei, 2016. "Carbon emissions reductions and technology gaps in the world's factory, 1990–2012," Energy Policy, Elsevier, vol. 91(C), pages 28-37.
    20. Halkos, George & Tzeremes, Nickolaos, 2013. "An additive two-stage DEA approach creating sustainability efficiency indexes," MPRA Paper 44231, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jossai:v:5:y:2017:i:5:p:473-488:n:7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.