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A synthesized data envelopment analysis model and its application in resource efficiency evaluation and dynamic trend analysis

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  • Sun Meng
  • Wei Zhou
  • Jin Chen
  • Cheng Zhang

Abstract

Based on the total factor productivity and the resource efficiency, this paper proposes a synthesized data envelopment analysis (DEA) model by using the DEA approach and the Malmquist index. Furthermore, this model is applied to a comprehensive empirical study of the resource efficiency evaluation in China from 2013 to 2015. By introducing some desirable and undesirable factors, we calculate and analyze the whole resource efficiency, the input redundancy ratio, and the output inefficiency ratio of China from 2013 to 2015 based on the synthesized DEA model. Then, we analyze the dynamic trends of the resource efficiency in 31 provinces of China during these three years by applying the corresponding Malmquist index. After that, some interesting conclusions are derived, which are useful for the government. At last, some practical suggestions about improving the resource efficiency of these provinces are provided.

Suggested Citation

  • Sun Meng & Wei Zhou & Jin Chen & Cheng Zhang, 2018. "A synthesized data envelopment analysis model and its application in resource efficiency evaluation and dynamic trend analysis," Energy & Environment, , vol. 29(2), pages 260-280, March.
  • Handle: RePEc:sae:engenv:v:29:y:2018:i:2:p:260-280
    DOI: 10.1177/0958305X17745687
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    References listed on IDEAS

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    1. Nassiri, Seyed Mehdi & Singh, Surendra, 2009. "Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique," Applied Energy, Elsevier, vol. 86(7-8), pages 1320-1325, July.
    2. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    3. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    4. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Bian, Yiwen & Yang, Feng, 2010. "Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy," Energy Policy, Elsevier, vol. 38(4), pages 1909-1917, April.
    7. Zhou, Yan & Xing, Xinpeng & Fang, Kuangnan & Liang, Dapeng & Xu, Chunlin, 2013. "Environmental efficiency analysis of power industry in China based on an entropy SBM model," Energy Policy, Elsevier, vol. 57(C), pages 68-75.
    8. W. Cooper & Shanling Li & L. Seiford & Kaoru Tone & R. Thrall & J. Zhu, 2001. "Sensitivity and Stability Analysis in DEA: Some Recent Developments," Journal of Productivity Analysis, Springer, vol. 15(3), pages 217-246, May.
    9. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    10. Hedman, Åsa & Sepponen, Mari & Virtanen, Mikko, 2014. "Energy efficiency rating of districts, case Finland," Energy Policy, Elsevier, vol. 65(C), pages 408-418.
    11. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    12. Azadeh, A. & Ghaderi, S.F. & Omrani, H. & Eivazy, H., 2009. "An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units," Energy Policy, Elsevier, vol. 37(7), pages 2605-2618, July.
    13. 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.
    14. 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.
    15. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
    16. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    17. Barros, C.P. & Emrouznejad, Ali, 2016. "Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banksAuthor-Name: Wanke, Peter," European Journal of Operational Research, Elsevier, vol. 249(1), pages 378-389.
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