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Industrial Efficiency Evaluation in China: A Nonparametric Production-Frontier Approach

Author

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  • Linlin Zhao

    (School of Business, Nanjing Audit University, Yushan West Road 86, Nanjing 211815, China)

  • Lin Zhang

    (School of Business, Nanjing Audit University, Yushan West Road 86, Nanjing 211815, China)

  • Yong Zha

    (School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026, China)

Abstract

An industrial system has positive and negative strategies to adapt to environmental regulations, which can be defined as natural disposability and managerial disposability. Meanwhile, the operational process of an industrial system can be divided into regular production activities and pollutant control activities. Within this, industrial system’s technical efficiency (TE) can be decomposed into economic efficiency (ECE) and environmental efficiency (ENE). On the basis of natural disposability and managerial disposability, this paper proposes static and dynamic data envelopment analysis (DEA) models to evaluate the efficiencies of industrial systems. Based on the proposed approach, TE, ECE, ENE, and Malmqusit productivity index (MPI) values were obtained simultaneously. The MPI values were further separated into the effects of static efficiency change and technical change. The proposed method was applied to assess the technical efficiencies of Chinese regional industrial systems between 2011 and 2015. Key findings are that (1) the low ENE is the main source of technical inefficiency; (2) the average static TE and ENE under natural disposability are both lower than those under managerial disposability; (3) the static efficiency change and technical change of TE are similar to those of ENE; and (4) the technical change has a significant impact on the changes in TE.

Suggested Citation

  • Linlin Zhao & Lin Zhang & Yong Zha, 2019. "Industrial Efficiency Evaluation in China: A Nonparametric Production-Frontier Approach," Sustainability, MDPI, vol. 11(18), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:5019-:d:267066
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    as
    1. Wu, Jie & Zhu, Qingyuan & Ji, Xiang & Chu, Junfei & Liang, Liang, 2016. "Two-stage network processes with shared resources and resources recovered from undesirable outputs," European Journal of Operational Research, Elsevier, vol. 251(1), pages 182-197.
    2. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    3. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    4. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    5. Wang, Derek & Li, Shanling & Sueyoshi, Toshiyuki, 2014. "DEA environmental assessment on U.S. Industrial sectors: Investment for improvement in operational and environmental performance to attain corporate sustainability," Energy Economics, Elsevier, vol. 45(C), pages 254-267.
    6. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    7. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.
    8. 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.
    9. Zhang, Ning & Wang, Bing & Liu, Zhu, 2016. "Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors," Energy, Elsevier, vol. 99(C), pages 10-19.
    10. 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.
    11. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry," European Journal of Operational Research, Elsevier, vol. 216(3), pages 668-678.
    12. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    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. Ronggang Zhang & Ching-Cheng Lu & Jen-Hui Lee & Ying Feng & Yung-Ho Chiu, 2019. "Dynamic Environmental Efficiency Assessment of Industrial Water Pollution," Sustainability, MDPI, vol. 11(11), pages 1-12, May.
    15. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    16. George E. Halkos & Nickolaos G. Tzeremes & Stavros A. Kourtzidis, 2016. "Measuring Sustainability Efficiency Using a Two-Stage Data Envelopment Analysis Approach," Journal of Industrial Ecology, Yale University, vol. 20(5), pages 1159-1175, October.
    17. Yingnan Liu & Ke Wang, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA-based decomposition analysis," CEEP-BIT Working Papers 83, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    18. Makridou, Georgia & Andriosopoulos, Kostas & Doumpos, Michael & Zopounidis, Constantin, 2016. "Measuring the efficiency of energy-intensive industries across European countries," Energy Policy, Elsevier, vol. 88(C), pages 573-583.
    19. Goto, Mika & Otsuka, Akihiro & Sueyoshi, Toshiyuki, 2014. "DEA (Data Envelopment Analysis) assessment of operational and environmental efficiencies on Japanese regional industries," Energy, Elsevier, vol. 66(C), pages 535-549.
    20. Arcos-Vargas, A. & Núñez-Hernández, F. & Villa-Caro, Gabriel, 2017. "A DEA analysis of electricity distribution in Spain: An industrial policy recommendation," Energy Policy, Elsevier, vol. 102(C), pages 583-592.
    21. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    22. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    23. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    24. 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.
    25. Yongjun Li & Xiao Shi & Ali Emrouznejad & Liang Liang, 2018. "Environmental performance evaluation of Chinese industrial systems: a network SBM approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(6), pages 825-839, June.
    26. Kaoru Tone, 2011. "Slacks-Based Measure of Efficiency," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 195-209, Springer.
    27. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    28. Emrouznejad, Ali & Yang, Guo-liang, 2016. "CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index," Energy Policy, Elsevier, vol. 96(C), pages 397-410.
    29. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    30. Kao, Chiang & Hwang, Shiuh-Nan, 2014. "Multi-period efficiency and Malmquist productivity index in two-stage production systems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 512-521.
    31. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
    32. Jie Wu & Beibei Xiong & Qingxian An & Jiasen Sun & Huaqing Wu, 2017. "Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs," Annals of Operations Research, Springer, vol. 255(1), pages 257-276, August.
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    2. Manli Cheng & Zhen Shao & Changhui Yang & Xiaoan Tang, 2019. "Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries," Sustainability, MDPI, vol. 11(22), pages 1-20, November.

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