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Fujian’s Industrial Eco-Efficiency: Evaluation Based on SBM and the Empirical Analysis of lnfluencing Factors

Author

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  • Xiaoqing Wang

    (School of Economics and Management, Fuzhou University, Fuzhou 350000, China)

  • Qiuming Wu

    (School of Economics and Management, Fuzhou University, Fuzhou 350000, China)

  • Salman Majeed

    (School of Economics and Management, Fuzhou University, Fuzhou 350000, China)

  • Donghao Sun

    (School of Economics and Management, Fuzhou University, Fuzhou 350000, China)

Abstract

The coordinated development of industrialization and its ecological environment are vital antecedents to sustainable development in China. However, along with the accelerating development of industrialization in China, the contradiction between industrial development and environment preservation has turned out to be increasingly evident and inevitable. Eco-efficiency can be seen either as an indicator of environmental performance, or as a business strategy for sustainable development. Hence, industrial eco-efficiency promotion is the key factor for green industrial development. This study selects indicators relevant to resources, economy, and the environment of industrial development, and the indicators can well reflect the characteristics of industrial eco-efficiency. The SBM (Slacks-Based Measure) model overcomes the limitations of a radial model and directly accounts for input and output slacks in the efficiency measurements, with the advantage of capturing the entire aspect of inefficiency. This study evaluates the industrial eco-efficiency of nine cities in Fujian province during the period of 2006–2016, based on undesired output SBM (Slacks-Based Measure) model and also uses a Tobit regression model to analyze the influencing factors. The results show that there is a positive correlation among the economic development level, opening level, research and development (R&D) innovation, and industrial eco-efficiency in Fujian Province. However, a negative correlation was found between the industrial structure and industrial eco-efficiency in Fujian Province. Moreover, environmental regulation in Fujian Province was not found to significantly influence the industrial eco-efficiency. Hence, through the systematic analysis of industrial eco-efficiency and its influencing factors in Fujian, the study gives further insight on how policy-making can help achieve sustainable development, balancing between economic benefits and ecological improvements.

Suggested Citation

  • Xiaoqing Wang & Qiuming Wu & Salman Majeed & Donghao Sun, 2018. "Fujian’s Industrial Eco-Efficiency: Evaluation Based on SBM and the Empirical Analysis of lnfluencing Factors," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3333-:d:170520
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    as
    1. Zhijun Feng & Wei Chen, 2018. "Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    2. 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.
    3. Picazo-Tadeo, Andrés J. & Castillo-Giménez, Juana & Beltrán-Esteve, Mercedes, 2014. "An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union," Ecological Economics, Elsevier, vol. 100(C), pages 173-182.
    4. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    5. Abreu, M. Florentina & Alves, Anabela C. & Moreira, Francisco, 2017. "Lean-Green models for eco-efficient and sustainable production," Energy, Elsevier, vol. 137(C), pages 846-853.
    6. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    7. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    8. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    9. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    10. Baofeng Shi & Hufeng Yang & Jing Wang & Jingxu Zhao, 2016. "City Green Economy Evaluation: Empirical Evidence from 15 Sub-Provincial Cities in China," Sustainability, MDPI, vol. 8(6), pages 1-39, June.
    11. Briec, W., 2000. "An extended Fare-Lovell technical efficiency measure," International Journal of Production Economics, Elsevier, vol. 65(2), pages 191-199, April.
    12. 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.
    13. Kunapatarawong, Rasi & Martínez-Ros, Ester, 2016. "Towards green growth: How does green innovation affect employment?," Research Policy, Elsevier, vol. 45(6), pages 1218-1232.
    14. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    15. Picazo-Tadeo, Andres J. & Reig-Martinez, Ernest & Hernandez-Sancho, Francesc, 2005. "Directional distance functions and environmental regulation," Resource and Energy Economics, Elsevier, vol. 27(2), pages 131-142, June.
    16. Hua, Zhongsheng & Bian, Yiwen & Liang, Liang, 2007. "Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach," Omega, Elsevier, vol. 35(5), pages 578-587, October.
    17. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    18. Fuyou Guo & Kevin Lo & Lianjun Tong, 2016. "Eco-Efficiency Analysis of Industrial Systems in the Songhua River Basin: A Decomposition Model Approach," Sustainability, MDPI, vol. 8(12), pages 1-19, December.
    19. Mahlberg, Bernhard & Luptacik, Mikulas, 2014. "Eco-efficiency and eco-productivity change over time in a multisectoral economic system," European Journal of Operational Research, Elsevier, vol. 234(3), pages 885-897.
    20. 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.
    21. Tianqun Xu & Ping Gao & Qian Yu & Debin Fang, 2017. "An Improved Eco-Efficiency Analysis Framework Based on Slacks-Based Measure Method," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    22. Hwang, Shiuh-Nan & Chen, Chialin & Chen, Yao & Lee, Hsuan-Shih & Shen, Pei-Di, 2013. "Sustainable design performance evaluation with applications in the automobile industry: Focusing on inefficiency by undesirable factors," Omega, Elsevier, vol. 41(3), pages 553-558.
    23. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    24. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    25. 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.
    26. 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.
    27. 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.
    28. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    29. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    30. Yongrok Choi & Yanni Yu & Hyoung Seok Lee, 2018. "A Study on the Sustainable Performance of the Steel Industry in Korea Based on SBM-DEA," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
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