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Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability

Author

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  • Toshiyuki Sueyoshi

    (New Mexico Institute of Mining & Technology, Department of Management, 801 Leroy Place, Socorro, NM 87801, USA)

  • Yan Yuan

    (New Mexico Institute of Mining & Technology, Department of Management, 801 Leroy Place, Socorro, NM 87801, USA)

  • Aijun Li

    (The Center for Economic Research, Shandong School of Development, Shandong University, Jinan 250100, China)

  • Daoping Wang

    (The Center for Economic Research, Shandong School of Development, Shandong University, Jinan 250100, China)

Abstract

Natural and managerial disposability are two important strategic concepts, whose priorities are economic prosperity and environmental protection, respectively. This study defines social sustainability as the simultaneous achievement of economic prosperity and environmental protection, and then assesses the degree of social sustainability across provinces in China. In addition, this study combines the concepts of natural and managerial disposability with Data Envelopment Analysis window analysis. The method allows for frontier shifts among different time periods and thus can provide more stable and reliable results. This method is applied to assess the energy and environmental performances across the provinces of China during 2003–2014, and provides detailed information about provincial variations, which are valuable and important to policy makers (especially for those in local governments). This study identifies three important findings. First, there were no significant improvements in China’s environmental performance during the analysis periods, since, historically, the governments have not paid enough attention to environmental protection. Second, there are increasing trends in the provincial gaps regarding the environmental performance. In this regard, the central government should help the poor provinces to protect the environment. Third, there are significant differences between the results obtained under natural disposability and those obtained under managerial disposability, since they have different priorities regarding the operational and the environmental performances. Thus, significant contributions can be made by eco-technology progress combined with managerial performance improvements by business leaders and policy makers. This can be a new policy direction for the Chinese government.

Suggested Citation

  • Toshiyuki Sueyoshi & Yan Yuan & Aijun Li & Daoping Wang, 2017. "Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:2078-:d:119417
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    References listed on IDEAS

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    1. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "DEA radial measurement for environmental assessment: A comparative study between Japanese chemical and pharmaceutical firms," Applied Energy, Elsevier, vol. 115(C), pages 502-513.
    2. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
    3. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations," Energy Economics, Elsevier, vol. 56(C), pages 270-287.
    4. 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.
    5. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Japanese fuel mix strategy after disaster of Fukushima Daiichi nuclear power plant: Lessons from international comparison among industrial nations measured by DEA environmental assessment in time hori," Energy Economics, Elsevier, vol. 52(PA), pages 87-103.
    6. Zhang, Yue-Jun & Hao, Jun-Fang & Song, Juan, 2016. "The CO2 emission efficiency, reduction potential and spatial clustering in China’s industry: Evidence from the regional level," Applied Energy, Elsevier, vol. 174(C), pages 213-223.
    7. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    8. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment," Energy Economics, Elsevier, vol. 40(C), pages 130-145.
    9. Sueyoshi, Toshiyuki & Yuan, Yan & Li, Aijun & Wang, Daoping, 2017. "Methodological comparison among radial, non-radial and intermediate approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 67(C), pages 439-453.
    10. 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.
    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. Szopik-Depczyńska, Katarzyna & Cheba, Katarzyna & Bąk, Iwona & Kiba-Janiak, Maja & Saniuk, Sebastian & Dembińska, Izabela & Ioppolo, Giuseppe, 2017. "The application of relative taxonomy to the study of disproportions in the area of sustainable development of the European Union," Land Use Policy, Elsevier, vol. 68(C), pages 481-491.
    13. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    14. Raffaella Taddeo & Alberto Simboli & Giuseppe Ioppolo & Anna Morgante, 2017. "Industrial Symbiosis, Networking and Innovation: The Potential Role of Innovation Poles," Sustainability, MDPI, vol. 9(2), pages 1-17, January.
    15. Sueyoshi, Toshiyuki & Aoki, Shingo, 2001. "A use of a nonparametric statistic for DEA frontier shift: the Kruskal and Wallis rank test," Omega, Elsevier, vol. 29(1), pages 1-18, February.
    16. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions," Energy Economics, Elsevier, vol. 34(3), pages 700-713.
    17. Goto, Mika & Tsutsui, Miki, 1998. "Comparison of Productive and Cost Efficiencies Among Japanese and US Electric Utilities," Omega, Elsevier, vol. 26(2), pages 177-194, April.
    18. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations," Energy Economics, Elsevier, vol. 40(C), pages 370-382.
    20. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    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. 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.
    23. 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.
    24. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    25. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
    26. 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.
    27. Sueyoshi, Toshiyuki & Yuan, Yan, 2015. "China's regional sustainability and diversified resource allocation: DEA environmental assessment on economic development and air pollution," Energy Economics, Elsevier, vol. 49(C), pages 239-256.
    28. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    29. Yang, Wen-Chi & Lee, Yuh-Ming & Hu, Jin-Li, 2016. "Urban sustainability assessment of Taiwan based on data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 341-353.
    30. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    31. 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.
    32. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models," Energy Economics, Elsevier, vol. 34(6), pages 1854-1863.
    33. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Environmental assessment for corporate sustainability by resource utilization and technology innovation: DEA radial measurement on Japanese industrial sectors," Energy Economics, Elsevier, vol. 46(C), pages 295-307.
    34. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    35. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2012. "A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs?," Energy Policy, Elsevier, vol. 46(C), pages 574-584.
    36. 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.
    37. Yao, Xin & Zhou, Hongchen & Zhang, Aizhen & Li, Aijun, 2015. "Regional energy efficiency, carbon emission performance and technology gaps in China: A meta-frontier non-radial directional distance function analysis," Energy Policy, Elsevier, vol. 84(C), pages 142-154.
    38. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    39. Wei, Chu & Ni, Jinlan & Du, Limin, 2012. "Regional allocation of carbon dioxide abatement in China," China Economic Review, Elsevier, vol. 23(3), pages 552-565.
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    Cited by:

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    2. Pang, Qinghua & Qiu, Man & Zhang, Lina & Chiu, Yung-ho, 2023. "Congestion effects of energy and capital in China's carbon emission reduction: Evidence from provincial levels," Energy, Elsevier, vol. 274(C).
    3. Gautier, Axel & Nsabimana, René & Walheer, Barnabé, 2023. "Quality performance gaps and minimal electricity losses in East Africa," Utilities Policy, Elsevier, vol. 82(C).
    4. Nicholas Igbudu & Zanete Garanti & Temitope Popoola, 2018. "Enhancing Bank Loyalty through Sustainable Banking Practices: The Mediating Effect of Corporate Image," Sustainability, MDPI, vol. 10(11), pages 1-11, November.
    5. Tao Ding & Zhixiang Zhou & Qianzhi Dai & Liang Liang, 2020. "Analysis of China’s Regional Economic Environmental Performance: A Non-radial Multi-objective DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1209-1231, April.
    6. Li, Aijun & Zhang, Aizhen & Huang, Huijie & Yao, Xin, 2018. "Measuring unified efficiency of fossil fuel power plants across provinces in China: An analysis based on non-radial directional distance functions," Energy, Elsevier, vol. 152(C), pages 549-561.
    7. Yongzhong Jiang & Xueli Chen & Vivian Valdmanis & Tomas Baležentis, 2019. "Evaluating Economic and Environmental Performance of the Chinese Industry Sector," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    8. Sun, Chuanwang & Liu, Xiaohong & Li, Aijun, 2018. "Measuring unified efficiency of Chinese fossil fuel power plants: Intermediate approach combined with group heterogeneity and window analysis," Energy Policy, Elsevier, vol. 123(C), pages 8-18.
    9. Tingting Yang & Xuefeng Guan & Yuehui Qian & Weiran Xing & Huayi Wu, 2019. "Efficiency Evaluation of Urban Road Transport and Land Use in Hunan Province of China Based on Hybrid Data Envelopment Analysis (DEA) Models," Sustainability, MDPI, vol. 11(14), pages 1-18, July.

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