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Sustainability Assessment of Autonomous Regions in China Using GRA-SPA Method


  • Ruxue Shi

    (Department of Technical Economics and Management, School of Business Administration, Northeastern University, Shenyang 110167, China
    Department of Trade Finance, School of Economics and Management, Ningxia Institute of Science and Technology, Ningxia 753400, China)

  • Pingtao Yi

    (Department of Technical Economics and Management, School of Business Administration, Northeastern University, Shenyang 110167, China)

  • Weiwei Li

    (Department of Technical Economics and Management, School of Business Administration, Northeastern University, Shenyang 110167, China)

  • Lu Wang

    (Department of Technical Economics and Management, School of Business Administration, Northeastern University, Shenyang 110167, China)


Sustainability development is a core issue in autonomous regions’ construction and development. The paper evaluated the sustainability development of the five autonomous regions in Western China from 2010 to 2019. In order to further analyze the sustainable development level of the autonomous regions, it is compared with the three provinces with the largest GDP in Central China in the past three years, and similarly, with the three provinces in Eastern China. A new weighting method was proposed by combining the grey relational analysis (GRA) and set pair analysis (SPA) methods that not only analyze the correlation between indicators and ideal points but also analyze the status and development trend. The method can ensure the objectivity of indicator weight. Firstly, the ideal reference point is determined by the grey correlation degree between the indicator and the ideal positive point. Secondly, the indicator and the ideal reference point constitute a set pair system, and the relation number is used further to analyze the status and development trend of the indicator to determine the weight objectively. The sustainability results showed that the progress of the autonomous regions’ sustainable development in China was increased slowly in 2010–2019. For example, Ningxia and Xinjiang saw the slowest growth. The prime reason is that economic sustainability has declined severely. Although Inner Mongolia presented the highest increasing trends, the growth rate value was 0.75%. In contrast, other autonomous regions showed a negative growth trend. Regarding sustainable development in three dimensions, the economic sustainability performance of autonomous regions is not ideal, but the environmental sustainability performance is the most ideal. This conclusion implicates the necessity and urgency of improving the coordinated development of the three dimensions of autonomous regions in China.

Suggested Citation

  • Ruxue Shi & Pingtao Yi & Weiwei Li & Lu Wang, 2021. "Sustainability Assessment of Autonomous Regions in China Using GRA-SPA Method," Sustainability, MDPI, vol. 13(19), pages 1-19, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11008-:d:649773

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    References listed on IDEAS

    1. Deshan Li & Rongwei Wu, 2018. "A Dynamic Analysis of Green Productivity Growth for Cities in Xinjiang," Sustainability, MDPI, vol. 10(2), pages 1-13, February.
    2. Lee Liu & Jie Liu & Zhenguo Zhang, 2014. "Environmental Justice and Sustainability Impact Assessment: In Search of Solutions to Ethnic Conflicts Caused by Coal Mining in Inner Mongolia, China," Sustainability, MDPI, vol. 6(12), pages 1-19, December.
    3. Liu, Yansui, 2018. "Introduction to land use and rural sustainability in China," Land Use Policy, Elsevier, vol. 74(C), pages 1-4.
    4. Jean-Philippe Boussemart & Hervé Leleu & Zhiyang Shen & Vivian Valdmanis, 2020. "Performance analysis for three pillars of sustainability," Journal of Productivity Analysis, Springer, vol. 53(3), pages 305-320, June.
    5. Koray Altintas & Ozalp Vayvay & Sinan Apak & Emine Cobanoglu, 2020. "An Extended GRA Method Integrated with Fuzzy AHP to Construct a Multidimensional Index for Ranking Overall Energy Sustainability Performances," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    6. Wenfei Luan & Ling Lu & Xin Li & Chunfeng Ma, 2018. "Integrating Extended Fourier Amplitude Sensitivity Test and Set Pair Analysis for Sustainable Development Evaluation from the View of Uncertainty Analysis," Sustainability, MDPI, vol. 10(7), pages 1-23, July.
    7. Ya Wang & Lihua Zhou, 2016. "Assessment of the Coordination Ability of Sustainable Social-Ecological Systems Development Based on a Set Pair Analysis: A Case Study in Yanchi County, China," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    8. Wei Zhang & Xinxin Zhang & Fan Liu & Yan Huang & Yuwei Xie, 2020. "Evaluation of the Urban Low-Carbon Sustainable Development Capability Based on the TOPSIS-BP Neural Network and Grey Relational Analysis," Complexity, Hindawi, vol. 2020, pages 1-16, December.
    9. Pingtao Yi & Lu Wang & Danning Zhang & Weiwei Li, 2019. "Sustainability Assessment of Provincial-Level Regions in China Using Composite Sustainable Indicator," Sustainability, MDPI, vol. 11(19), pages 1-20, September.
    10. Costanza, Robert & Patten, Bernard C., 1995. "Defining and predicting sustainability," Ecological Economics, Elsevier, vol. 15(3), pages 193-196, December.
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