IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p11008-d649773.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

Abstract

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/11008/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/19/11008/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Małgorzata Trojanowska & Krzysztof Nęcka, 2020. "Selection of the Multiple-Criiater Decision-Making Method for Evaluation of Sustainable Energy Development: A Case Study of Poland," Energies, MDPI, vol. 13(23), pages 1-24, November.
    2. Zhang, Pengyan & Yang, Dan & Qin, Mingzhou & Jing, Wenlong, 2020. "Spatial heterogeneity analysis and driving forces exploring of built-up land development intensity in Chinese prefecture-level cities and implications for future Urban Land intensive use," Land Use Policy, Elsevier, vol. 99(C).
    3. Rigby, Dan & Woodhouse, Phil & Young, Trevor & Burton, Michael, 2001. "Constructing a farm level indicator of sustainable agricultural practice," Ecological Economics, Elsevier, vol. 39(3), pages 463-478, December.
    4. Jianglin Lu & Keqiang Wang & Hongmei Liu, 2022. "Residents’ Selection Behavior of Compensation Schemes for Construction Land Reduction: Empirical Evidence from Questionnaires in Shanghai, China," Land, MDPI, vol. 12(1), pages 1-29, December.
    5. Lü, Da & Gao, Guangyao & Lü, Yihe & Xiao, Feiyan & Fu, Bojie, 2020. "Detailed land use transition quantification matters for smart land management in drylands: An in-depth analysis in Northwest China," Land Use Policy, Elsevier, vol. 90(C).
    6. Yang, Yuanyuan & Bao, Wenkai & Liu, Yansui, 2020. "Scenario simulation of land system change in the Beijing-Tianjin-Hebei region," Land Use Policy, Elsevier, vol. 96(C).
    7. Qiu, Bingwen & Li, Haiwen & Tang, Zhenghong & Chen, Chongcheng & Berry, Joe, 2020. "How cropland losses shaped by unbalanced urbanization process?," Land Use Policy, Elsevier, vol. 96(C).
    8. Magdalena Raftowicz & Bertrand le Gallic & Magdalena Kalisiak-Mędelska & Krzysztof Rutkiewicz & Emilia Konopska-Struś, 2021. "Effectiveness of Public Aid for Inland Aquaculture in Poland—The Relevance of Traditional Performance Ratios," Sustainability, MDPI, vol. 13(9), pages 1-22, May.
    9. Weijia Chen & Yongquan Lu & Guilin Liu, 2022. "Balancing cropland gain and desert vegetation loss: The key to rural revitalization in Xinjiang, China," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1122-1145, September.
    10. Wang, Bo & Li, Fan & Feng, Shuyi & Shen, Tong, 2020. "Transfer of development rights, farmland preservation, and economic growth: a case study of Chongqing’s land quotas trading program," Land Use Policy, Elsevier, vol. 95(C).
    11. Veland Ramadani & Sucheta Agarwal & Andrea Caputo & Vivek Agrawal & Jitendra Kumar Dixit, 2022. "Sustainable competencies of social entrepreneurship for sustainable development: Exploratory analysis from a developing economy," Business Strategy and the Environment, Wiley Blackwell, vol. 31(7), pages 3437-3453, November.
    12. Chi, Yuan & Liu, Dahai & Wang, Jing & Wang, Enkang, 2020. "Human negative, positive, and net influences on an estuarine area with intensive human activity based on land covers and ecological indices: An empirical study in Chongming Island, China," Land Use Policy, Elsevier, vol. 99(C).
    13. Xinhui Feng & Yan Li & Lu Zhang & Chuyu Xia & Er Yu & Jiayu Yang, 2022. "Carbon Metabolism in Urban “Production–Living–Ecological” Space Based on Ecological Network Analysis," Land, MDPI, vol. 11(9), pages 1-22, August.
    14. Xu, Tingting & Gao, Jay & Li, Yuhua, 2019. "Machine learning-assisted evaluation of land use policies and plans in a rapidly urbanizing district in Chongqing, China," Land Use Policy, Elsevier, vol. 87(C).
    15. Yin, Xu & Wang, Jing & Li, Yurui & Feng, Zhiming & Wang, Qianyi, 2021. "Are small towns really inefficient? A data envelopment analysis of sampled towns in Jiangsu province, China," Land Use Policy, Elsevier, vol. 109(C).
    16. Vincenzo Formisano & Bernardino Quattrociocchi & Maria Fedele & Mario Calabrese, 2018. "From Viability to Sustainability: The Contribution of the Viable Systems Approach (VSA)," Sustainability, MDPI, vol. 10(3), pages 1-17, March.
    17. Lili Guo & Yuting Song & Mengqian Tang & Jinyang Tang & Bright Senyo Dogbe & Mengying Su & Houjian Li, 2022. "Assessing the Relationship among Land Transfer, Fertilizer Usage, and PM 2.5 Pollution: Evidence from Rural China," IJERPH, MDPI, vol. 19(14), pages 1-18, July.
    18. Liu, Yansui & Zhou, Yang, 2021. "Territory spatial planning and national governance system in China," Land Use Policy, Elsevier, vol. 102(C).
    19. Xi Yang & Xingwei Chen, 2021. "Using a combined evaluation method to assess water resources sustainable utilization in Fujian Province, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 8047-8061, May.
    20. Antonín Vaishar & Milada Šťastná, 2019. "Sustainable Development of a Peripheral Mountain Region on the State Border: Case Study of Moravské Kopanice Microregion (Moravia)," Sustainability, MDPI, vol. 11(19), pages 1-15, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11008-:d:649773. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.