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Comprehensive Evaluation of Regional Sustainable Development Based on Data Envelopment Analysis

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  • Zhijiang Li

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
    Institute of Climate Change and Public Policy, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Decai Tang

    (Institute of Climate Change and Public Policy, Nanjing University of Information Science & Technology, Nanjing 210044, China
    China Institute of Manufacturing Development, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Mang Han

    (Institute of Climate Change and Public Policy, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Brandon J. Bethel

    (School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

In the light of the shortcomings of the analytic hierarchy process and other common regional sustainable development evaluation methods, this paper proposes the use of a combination of subjective and objective weights to generate input/output indicators using the Data Envelopment Analysis (DEA) method. Using this methodology, we construct a comprehensive evaluation index which is useful in expanding the application of Data Envelopment Analysis (DEA) in the comprehensive evaluation of sustainable development. Moreover, this paper addresses the shortfalls of the traditional DEA evaluation model and uses the Super-Slack Based Measure (SBM)-Undesirable and DEA-Malmquist evaluation models, which are based on traditional DEA model optimization, to analyze the spatio-temporal characteristics of sustainable development on regional scales. Using China’s Yangzte River Economic Belt as an example, an empirical analysis is carried out. We show that analysis results are virtually identical to the extant situation and can objectively reflect the status and abilities of sustainable development in each subregion. Additionally, from the angles of input, output and technological progress, this paper uses the DEA evaluation method to analyze the reasons behind the slow development in several provinces and municipalities along the Yangzte River Economic Belt (YERB). The regional characteristics of each province and city within our study are combined to explore the optimal mechanisms for sustainable development.

Suggested Citation

  • Zhijiang Li & Decai Tang & Mang Han & Brandon J. Bethel, 2018. "Comprehensive Evaluation of Regional Sustainable Development Based on Data Envelopment Analysis," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:3897-:d:178486
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    References listed on IDEAS

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    Cited by:

    1. Kai Li & Zhili Ma & Guozhou Zhang, 2019. "Evaluation of the Supply-Side Efficiency of China’s Real Estate Market: A Data Envelopment Analysis," Sustainability, MDPI, vol. 11(1), pages 1-18, January.
    2. Gang Liu & Fan Zhang, 2022. "Land Zoning Management to Achieve Carbon Neutrality: A Case Study of the Beijing–Tianjin–Hebei Urban Agglomeration, China," Land, MDPI, vol. 11(4), pages 1-18, April.
    3. Zhiwei Pan & Decai Tang & Haojia Kong & Junxia He, 2022. "An Analysis of Agricultural Production Efficiency of Yangtze River Economic Belt Based on a Three-Stage DEA Malmquist Model," IJERPH, MDPI, vol. 19(2), pages 1-15, January.
    4. Hania Rahma & Akhmad Fauzi & Bambang Juanda & Bambang Widjojanto, 2019. "Development of a Composite Measure of Regional Sustainable Development in Indonesia," Sustainability, MDPI, vol. 11(20), pages 1-16, October.
    5. Decai Tang & Zhijiang Li & Brandon J. Bethel, 2019. "Relevance Analysis of Sustainable Development of China’s Yangtze River Economic Belt Based on Spatial Structure," IJERPH, MDPI, vol. 16(17), pages 1-16, August.
    6. Nomita Pachar & Jyoti Dhingra Darbari & Kannan Govindan & P. C. Jha, 2022. "Sustainable performance measurement of Indian retail chain using two-stage network DEA," Annals of Operations Research, Springer, vol. 315(2), pages 1477-1515, August.
    7. Georgios Tsaples & Jason Papathanasiou & Andreas C. Georgiou, 2022. "An Exploratory DEA and Machine Learning Framework for the Evaluation and Analysis of Sustainability Composite Indicators in the EU," Mathematics, MDPI, vol. 10(13), pages 1-27, June.
    8. Brodny, Jarosław & Tutak, Magdalena, 2023. "Assessing regional implementation of Sustainable Development Goal 9 “Build resilient infrastructure, promote sustainable industrialization and foster innovation” in Poland," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    9. Keihan Hassanzadehkermanshahi & Sara Shirowzhan, 2022. "Measuring Urban Sustainability over Time at National and Regional Scale for Addressing United Nations Sustainable Development Goal (SDG) 11: Iran and Tehran as Case Studies," Sustainability, MDPI, vol. 14(12), pages 1-25, June.
    10. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.

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