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CRITIC-TOPSIS Based Evaluation of Smart Community Governance: A Case Study in China

Author

Listed:
  • Jiyao Yin

    (Technology and Information Center, Shenzhen Urban Public Safety and Technology Institute, Shenzhen 518000, China)

  • Jueqi Wang

    (School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Chenyang Wang

    (School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Linxiu Wang

    (School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Zhangyu Chang

    (Technology and Information Center, Shenzhen Urban Public Safety and Technology Institute, Shenzhen 518000, China)

Abstract

As the basic unit of a smart city, the smart community has received considerable attention and problems in community governance have appeared simultaneously. Previous studies of smart community governance have failed to encompass all aspects, especially the evaluation tools for ensuring its outcomes. Therefore, this paper developed a comprehensive evaluation framework based on the CRITIC-TOPSIS method combined with the identified evaluation indicators. Seven smart communities from four cities in China were selected as cases to show how this evaluation framework could be applied to decision-making. The results indicated that the evaluation indicator ”Mediation of Conflict” had the highest weight while ”The participation of social enterprises in governance” had the lowest weight. Furthermore, the Yucun community presented the highest governance performance among these seven smart communities. Several strategies are proposed for improving the level of smart community governance, such as devoting significant resources to develop infrastructure in smart communities, facilitating communication among multiple participants, and increasing funding for the implementation of smart communities. This research contributes both to the innovation of community governance evaluation and to the improvement of smart communities.

Suggested Citation

  • Jiyao Yin & Jueqi Wang & Chenyang Wang & Linxiu Wang & Zhangyu Chang, 2023. "CRITIC-TOPSIS Based Evaluation of Smart Community Governance: A Case Study in China," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:1923-:d:1041271
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    References listed on IDEAS

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    1. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    2. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2017. "Decomposing inequality in energy-related CO2 emissions by source and source increment: The roles of production and residential consumption," Energy Policy, Elsevier, vol. 107(C), pages 698-710.
    3. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    4. Wang, Zhaohua & Wang, Xiaomeng & Guo, Dongxue, 2017. "Policy implications of the purchasing intentions towards energy-efficient appliances among China’s urban residents: Do subsidies work?," Energy Policy, Elsevier, vol. 102(C), pages 430-439.
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