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Two-Stage Integrated Dynamic Assessment Method for Urban Resilience Based on Multisource Data

Author

Listed:
  • Lulu Shen

    (School of Economics and Management, Hefei University, Hefei 230601, P. R. China†School of Management, University of Science and Technology of China, Hefei 230026, P. R. China)

  • Jianping Li

    (��School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100049, P. R. China)

  • Xiaolei Sun

    (�Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, P. R. China)

  • Weilan Suo

    (�School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, P. R. China¶Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, P. R. China)

Abstract

Urban resilience assessment (URA) is challenging because of urban system complexity and dynamic resilience variability. This paper develops a URA method with comprehensive feature consideration and integrated data use and then constructs a hierarchical URA criteria system. Subsequently, a two-stage integrated dynamic assessment method based on multisource data is presented, wherein the subjective–objective combination weights are determined, and the dimensional and overall urban resilience (UR) indexes are constructed. The applicability and superiority of the proposed method to existing methods are verified using a case study in Beijing. The results showed that UR in Beijing has improved substantially in 2016–2020; social and ecological dimensions are important for UR improvement; and synergies exist between different UR dimensions, which are crucial for resilient urban development. This study provides a systematic solution for URA that features a dynamic perspective, multisource data utilization, and subjective–objective combination weights, enhancing URA comprehensiveness and accuracy.

Suggested Citation

  • Lulu Shen & Jianping Li & Xiaolei Sun & Weilan Suo, 2025. "Two-Stage Integrated Dynamic Assessment Method for Urban Resilience Based on Multisource Data," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 24(01), pages 29-59, January.
  • Handle: RePEc:wsi:ijitdm:v:24:y:2025:i:01:n:s0219622024410013
    DOI: 10.1142/S0219622024410013
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