Proceedings of the 3rd International Conference on Public Management and Big Data Analysis, PMBDA 2023, December 15–17, 2023, Nanjing, China

Research Article

An SEM Analysis of Perceived Urban Community Resilience of Citizens from Shanghai and Wuhan in Post Covid Era

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  • @INPROCEEDINGS{10.4108/eai.15-12-2023.2345342,
        author={Tan  Mu and Limu  Fai and Bojia  Yuan and Wangrui  Min},
        title={An SEM Analysis of Perceived Urban Community Resilience of Citizens from Shanghai and Wuhan in Post Covid Era},
        proceedings={Proceedings of the 3rd International Conference on Public Management and Big Data Analysis, PMBDA 2023, December 15--17, 2023, Nanjing, China},
        publisher={EAI},
        proceedings_a={PMBDA},
        year={2024},
        month={5},
        keywords={structural equation model; urban community resilience; crisis learning shanghai wuhan},
        doi={10.4108/eai.15-12-2023.2345342}
    }
    
  • Tan Mu
    Limu Fai
    Bojia Yuan
    Wangrui Min
    Year: 2024
    An SEM Analysis of Perceived Urban Community Resilience of Citizens from Shanghai and Wuhan in Post Covid Era
    PMBDA
    EAI
    DOI: 10.4108/eai.15-12-2023.2345342
Tan Mu1,*, Limu Fai1, Bojia Yuan1, Wangrui Min1
  • 1: Donghua University
*Contact email: 13810647765@163.com

Abstract

Ever since the post Covid era to enhance the capacity of urban community resilience and level of emergency governance has been a major concern for local government and rose on top of national agenda. This essay employed the SEM analysis to research how the perception of urban community resilience by citizens in metropolitans exhibited in different facets. A questionnaire including 6 latent variables and 40 items have been designed and tested by a theory model incorporating variants like baseline community resilience, crisis learning, conflict resolution, community leadership as well as services provided by community civil organizations. A second-order construct termed post Covid community resilience is coined to evaluate how citizens may evolve after learning from coping with persistent strikes of crises and adapt with continuously changing regulations. By disseminating the questionnaire online in Shanghai and Wuhan, the researchers collected and trimmed the data, compared the SEM models by using Amos 24 and suggested a significant positive correlation between the former three variables (baseline community resilience, crisis learning, post Covid community resilience). The crisis learning is emphasized and this research contribute by initiating an innate perspective of resilience to adapt and invent new ways from local resources and personnel.