<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>As urbanization and informatization progress, human societies increasingly face unforeseeable public safety risks, necessitating a comprehensive governance system for early risk prevention. This paper introduces a model for community public safety resilience governance grounded in the adaptive cycle model and formulates research hypotheses. We derive a mathematical formula for calculating the safety disaster risk value using risk management theory, which aids in determining the resilience value and risk level of communities. The proposed governance model assesses community resilience through a four-faceted approach that encompasses natural disasters, accidents, public health events, and social security incidents. The public safety resilience of Community L in N city, Jiangsu Province, was evaluated using this model. Furthermore, it was determined that urban communities in NJ City, WX City, and XZ City had resilience governance scores of 77.655, 73.18, and 73.475, with scores exceeding 70 points. An analysis of 16 subject cities revealed that only five are currently in the renewal stage, representing an optimal state of high resilience and low risk. The remaining 11 cities face varying degrees of challenges. To prevent systemic decay, it is crucial to implement customized public safety governance strategies for different urban types.</p>
</abstract>

As urbanization and informatization progress, human societies increasingly face unforeseeable public safety risks, necessitating a comprehensive governance system for early risk prevention. This paper introduces a model for community public safety resilience governance grounded in the adaptive cycle model and formulates research hypotheses. We derive a mathematical formula for calculating the safety disaster risk value using risk management theory, which aids in determining the resilience value and risk level of communities. The proposed governance model assesses community resilience through a four-faceted approach that encompasses natural disasters, accidents, public health events, and social security incidents. The public safety resilience of Community L in N city, Jiangsu Province, was evaluated using this model. Furthermore, it was determined that urban communities in NJ City, WX City, and XZ City had resilience governance scores of 77.655, 73.18, and 73.475, with scores exceeding 70 points. An analysis of 16 subject cities revealed that only five are currently in the renewal stage, representing an optimal state of high resilience and low risk. The remaining 11 cities face varying degrees of challenges. To prevent systemic decay, it is crucial to implement customized public safety governance strategies for different urban types.

Analysis of the Construction of Resilient Governance System for Public Safety in Urban Communities in Jiangsu--Based on the Perspective of Adaptive Loop Modeling

School of Philanthropy Management, Nanjing Tech University Pujiang Institute

School of Marxism, Nanjing University of Aeronautics and Astronautics

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

As urbanization and informatization progress, human societies increasingly face unforeseeable public safety risks, necessitating a comprehensive governance...

Analysis of the Construction of Resilient Governance System for Public Safety in Urban Communities in Jiangsu--Based on the Perspective of Adaptive Loop Modeling

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 20. Apr. 2024

Akzeptiert: 04. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2023

Schlüsselwörter
Adaptive cycle, Public safety resilience governance, Research hypothesis, Resilience value, Resilience measurement

© 2024 Ruyi Fan., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of the Construction of Resilient Governance System for Public Safety in Urban Communities in Jiangsu--Based on the Perspective of Adaptive Loop Modeling

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 20. Apr. 2024

Akzeptiert: 04. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2023

SchlüsselwörterAdaptive cycle, Public safety resilience governance, Research hypothesis, Resilience value, Resilience measurement

© 2024 Ruyi Fan., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Adaptive cycle, Public safety resilience governance, Research hypothesis, Resilience value, Resilience measurement