摘要
近年来我国风险社会特征日益明显,对政府应急管理能力提出了新的要求。选取三类共12个突发公共事件案例,构建TOE和应急能力双维度理论框架,选定6个影响因素,采取QCA比较分析方法,探究政府应急能力影响因素与组态路径。研究表明,应急智能系统使用、预案演练检查、事件专班设立、信息回应、应急意识培育、总结交流六个因素都不能单独作为政府应急能力的必要条件,政府应急能力强是多个因素共同作用的结果。进一步分析出智慧技术驱动型、应急氛围培育型、综合协同治理型三种关键条件组态路径。结合具体案例,从加强应急技术开发、重视应急文化培育、优化协同体系等角度针对性提出提升政府应急能力的对策建议。
In recent years,risk society has been increasingly characterized,which puts forward new requirements for the government's emergency management capability.Choose three types of public emergencies with a total of 12 cases,construct a two-dimensional theoretical framework of Technology-Qrganization-Environment and emergency response capability,select six influencing factors,and adopt the QCA comparative analysis method to explore the influencing factors and grouping paths of the government's emergency response capability.The study shows that none of the six factors,including the use of emergency intelligent system,the checking of plan rehearsal,the establishment of incident task force,the response of information,the cultivation of emergency awareness,and the summarization and communication,can be regarded as the necessary conditions of government emergency response capability alone,and a strong government emergency response capability is the result of the joint action of multiple factors.Three key conditions are further analyzed:intelligent technology driven,emergency atmosphere cultivation,and comprehensive collaborative governance.Combined with specific cases,countermeasures and suggestions for improving government emergency response capability are proposed from the perspectives of strengthening emergency technology development,emphasizing emergency culture cultivation and optimizing the synergistic system.
作者
李世祥
李尚蔚
雷婷婷
Li Shixiang;Li Shangwei;Lei Tingting
出处
《中国应急管理科学》
2024年第1期83-96,共14页
Journal of China Emergency Management Science
基金
国家社会科学基金重点项目“新时代公共安全应急框架体系研究”(23AZD072)
中央高校基本科研业务费专项资金资助项目“自然灾害与应急管理”(CUG2642022006)。
关键词
突发公共事件
政府应急能力
定性比较分析(QCA)
Public Emergencies
Government Emergency Response Capacity
Qualitative Comparative Analysis