数智赋能应急管理体系和能力现代化建设影响因素分析:基于DEMATEL-ISM方法

doi:10.16265/j.cnki.issn1003-3033.2025.11.0259

摘要/Abstract

摘要： 为探究应急管理体系与能力现代化建设进程中数智赋能所发挥的作用,明确关键影响因素并梳理因素间的关系。利用Citespace软件聚类分析国内外相关文献,借助Nvivo12plus软件从环境、机制、技术、数据4方面识别16项影响因素;利用决策试验与评价试验量(DEMATEL)模型计算识别出16项影响因素,确定各因素间的影响度、被影响度、中心度和原因度;应用解释结构模型(ISM)分析影响因素的层次结构,确定其内在逻辑关系和层级结构,并将2种模型结合,识别出关键因素。结果表明:政治法律、文化意识、需求供应、管理策略与规划、管理者关注与支持5个因素在影响度、被影响度、中心度以及原因度等指标中排名前列,是推动应急管理体系现代化建设的关键影响因素。

关键词: 数智赋能, 应急管理体系, 能力现代化建设, 影响因素, 决策试验与评价实验室(DEMATEL), 解释结构模型(ISM)

Abstract:

In order to explore the role of intelligent and digital empowerment in the modernization of emergency management systems and capacities, this study identified the key influencing factors and clarifies their interrelationships. CiteSpace was applied to cluster and analyze relevant domestic and international literature, while NVivo12plus, combined with expert consultations, was used to identify 16 influencing factors from four dimensions: environment, mechanism, technology, and data. DEMATEL method was employed to calculate the influence, dependence, centrality, and causality of each factor, and ISM was used to construct a hierarchical structure and reveal their internal logical relationships. By integrating the DEMATEL and ISM models, five key factors were identified, namely political and legal frameworks, cultural awareness, demand and supply, management strategies and planning, and managerial attention and support, which rank highest in multiple indicators and play a significant role in promoting modernization.

Key words: digital intelligence empowerment, emergency management system, modernization of capabilities construction, influencing factors, decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modeling (ISM)

中图分类号:

X915.2安全社会学

吴翊鸣, 申霞. 数智赋能应急管理体系和能力现代化建设影响因素分析:基于DEMATEL-ISM方法[J]. 中国安全科学学报, 2025, 35(11): 236-244.

WU Yiming, SHEN Xia. Analysis of influencing factors on digital intelligence empowering emergency management system and capacity modernization: based on DEMATEL-ISM method[J]. China Safety Science Journal, 2025, 35(11): 236-244.

图/表 7

图1

图2

表1

关键影响因素及其释义

维度	影响因素	因素释义	维度	影响因素	因素释义
环境 C₁	政治法律F₁	数智应急的政治体制、政府政策、法律法规等^[9]	技术 C₃	硬件建设F₉	信息采集、存储、处理过程中所需的基础设施(如传感器、存储服务器、计算器等)建设^[17-18]
	文化意识F₂	应急管理领域与数智有关的价值观、语言文化、教育水平以及对数智意识的探讨、培养^[10]		技术交流F₁₀	以大数据、云计算、物联网、人工智能为代表的新型数智技术的讨论^[19]
	需求供应F₃	需求方对数据或服务的需求现状以及数据资源供给方提供数据或服务的能力^[11]		信息共享F₁₁	应急系统内打破信息壁垒,提升横纵传递效率,以及畅通应急系统与外界交互渠道^[20]
机制 C₂	管理策略与规划F₄	为实现数智应急长期目标的顶层设计,包含为适应数智化趋势,对应急管理体制和工作机制建设的思考^[12]		系统应用F₁₂	用于数据操作、管理系统及信息交互的平台,如“互联网+执法”、应急管理“一张图” “天眼”卫星监测系统等应用系统等^[4]
	管理者关注与支持F₅	组织管理层对于数智赋能的重视及资源支持,如人力,财力支持等^[13]		技术效果F₁₃	对数智技术嵌入应急管理后,是否可以面向实际的应急管理需求提供相应的功能进行评估并为改进提供依据^[21]
	持续监督反馈提升F₆	在数智赋能进程中,持续发现和纠正问题,建立反馈和持续提升改进机制^[14]	数据 C₄	数据采集F₁₄	运用各种手段与技术对风险、突发事件等对象的数据收集与生产^[22]
	职业素养提升F₇	在数智赋能进程中,各阶段相关人员能力提升^[15]		数据整理F₁₅	对收集的数据按照固定的格式,进行分类的整理与存储,并组建数据库以供便捷取阅^[23]
	多元主体合作F₈	实现政府、企业、社会之间的协调与合作^[16]		数据分析F₁₆	利用大数据、云计算、人工智能等数智技术,对数据进行深度的分析,挖掘内在价值,提供智力支持^[24]

表1

表2

表3

表4

图3

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因素	D	C	M	R	W	因素属性	因素	D	C	M	R	W	因素属性
F₁	1.428	0.362	1.790	1.066	0.117	原因	F₉	0.234	0.575	0.808	-0.341	0.053	结果
F₂	0.722	0.254	0.976	0.468	0.064	原因	F₁₀	0.091	0.439	0.530	-0.348	0.035	结果
F₃	0.576	0.524	1.100	0.051	0.072	原因	F₁₁	0.182	0.423	0.604	-0.241	0.040	结果
F₄	1.255	0.599	1.855	0.656	0.121	原因	F₁₂	0.401	0.422	0.823	-0.021	0.054	结果
F₅	1.032	0.659	1.691	0.374	0.111	原因	F₁₃	0.331	0.442	0.773	-0.111	0.051	结果
F₆	0.371	0.513	0.884	-0.141	0.058	结果	F₁₄	0.165	0.501	0.666	-0.335	0.044	结果
F₇	0.387	0.356	0.743	0.032	0.049	原因	F₁₅	0.087	0.526	0.613	-0.439	0.040	结果
F₈	0.176	0.465	0.641	-0.289	0.042	结果	F₁₆	0.199	0.580	0.779	-0.380	0.051	结果

级别	要素	层级
L₁	F₇、F₈、F₉、F₁₀、F₁₁、F₁₄、F₁₅、F₁₆	第1层(表层)
L₂	F₆、F₁₂、F₁₃	第2层(中层)
L₃	F₃、F₅	第3层(深层)
L₄	F₁、F₂、F₄	第4层(根源)