Understanding the influence of multiple information sources on risk perception dynamics and evacuation decisions: An agent-based modeling approach
Understanding the influence of multiple information sources on risk perception dynamics and evacuation decisions: An agent-based modeling approach
复制标题
DOI：
10.1016/j.ijdrr.2022.103328
复制
发表时间：
2022-10-06
影响因子：
5
通讯作者：
Mozumder，Pallab
中科院分区：
文献类型：
--
作者：
Roy，Kamol C.;Hasan，Samiul;Mozumder，Pallab
疏散是自然灾害期间减少风险的最有效战略之一。虽然许多研究已经调查了影响疏散决策的因素（例如，社会经济、风险预测、人口统计、环境线索等），所有这些因素在形成整体风险认知和疏散决策中如何相互作用还未得到充分研究。在这里，我们提出了一个基于代理的模型，利用灾后调查的经验证据来创建代理（家庭）的疏散趋势，并集成洪水相关的灾害风险，家庭的社会人口因素，社会网络特征和决策，以及邻居的决策动态演变复杂的决策模式在飓风疏散。我们模拟了多个信息源和他们的感知可信度对疏散参与的影响，分别确定疏散合规性（定义为从官方发布强制疏散命令的地方疏散）和影子疏散（定义为自发疏散，从地方没有发布强制命令）。我们使用的社会人口统计数据来自美国。S.美国人口普查局的数据、县网站的建筑足迹数据、美国环境保护局的雨水管理模型（SWMM）的径流数据以及所有其他数据都是在模型中综合生成的。我们的案例研究的基础上，社区的迈阿密戴德县表明，更高的感知可信度的危害风险导致更高的疏散遵守。我们还发现，虽然社交网络增加了整体疏散参与，但它们也增加了阴影疏散，对邻居行动的更高信任降低了疏散率。这项研究为应急管理提供了见解，以设计适当的战略，在灾害期间提供灾害预测或沟通整体风险。
Evacuation is one of the most effective strategies to reduce risk during natural disasters. Although many studies have investigated factors affecting evacuation decisions (e.g., socio-economic, risk forecast, demographic, environmental cues, etc.), how all these factors interplay in forming the overall risk perception and evacuation decision is underexplored. Here, we present an agent-based model that leverages empirical evidence from post-disaster surveys to create evacuation tendencies of the agents (households) and integrates flood-related hazard risk, household socio-demographic factors, social network characteristics and decisions, and neighbors’ decisions to dynamically evolve complex decision-making pattern during hurricane evacuation. We simulate the effect of multiple information sources and their perceived credibility on evacuation participation by separately determining evacuation compliance (defined as evacuation from places where official mandatory evacuation order is issued) and shadow evacuation (defined as spontaneous evacuation from places where a mandatory order is not issued). We use socio-demographic data from U. S. Census Bureau, building footprint data from County Website, run off data from Stormwater Management Model (SWMM) of U.S. Environmental Protection Agency, and all other data were synthetically generated within the model. Our case study based on a community of Miami-Dade County indicates that higher perceived credibility of hazard risk leads to higher evacuation compliance. We have also found that while social networks increase overall evacuation participation, they also increase shadow evacuation and higher trust on neighbor actions reduces evacuation rates. This study gives insights for emergency management to design appropriate strategies for providing hazard forecasts or communicating overall risk during disasters.