When crisis strikes, why do some communities utilize evacuation shelters more than others? This mixed methods study draws on a new dataset of almost-daily tallies of evacuees at 660 local shelters following Japan’s 2018 Eastern Iburi Earthquake in Hokkaido to create a large-N time-series cross sectional (TSCS) dataset of local, short-distance evacuation. We pair time-series cross-sectional data models with qualitative comparative analysis (QCA) of nine affected municipalities to examine why some shelters see higher evacuation rates than others. While past studies have used Facebook user data, post-hoc surveys, or ad-hoc roadside interviews to measure evacuation, this study uses meticulously recorded shelter attendance data to draw inferences about evacuation behavior. Controlling for types of shelters, damage levels, infrastructure quality, social vulnerability, governance capacity, and community resources, we find that in affected communities, stronger bridging social ties, especially when aided by linking ties, motivate greater evacuation to shelters. In unaffected communities, stronger bonding and bridging ties encourage potentially unnecessary evacuation, helping spread rumors during blackouts. These results highlight the necessity of clear, transparent communication with the public, and fostering trust in government during crises.

当危机袭来时，为什么有些社区比其他社区更多地使用避难所？这项混合方法研究借鉴了日本2018年北海道东部伊布里（Eburi）地震之后在660个避难所中几乎每天清点人员的新数据集，以创建一个大N时间序列横截面（TSCS）数据集，用于本地，短途疏散。我们将时间序列横截面数据模型与9个受影响城市的定性比较分析（QCA）配对，以研究为什么某些避难所的疏散率高于其他避难所。尽管过去的研究使用Facebook用户数据，事后调查或临时路边采访来衡量疏散情况，但本研究使用精心记录的避难人员出勤数据来得出有关疏散行为的推论。控制避难所的类型，破坏程度，基础设施质量，在社会脆弱性，治理能力和社区资源方面，我们发现，在受影响的社区中，建立更紧密的社会纽带，尤其是在联系纽带的帮助下，会促使人们向避难所疏散。在未受影响的社区中，更牢固的联系和桥梁联系会鼓励潜在的不必要的疏散，从而有助于在停电期间散布谣言。这些结果凸显了与公众进行清晰透明沟通的必要性，并在危机期间建立了对政府的信任。在停电期间协助散布谣言。这些结果凸显了与公众进行清晰透明沟通的必要性，并在危机期间建立了对政府的信任。在停电期间协助散布谣言。这些结果凸显了与公众进行清晰透明沟通的必要性，并在危机期间建立了对政府的信任。