RAPID/Collaborative Research: Households' Immediate Protective Actions and Trade-Off Processes Between Property Security and Life Safety in Response to 2022 Hurricane Ian

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In recent years, increased climate change together with rising populations in coastal communities has exposed residents to escalating risks of destructive extreme weather events such as hurricanes. These threats are increasing the urgency of conducting studies on coastal households’ risk perceptions and behavioral responses that could improve policies to protect lives and property. Despite decades of progress, hurricane evacuation studies still lack an adequate understanding of households’ decisions about the trade-offs between property protection and life safety among alternative protective actions. Hurricane Ian was a Category 4 storm with a last-minute intensification and track-change that affected a wide range of communities with diverse socio-demographic characteristics. This hurricane presents a unique opportunity to study how households dealt with conflicting objectives in their protective action decision making and why they delayed evacuating or even refused to leave. This Grant for Rapid Response Research (RAPID) project enhances scientific knowledge of households’ emergency responses to hurricane threats by extending the Protective Action Decision Model (PADM) and gathering critical data in two coastal counties and one inland county in Florida. The outcomes promote teaching, training, and learning; increase the participation of underrepresented groups; and significantly improve emergency management and community resilience across the US coastal areas.This project addresses four current limitations in the evacuation literature: 1) risk communication challenges amid rapid changes in hurricane characteristics; 2) the low accuracy in predicting protective action decisions based on linear statistical approaches; 3) an inadequate understanding of households’ decisions in the context of buildings’ vulnerabilities to extreme environmental conditions (e.g., the actual strength of houses against hurricane-force wind speeds); and 4) ignoring tradeoffs among protective action alternatives during the evacuation decision-making process. To tackle these research challenges, this project gathers ephemeral data on housing damage and empirical data regarding households’ experiences and perceptions. The five tasks include 1) field investigation; 2) household survey; 3) comparison of respondents’ perceptions against risk levels as evaluated by experts; 4) comparison of conventional linear regression analyses and machine-learning-enhanced logistic regression models; and 5) development of a trade-off model of decision making among multiple protective actions. This project advances the state of knowledge about households’ protective action decision making and tradeoffs among protective action PA alternatives in response to a hurricane emergency.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.