A Cross‐Community Comparison of Antecedents of Hurricane Ian Risk Perceptions and Evacuation Behaviours.
Published In: Journal of Contingencies & Crisis Management, 2024, v. 32, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Zhang, Xiaochen Angela; Borden, Jonathan 3 of 3
Abstract
This study seeks to understand how historical models of risk perception and protective action antecedents, as predicted by The Protective Action Decision Model (PADM), apply across micro‐regional differences in the context of Florida counties during the 2022 Hurricane Ian, and how these regional differences may lead to differences in reception, perception and response to information and evacuation warnings across the state. Two Florida communities (Southwest vs. Central and Eastern regions) with different typography, historical disaster experience, demographics and existing hazard adjustment programs were surveyed and compared. Results showed that, within the same hurricane event and broader geographic region (Florida), the two community locations differ in their reliance on information sources, social cues and prior hurricane experiences to inform risk perceptions and evacuation decisions. Additionally, different mediation patterns of risk perceptions were found between the antecedents and evacuation behaviours for the different community locations. The findings imply the importance to consider regional variations and to strategize messaging communicating risk and self‐protective behaviours accordingly. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Contingencies & Crisis Management. 2024/12, Vol. 32, Issue 4, p1
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2024
- ISSN:0966-0879
- DOI:10.1111/1468-5973.70009
- Accession Number:181847137
- Copyright Statement:Copyright of Journal of Contingencies & Crisis Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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