Modeling Evacuees’ Intended Responses to a Phased Hurricane Evacuation Order
Source abstract
Abstract
Phased evacuation is an under-studied strategy, and relatively little is known about compliance with the phased process. This study modelled households’ responses to a phased evacuation order based on a household behavioral intention survey. About 66% of the evacuees reported that they would comply with a phased evacuation order. A latent class logit model sorted evacuees into two classes (“evacuation reluctant” and “evacuation keen”) by their stakeholder perceptions (i.e., whether government agencies have responsibility for the safety of individuals) and evacuation perceptions (i.e., whether evacuation is an effective protective action), while risk perception becomes non-significant in interpreting their compliance behavior to a phased evacuation order. Those that evacuate to the home of friends/relatives and/or bring more vehicles during evacuation are less likely to follow phased evacuation orders. “Evacuation reluctant” individuals with a longer housing tenure are more likely to follow phased evacuation orders. “Evacuation keen” individuals with a longer travel delay expectation are more likely to comply with phased evacuation orders. This study not only unveiled the impacts of incorporating three psychological perceptions (i.e., risk, stakeholder, and evacuation perceptions) in modeling compliance behavior (e.g., parameter sign/significance shift) but also provides insights of evacuees’ compliance behavior to phased evacuation orders.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Evacuation and Crowd Dynamics · Disaster Management and Resilience · Traffic and Road Safety
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Louisiana Transportation Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA
Biden School of Public Policy & Administration, University of Delaware, Newark, DE 19716, USA
Department of Civil and Environmental Engineering, University of Missouri, Columbia, MO 65211, USA
Grado Department of Industrial and Systems Engineering, Virginia Tech, Falls Church, VA 22043, USA
Funding
National Science Foundation
References (84)
Show source-provided references
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