A statistical analysis of the dynamics of household hurricane-evacuation decisions
Md Tawfiq Sarwar (),
Panagiotis Ch. Anastasopoulos (),
Satish V. Ukkusuri (),
Pamela Murray-Tuite () and
Fred L. Mannering ()
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Md Tawfiq Sarwar: University at Buffalo, The State University of New York
Panagiotis Ch. Anastasopoulos: University at Buffalo, The State University of New York
Satish V. Ukkusuri: Purdue University
Pamela Murray-Tuite: Virginia Tech
Fred L. Mannering: University of South Florida
Transportation, 2018, vol. 45, issue 1, 51-70
Abstract With the increasing number of hurricanes in the last decade, efficient and timely evacuation remains a significant concern. Households’ decisions to evacuate/stay and selection of departure time are complex phenomena. This study identifies the different factors that influence the decision making process, and if a household decides to evacuate, what affects the timing of the execution of that decision. While developing a random parameters binary logit model of the evacuate/stay decision, several factors, such as, socio-economic characteristics, actions by authority, and geographic location, have been considered along with the dynamic nature of the hurricane itself. In addition, taking the landfall as a base, how the evacuation timing varies, considering both the time-of-day and hours before landfall, has been analyzed rigorously. Influential factors in the joint model include the relative time until the hurricane’s landfall, height of the coastal flooding, and approaching speed of the hurricane; household’s geographic location (state); having more than one child in the household, vehicle ownership, and level of education; and type of evacuation notice received (voluntary or mandatory). Two time intervals from 30 to 42 h and 42 to 66 h before landfall resulted in random parameters, reflecting mixed effects on the likelihood to evacuate/stay. Possible sources of the unobserved heterogeneity captured by the random parameters include the respondents’ risk perception or other unobserved physiological and psychological factors associated with how respondents comprehend a hurricane threat. Thus, the model serves the purpose of estimating evacuation decision and timing simultaneously using the data of Hurricane Ivan.
Keywords: Emergency management; Dynamics of hurricane evacuation; Joint modeling of evacuation decision and timing; Unbalanced panel data; Random parameters; Binary logit model (search for similar items in EconPapers)
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