Behavioral Model to Understand Household-Level Hurricane Evacuation Decision Making
Publication: Journal of Transportation Engineering
Volume 137, Issue 5
Abstract
Hurricanes are one of the most costly natural disasters in the United States and have increased in frequency in the last few years. The critical role of evacuation, particularly for the vulnerable communities, has been realized from some disastrous evacuation experiences in recent hurricanes (for example, Hurricanes Katrina and Rita in 2005). Therefore, a thorough understanding of the determinants of evacuation behavior is needed to protect the loss of lives, especially in the vulnerable communities. However, a household’s decision-making process under a hurricane risk is a very complex process influenced by many factors. This paper presents a model of household hurricane evacuation behavior accounting for households’ heterogeneous behavior in decision making by using original data from Hurricane Ivan. It develops a mixed logit (also known as random-parameters logit) model of hurricane evacuation decision, where random parameters reflect the heterogeneous responses of households caused by a hurricane. We report several factors consistent with some of the previous findings, which are important for understanding household-level evacuation decision making. We also explain the varied influences of some of the determining variables on the hurricane evacuation decision.
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Acknowledgments
This work was funded by the National Science Foundation Award NSFSES-0826874 “Incorporating Household Decision Making and Dynamic Transportation Modeling in Hurricane Evacuation: An Integrated Social Science-Engineering Approach,” for which the writers are grateful. However, the writers are solely responsible for the contents of the research work. The writers also acknowledge Prof. Fred Mannering of Purdue University for his suggestions on estimating marginal effect and two anonymous referees, who provided useful comments on an earlier draft of the paper. Particularly, the comments of one of the reviewers improved the paper significantly.
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Information
Published In
Journal of Transportation Engineering
Volume 137 • Issue 5 • May 2011
Pages: 341 - 348
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Mar 26, 2010
Accepted: Sep 21, 2010
Published online: Sep 23, 2010
Published in print: May 1, 2011
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