Estimating the Sequencing of Evacuation Destination and Accommodation Type in Hurricanes

Abstract Hurricanes are one of the most dangerous catastrophes faced by the USA. The associated life losses can be reduced by proper planning and estimation of evacuation demand by emergency planners. Traditional evacuation demand estimation involves a sequential process of estimating various decisions such as whether to evacuate or stay, evacuation destination, and accommodation type. The understanding of this sequence is not complete nor restricted to strict sequential ordering. For instance, it is not clear whether the evacuation destination decision is made before the accommodation type decision, or the accommodation type decision is made first or both are simultaneously made. In this paper, we develop a nested logit model to predict the relative ordering of evacuation destination and accommodation type that considers both sequential and simultaneous decision making. Household survey data from Hurricane Matthew is used for computing empirical results. Empirical results underscore the importance of developing a nested structure among various outcomes. In addition to variables related to risk perception and household characteristics, it is found that social networks also affect this decision-making process.