The Role of Social Networks and Information Sources on Hurricane Evacuation Decision Making

Hurricanes often threaten to have catastrophic impacts on the lives of residents in coastal areas of the U.S. Timely evacuation limits this impact, but people may choose to evacuate or not during extreme weather conditions owing to differing personal environmental constraints that have little do with the direct risk. For example, during Hurricane Sandy a significant portion of New York and New Jersey residents facing potentially life-threatening storm-surge risk elected not to evacuate. In some cases, evacuation decisions are based solely on personal obligations and needs, yet they can often be influenced by the people with whom an individual is in contact. Previous sociological studies suggest that social networks serve the purpose of transmitting warning messages by disseminating information about an impending threat, and individuals having more social connections can be expected to receive more warning information. However, the empirical literature is inconclusive about how warnings received from social connections factor into evacuation-related decision making. This study uses novel social network data obtained from interviewing people from high-storm-surge-risk areas to understand evacuation responses during Hurricane Sandy. Individuals' egocentric social network information was obtained using the personal network research design approach. A mixed (random parameters) logit model of individual-level evacuation decision making is developed to explain the combined effects of individual, household, and social network characteristics, along with the reliability of different information sources within a unified modeling framework. This model will enable emergency managers and planners to better predict evacuation demand: the number of individuals evacuating to a safe destination during a major hurricane threat. Researchers exploring different dimensions of evacuation logistics (e.g.,departure time, destination, modal split, route choice) and simulations may also find this study informative.