Towards Modelling of Evacuation Behavior and Planning for Emergency Logistics Due to the Philippine Taal Volcanic Eruption in 2020

Emergency evacuation is the immediate escape of people away from a place of an imminent threat to a place of safety. The ability of the households to evacuate is a crucial component in reducing disaster risk. Logistical issues such as a lack of resources during and after the evacuation, as well as road congestion, might arise, especially in short and no-notice calamities such as a volcanic eruption. This study examines the relationship of variables of evacuation logistics of Barangay Banga, Talisay, Batangas in the context of the 2020 Taal Volcanic eruption. A survey was conducted based on the experience of the households during the volcanic eruption. A descriptive statistical analysis was performed for all the variables on household evacuation logistics to understand the behavior of households as they make decisions during emergencies. These variables include the type of evacuation, departure timing, evacuation mode choice, and destination choice. Additionally, a pairwise correlation was employed to identify the influential factors related to household evacuation logistics such as socio-demographic and household characteristics, hazard-related factors as well as their experience with Taal Volcano’s recurring activities. The results of this study aim to provide insights to a better understanding of the evacuation behavior of households in the context of a volcanic eruption and be useful in the evacuation logistics planning of the country.

Studying the Role of Personality Traits on the Evacuation Choice Behavior Pattern in Urban Road Network in Different Severity Scales of Natural Disaster

The study of evacuation behavior in response to disaster is necessary for emergency traffic management. As decision-making is not exclusively dependent on observable variables, in this research, it is attempted to study the evacuation choice behavior pattern in emergency response to earthquake disaster by considering both physical and behavioral factors. Personality traits are measured as behavioral latent factors by confirmatory factor analysis (CFA) of the short form of NEO-Five-Factor Inventory (NEO-FFI). A revealed preference survey with more than 700 samples was conducted in Qazvin city (Iran) which was based on real-life earthquake experience and the stated preference survey was conducted for six designated scenarios with different severities and times of earthquakes. Analysis of evacuation behavior is conducted by 3 types of discrete choice models (traditional binary logit model (TBLM), hybrid binary logit model (HBLM), and random parameters/mixed binary logit model (MBLM)). First, TBLM is estimated to study the effect of observable variables on response of people to earthquake disaster. Then, by adding the personality traits to modeling structure and constructing HBLM, the correct prediction percentage of the model increased. This study also considers heterogeneous mixtures of population in terms of income, family size, and five factors of personality traits by MBLM. The MBLM captures the heterogeneous responses of the respondent. By considering these variables as random parameters, the Log Likelihood function and pseudo square (ρ2) of the model increased.

Regional differences in cognitive dissonance in evacuation behavior at the time of the 2011 Japan earthquake and tsunami

This paper constructs an evacuation decision-making model that takes cognitive dissonance into consideration. The purpose of this construction is to clarify the psychological mechanism for the evacuation behavior of residents during an emergency, based on Akerlof and Dickens (Akerlof and Dickens Am Econ Rev 72:307–319, 1982) "The economic consequences of cognitive dissonance". Specifically, we empirically explore people’s psychological mechanism (e.g., cognitive dissonance) for evacuation behavior when a tsunami disaster occurs. As a result, we show that the level of anxiety depends on the area where residents live and that the average anxiety of residents is mostly correlated with the level of damage of past disasters, and that it is affected also by the ages of residents. Since the level of anxiety largely affects an individual’s evacuation behavior, this result can indicate for what kinds of people intervention and assistance are required based on the level of anxiety. A high level of anxiety basically promotes evacuation. Since our results show that anxiety is increased by the experience of tsunamis, education having people virtually experience tsunamis may increase evacuation rates efficiently.

Evacuation Behavior in a Subway Train Emergency: A Video-based Analysis

How do people behave in the seconds after they become aware they have been caught up in a real-life transport emergency? This paper presents the first micro-behavioral, video-based analysis of the behavior of passengers during a small explosion and subsequent fire on a subway train. We analyzed the behavior of 40 passengers present in the same carriage as the explosion. We documented the first action of the passengers following the onset of the emergency and described evidence of pro- and anti-social behavior. Passengers’ first actions varied widely. Moreover, anti-social behavior was rare and displays of pro-sociality were more common. In a quantitative analysis, we examined spatial clustering of running behavior and patterns in passenger exit choices. We found both homogeneity and heterogeneity in the running behavior and exiting choices of passengers. We discuss the implications of these findings for the mass emergency literature and for evacuation modeling.