Catastrophic disaster represents a vital issue in emergency management for many countries in the European Union (EU) and around the world. Given the damage to human lives that different hazards represent, evacuation operations can be the only option available to emergency managers to mitigate the loss of life from catastrophic disaster. However, due to the amount of time needed to effectively evacuate a large area, the decision to evacuate must occur when there is a relatively low probability of the event. An explicit understanding of the evacuation decision can lead to better organisational preparedness in advance of catastrophic disaster events. This research represents work performed with 159 emergency experts and professionals across ten countries. The goal of this research was to create decision-making aids for evacuations in advance of a variety of catastrophic disaster scenarios. Traditional Decision Theory (DT) provides a rational approach to decision-making that emphasizes the optimization of subjective preferences combined with uncertainty. Within evacuation decision-making, DT and its respective outputs are appealing; however the analytical process can be difficult due to the lack of observed data to support quantitative assessments from catastrophic events and relative infrequency of evacuation operations. This research explored the traditional use of DT applied to catastrophic evacuation scenarios. Theoretical contributions to DT and emergency management include: 1) identification of evacuation decision criteria, 2) inter-model analysis between decision structures called Influence Diagrams (IDs), 3) complete application of quantitative decision analysis to support evacuation decision-making and 4) multi-criteria analysis for evacuation vulnerability using spatial data. Important contributions from this work include:1) An analysis of evacuation criteria for a variety of catastrophic disaster scenarios2) Inter-model analysis of evacuation scenarios (flooding, nuclear dispersion and terrorist attack) to identify common probabilistic structures to support multi-hazard strategy planning3) Quantitative decision models to support evacuation strategies, identify key uncertainties and policy analysis 4) Process to use spatial data to support multi-criteria evacuation vulnerability analysis 5) Organisational self-assessment for evacuation decision-making and spatial data use based on findings across all participating countries.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:593632 |
| Date | January 2012 |
| Creators | Kailiponi, Paul |
| Publisher | Aston University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://publications.aston.ac.uk/24381/ |
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