Measuring the Measure: A Multi-dimensional Scale Model to Measure Community Disaster Resilience in the U.S. Gulf Coast Region

Over the past decades, coastal areas in the United States have experienced exponential increases in economic losses due to flooding, hurricanes, and tropical storms. This in part is due to increasing concentrations of human populations in high-risk coastal areas. Although significant progress has been made in developing mitigation measures to reduce losses in these areas, economic losses have continued to mount. The increase in losses has led to a significant change in hazard research by putting more emphasis on disaster resilience. While there has been a growing interest in the concept of disaster resilience, to date there is little or no empirical research that has focused on systematically measuring this concept. Therefore, the main objective of this dissertation was to develop a theoretically-driven index that can be used to measure disaster resilience in coastal communities. This dissertation argues that a comprehensive measure of disaster resilience should address issues of relevance to all phases of disaster: mitigation, preparedness, response, and recovery. Furthermore, a fruitful approach to measure disaster resilience is to assess various forms of capital: social, economic, physical, and human. These capitals are important resources for communities to successfully perform disaster phases' activities. A conceptual model based on disaster phases' activities and community capitals was developed in which indicators for measuring disaster resilience were identified. The model was utilized by first identifying activities relevant to each disaster phase and then specifically identifying indicators from each form of capital that might be important for carrying out those activities. The selected indicators were aggregated and a composite index score was calculated using average method which is based on equal weighting. The reliability and validity of the index were assessed using Cronbach's alpha, regression analysis, and GIS techniques. The results provided convincing empirical evidence that the index is a valid and reliable measure. The application of the measure indicated that disaster resilience is an important predictor of flood property damage and flood related deaths in the U.S. Gulf coast region. Also, the findings indicated that Florida counties are the most resilient whereas counties along the Texas-Mexico border region are the least resilient.