Identifying, Weighting and Causality Modeling of Social and Economic Barriers to Rapid Infrastructure Recovery from Natural Disasters: A Study of Hurricanes Harvey, Irma and Maria

United States national and economic security rest upon a foundation of highly interdependent critical infrastructures. However, Natural disasters, especially hurricanes, occur frequently in U.S. and yield significant and substantial damages to the critical infrastructures and regional communities. Many studies have focused on identifying disaster recovery indicators and reconstructing resilient communities. However, the social and economic barrier factors to rapid disaster reconstruction have been rarely investigated and studied. Therefore, this study will identify the social and economic barrier factors to the rapid post-disaster reconstruction, measure the impact weight of each of the identified social and economic recovery barrier variables, and develop and validate Causality model determining the relationship and interdependency preventive rapid post-disaster recovery variables. This study hypothesized that delay in the post disaster infrastructure rehabilitation and reconstruction will impose an exponential cascading effect on the economy of the affected coastal communities. To successfully achieve the three above mentioned objectives, this study will utilize triangulation technique, combining both qualitative and quantitative methods in research, and formulate the following five-step methodology: Literature Review, Qualitative Data Collection, Quantitative Data Collection, Impact Weighting Analysis, and Model development and validation. This study will create a weighted ranking list of dominant social and economic barrier factors in rapid infrastructure recovery from natural disasters, especially hurricanes, in coastal communities. Furthermore, this study will develop a causality model which determines the interdependency relationship of rapid recovery barrier factors and also calculates the economic impact of these factors on regional communities of the affected areas. The outcome of this study will direct and guide infrastructure policy makers to timely assess the recovery barrier factors and address the social and economic preventive factors based on their associated weight impacts.