Uncertainty analysis of rework predictors in post-hurricane reconstruction of critical transportation infrastructure

The aims of this study are to identify the factors that contribute to occurrence of reworks in the reconstruction of transportation infrastructure following hurricanes, develop a model for predicting the costs associated with these reworks. In addition, this study determined the robustness and fragility of each rework predictor. Therefore, the stepwise multiple regression and extreme bound analysis (EBA) methods were adopted. The results demonstrated that the influential predictors are distance from highly-populated areas, shortage of laborers, logistics management, frequency of inspections, information management, coordination, environmental/safety issues, work suspensions, regulatory requirements, and temporary pathways. The outcomes provide accurate information that will be helpful in preventing/mitigating the cost of reworks in reconstruction of transport infrastructure.