A data-driven framework to evaluate the indirect economic impacts of transportation infrastructure disruptions

Transportation systems are critical to the sustainable development and economic vitality of cities. However, they are vulnerable to disruptions that can result from natural and man-made disasters as well as maintenance activities that may require temporary closure of road segments. Previous research indicated that transportation disruptions can cause not only significant direct economic losses, but also substantial indirect impacts, which are difficult to analyze and quantify. The comprehensive estimation of the indirect economic impacts calls for interdisciplinary research frameworks. This study introduces a new analytical framework for estimating the indirect economic impacts that are caused by various direct effects of transportation disruptions, including building and content losses, business interruptions, freight flow perturbations, and passenger flow perturbations. One of the state-of-the-art Computable General Equilibrium (CGE) models, the TERM model, is leveraged to calculate the indirect economic impacts, fed with information on transportation disruptions generated by explicit transportation network models through a series of well-built model linkages. These linkages are set based on a thorough investigation of the potential indirect impacts due to transportation disruptions. Besides, critical data that are required to achieve a comprehensive and accurate estimation of the indirect economic impacts are identified. Potential double counting issues related to the implementation of the framework and mitigation solutions are discussed. To deploy the framework, a case study of a hypothetical earthquake scenario in the Greater Los Angeles Area was conducted. The indirect economic impacts of transportation disruptions caused by earthquake-induced bridge damages were estimated and analyzed. Simulation results indicated that millions of dollars could be lost in this case due to road transportation network disruptions, and the geographical distribution of those losses could be quantified. This study lays a foundation for further interdisciplinary research on the integration of transportation system analyses with economic models.