Developing an inventory-based prioritization methodology for assessing inoperability and economic loss in interdependent sectors

Natural and man-caused disasters disrupt the production of commodities and services that are essential to the functions of infrastructure and economic sectors. The intrinsic interdependencies among these sectors trigger the propagation of disaster consequences that often result in a wider range of inoperability and amplified losses. This paper evaluates the impact of using inventory-enhanced policies on the recovery behavior among disrupted interdependent sectors. A dynamic inoperability input-output model (DIIM) is extended to identify the critical sectors based on two underlying minimization objectives, inoperability and economic loss. A dynamic cross prioritization plot (DCPP) is developed to integrate these objectives into a prioritization tool that allows variation in the importance associated with each objective. Implementing the methodology for the state of Virginia, a baseline inventory case revealed a high concentration of: (i) manufacturing sectors under the inoperability objective, and (ii) service sectors under the economic loss objective. Simulation of enhanced inventory policies to the manufacturing sectors reduced the recovery period by nearly a week and the total economic loss by $47.58M. The variation of importance attributed to the two objectives is demonstrated for the inventory-enhanced case. While the study focuses on enhancing inventory levels in Virginia´s manufacturing sectors, complementary analysis is recommended to manage the resilience of the service sectors. The flexibility and scalability of the proposed prioritization methodology and the resulting decision support system can also be extended to accommodate analysis in other regions as well as other disaster scenarios.