Inoperability input‐output modeling of disruptions to interdependent economic systems

In this study, the Inoperability Input‐Output Model (IIM) is deployed for assessing the impacts of disruptive events on interconnected economic systems. The IIM is based on Wassily Leontief's input‐output model which is capable of describing the ripple effects of disruptions to interdependent systems. Besides describing economic impact in financial terms, the “inoperability” metric is also used in the IIM to quantify the percentage of a system's production that is affected relative to the desired level. To analyze the magnitude and extent of system linkages, an interdependency matrix based on the North American Industry Classification System (NAICS) is constructed. The study highlights four key features of the IIM. First, demand patterns in the aftermath of such events are modeled and analyzed using available sector‐based performance data. Second, the NAICS‐based capital flow data released for the first time in 2003 by the US Bureau of Economic Analysis enable applying a dynamic IIM to describe the temporal behavior of economic impacts associated with disruptive events. Third, a discussion on utilizing other sources of data, such as consumer confidence for forecasting system‐specific demand disruptions, is presented. Fourth, a visualization tool is presented for conducting a multi‐criteria ranking of the most‐affected systems using both economic loss and inoperability metrics. Ultimately, the study offers insights on describing the sensitivity of economic systems to various classes of disruptions. In the broader perspective, this can provide guidance toward policymaking activities.