| description abstract | A supply driven dynamic input-output inoperability model (SDIIM), which extends the classical dynamic inoperability input-output model (DIIM), is described in this paper. The classical DIIM was developed to help understand the infrastructure interdependencies of deliberate external attacks or unfortunate natural disasters, such as terrorist attacks or earthquakes and flooding. However, classical DIIM is a demand-driven model. More supply driven sectors exist than demand-driven sectors in interdependent infrastructure systems, but value-added perturbation is the predominant feature in supply driven sectors for an interrupt event. Moreover, compared to classical DIIM, the value added by the proposed SDIIM can be controlled more easily than the final demand of a disruptive event because the final demand perturbation may be affected by the psychological effect on consumers. A supply driven input-output inoperability model (IIM) has also been proposed to complement the classical IIM. However, the supply driven IIM is a static model, and only equilibrium values can be determined. The SDIIM presented in this paper has been formulated to model the behavior of the value-added input perturbation up to equilibrium and to characterize the required sector adjustments for achieving new levels of output values. In addition, the interdependency resilience coefficient and the interdependency index are discussed by using the SDIIM. In this paper, the large-scale snow disaster that occurred in south China in 2008 is used as a case study, in which the SDIIM is used to analyze the inoperability and dynamic output values recovery of sectors caused by a value-added disturbance. The SDIIM is shown to effectively compute interdependent inoperability and economic losses, which can provide valuable insights into risk assessment and the management of interdependent infrastructure systems and sectors of the economy. | |
