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Toshihisa Toyoda. (2008). Economic impacts of Kobe Earthquake: A quantitative evaluation after 13 years. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 606–617). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The importance of distinguishing between direct and indirect losses of disasters is stressed. In order to estimate indirect losses, a conceptual framework of direct and indirect losses is presented. For the case of the Great Hanshin-Awaji (Kobe) Earthquake of 1995, direct stock losses of both the manufacturing and the commercial sectors record almost same size of big damage. As for indirect flow losses, the commercial and the other services sectors show far greater damage than the manufacturing sector. A careful statistical analysis of indirect losses using the gross regional product in the stricken area presents a new finding that the lost product and income in terms of estimated indirect losses are quite large and continue to arise for longer than 10 years, mounting to some 14 trillion yen (about US$0.13 trillion). Disaster management policy should be improved by paying attention not only to direct losses but also to indirect losses.
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Sarp Yeletaysi, Frank Fiedrich, & John R. Harrald. (2008). A framework for integrating GIS and systems simulation to analyze operational continuity of the petroleum supply chain. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 586–595). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Crisis and disaster management is a field that requires the understanding and application of tools and knowledge from multiple disciplines. Hurricanes Katrina and Rita in 2005 have proven that U.S. petroleum infrastructure is vulnerable to major supply disruptions as a direct result of disasters. Due to the structure of U.S. oil supply chain, primary oil production centers (i.e. PADD* 3) are geographically separated from primary demand centers (i.e. PADD 1), which creates a natural dependency between those districts. To better understand the extent of those dependencies and downstream impacts of supply disruptions, a multi-disciplinary research approach is necessary. The cross-disciplines in this research include disaster management, critical infrastructure and oil supply chain management, and the utilization of geographic information systems (GIS) and systems simulation. This paper specifically focuses on the framework for integrating GIS and systems simulation as analysis tools in this research.
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Mauro Falasca, Christopher W. Zobel, & Deborah Cook. (2008). A decision support framework to assess supply chain resilience. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 596–605). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Our research is aimed at developing a quantitative approach for assessing supply chain resilience to disasters, a topic that has been discussed primarily in a qualitative manner in the literature. For this purpose, we propose a simulation-based framework that incorporates concepts of resilience into the process of supply chain design. In this context, resilience is defined as the ability of a supply chain system to reduce the probabilities of disruptions, to reduce the consequences of those disruptions, and to reduce the time to recover normal performance. The decision framework incorporates three determinants of supply chain resilience (density, complexity, and node criticality) and discusses their relationship to the occurrence of disruptions, to the impacts of those disruptions on the performance of a supply chain system and to the time needed for recovery. Different preliminary strategies for evaluating supply chain resilience to disasters are identified, and directions for future research are discussed.
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Louise K. Comfort, Milos Hauskrecht, & Jeen-Shang Lin. (2008). Dynamic networks: Modeling change in environments exposed to risk. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 576–585). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Modeling the interaction between interdependent systems in dynamic environments represents a promising approach to enabling communities to assess and manage the recurring risk to which they are exposed. We frame the problem as a complex, adaptive system, examining the interaction between transportation and emergency response as a socio-technical system. Using methods of spatial and statistical analysis, we overlaid the engineered transportation system on the organizational emergency response system to identify the thresholds of fragility in each. We present a research design and preliminary results from a small-scale study conducted in the Pittsburgh Metropolitan Region that examined the interaction between the transportation and emergency response systems. These results informed the design of a Situational Assessment Module for emergency managers, currently under development at the University of Pittsburgh.
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