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Louise K. Comfort, Brian A. Chalfant, Jee Eun Song, Mengyao Chen, & Brian Colella. (2014). Managing information processes in disaster events: The impact of superstorm sandy on business organizations. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 230–239). University Park, PA: The Pennsylvania State University.
Abstract: Building community resilience to natural disasters represents a major policy priority for the United States as hazards impact vulnerable urban regions with increasing frequency and severity. Applying network analysis techniques, we examine the dynamics of emergency response to Superstorm Sandy, which struck the United States east coast in late October 2012 and caused over $72 billion in damages. Drawing on a variety of data sources and analytical techniques, we document the storm's impact on a system of interacting private, public, and nonprofit organizations. We find that the storm's response network exhibited clear patterns of information gaps and flows among different types of organizations. Our findings suggest a general lack of communication between government agencies and businesses, an area of potential improvement in future regional-scale emergency response systems.
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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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Louise K. Comfort, Brian Colella, Mark Voortman, Scott Connelly, Jill L. Drury, Gary L. Klein, et al. (2013). Real-time decision making in urgent events: Modeling options for action. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 571–580). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Decision making in extreme events presents a difficult challenge to emergency managers who are legally responsible for protecting life, property, and maintaining continuity of operations for their respective organizations or communities. Prior research has identified the benefits of gaining situation awareness in rapidly changing disaster contexts, but situation awareness is not always sufficient. We have investigated “option awareness” and the decision space to provide cognitive support for emergency managers to simulate computationally possible outcomes of different options before they make a decision. Employing a user-centered design process, we developed a computational model that rapidly generates ranges of likely outcomes for different options and displays them visually through a prototype decision-space interface that allows rapid comparison of the options. Feedback from emergency managers suggests that decision spaces may enable emergency managers to consider a wider range of options for decisions and may facilitate more targeted, effective decision making under uncertain conditions.
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