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Jose Vargas Florez, Anthony Charles, Matthieu Lauras, & Lionel Dupont. (2014). Designing realistic scenarios for disaster management quantitative models. 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. 180–189). University Park, PA: The Pennsylvania State University.
Abstract: Disaster Management has received a lot of attention over the last twenty years, and can now be considered a full research area. But a gap exists between research work proposals and their applications on the field. This is particularly true regarding quantitative approaches. One of the main issues is that the scenarios used to design and validate the proposals are often not accurate and/or too simple compared to the complexity of real situations. Designing realistic scenarios is of prime importance to be able to propose relevant quantitative models which could be implemented by practitioners. This paper tackles this problem by proposing a structured methodology which aims at defining realistic disaster scenarios. The case of earthquakes management in Peru is used to illustrate the consistency of our proposal.
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Fabiana Santos Lima, Bernd Hellingrath, Adam Widera, & Mirian Buss Gonçalves. (2013). A systemic process model for procurement decisions in humanitarian logistics. 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. 688–692). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The relief organizations work in volatile environments involving a variety of actors with different skills and knowledge. The service of emergency for victims of natural disasters requires a rapid decision-making. The objective of the approach presented in this paper is to develop a Systemic Process Model (SPM) for procurement decisions in humanitarian logistics. The SPM aims to support procurement tasks of humanitarian organizations during the response phase in disaster relief. The approach provides a decision support tool using an appropriate quantitative model reflecting the specific area of humanitarian logistics processes.
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Elio Rich. (2006). Modeling risk dynamics in e-operations transitions. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 239–250). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Migrations to new modes of operation are perilous times for most organizations. For firms that routinely work in high-threat, high-reward situations, the risks of innovation are particularly challenging. This paper presents a systems-based approach to understanding these risks, drawing examples from one firm migrating to e-Operations for offshore oil platforms to increase profitability. The firm recently participated in two facilitated group model building exercises to examine the effects of the migration on the organization and resources needed to safely implement multiple changes over time. Based on these exercises, a simulation model of the timing and relative levels of risk, was developed. The results of the workshop and simulation demonstrate the effect of a combined qualitative and quantitative modeling approach to understanding complex problems.
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Christopher W. Zobel. (2013). Analytically comparing disaster recovery following the 2012 derecho. 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. 678–682). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This work in progress paper discusses analytically characterizing nonlinear recovery behavior through the context of the derecho windstorm that struck the mid-Atlantic United States in the summer of 2012. The focus is on the recovery efforts of the Appalachian Power Company, and the discussion includes a look at the need for communicating the progress of such recovery efforts to the public. Publicly available recovery data is analyzed and compared with respect to the relative behaviors exhibited by two different nonlinear recovery processes, and some of the implications for understanding the efficiency of different disaster recovery operations are discussed.
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