Valentin Bertsch, Otto Rentz, & Jutta Geldermann. (2007). Preference elicitation and sensitivity analysis in multi-criteria group decision support for nuclear remediation management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 395–404). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The resolution of complex decision situations in crisis and remediation management following a man-made or natural emergency usually requires input from different disciplines and fields of expertise. Contributing to transparency and traceability of decisions and taking subjective preferences into account, multi-criteria decision analysis (MCDA) is suitable to involve various stakeholder and expert groups in the decision making process who may have diverse background knowledge and different views, responsibilities and interests. The focus of this paper is to highlight the role of MCDA in nuclear emergency and remediation management on the basis of a hypothetical case study. Special emphasis is placed on the modelling of the decision makers' preferences. The aim is to explore the sensitivity of decision processes to simultaneous variations of the subjective preference parameters and consequently to contribute to a facilitation of the preference modelling process by comprehensibly visualising and communicating the impact of the preferential uncertainties on the results of the decision analysis.
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Simone De Kleermaeker, & Jan Verkade. (2013). A decision support system for effective use of probability forecasts. 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. 290–295). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined.
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Michael K. Lindell. (2011). Evacuation modelling: Algorithms, assumptions, and data. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Survey researchers need to, Find out what assumptions evacuation modelers are making and collect empirical data to replace incorrect assumptions;, Obtain data on the costs of evacuation to households, businesses, and local government; and, Extend their analyses to address the logistics of evacuation and the process of re-entry. Evacuation modelers need to, Incorporate available empirical data on household evacuation behavior, and, Generate estimates of the uncertainties in their analyses. Cognitive scientists need to, Conduct experiments on hurricane tracking and evacuation decision making to better understand these processes, and, Develop training programs, information displays, and performance aids to assist local officials who have little or no previous experience in hurricane evacuation decision making.
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