Gertraud Peinel, Thomas Rose, & Elmar Berger. (2007). Process-oriented risk management for smaller municipalities. 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. 405–410). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Project ERMA (Electronic Risk Management Architecture) develops a platform for risk managers that can be cus-tomised to individual risk management scenarios in order to meet the needs of small and medium-sized municipali-ties. Due to their limited resources, smaller boroughs call for flexible and intelligent platforms that can be tailored to a set of risk management scenarios that might range from natural disasters to man-made hazards. This paper will promote a process-oriented stance for supporting emergency management operations. The scope of services ranges from decision support via key-indicators with attached process management system up-to alarming services that incorporate citizen relationship management services to keep the citizen well informed and use him for the capture of additional information.
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Linda Plotnick, Elizabeth Avery Gomez, Connie White, & Murray Turoff. (2007). Furthering development of a unified emergency scale using Thurstone's Law of Comparative Judgment: A progress report. 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. 411–418). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In disasters, local civilians on or near the scene, are often first to respond and give aid. Therefore, the public needs to be well-informed with accurate, time critical information. However, a primary information source is event-specific scales that are inconsistent in their categorization and measurement, adding confusion to public responsiveness. These scales are not extendable to new emergencies in a changing world. We argue for development of a unified emergency scale to facilitate communication and understanding. This scale will inform local communities with regional community-specific information, and will be extendable for further use by professional responders. Research in progress elicited 15 dimensions of an emergency using a Delphi-like process and then ranked the dimensions by importance utilizing Thurstone's Law of Comparative Judgment. Contributions of this paper are to highlight the need for an unequivocal, unified scale and further its development.
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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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