Tina Comes, Claudine Conrado, Michael Hiete, Michiel Kamermans, Gregor Pavlin, & Niek Wijngaards. (2010). An intelligent decision support system for decision making under uncertainty in distributed reasoning frameworks. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents an intelligent system facilitating better-informed decision making under severe uncertainty as found in emergency management. The construction of decision-relevant scenarios, being coherent and plausible descriptions of a situation and its future development, is used as a rationale for collecting, organizing, filtering and processing information for decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding time-consuming analysis and processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios, which was constructed using the best expertise available within a limited timeframe. Our theoretical framework is demonstrated in a distributed decision support system by orchestrating both automated systems and human experts into workflows tailored to each specific problem.
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Peter Otto, & Salvatore Belardo. (2006). A theoretical evaluation of information processing resources during organizational crisis. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 262–271). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The purpose of this paper is to present a model for testing different organizational learning characteristics and their effects on performance rate in times of an unexpected temporary increase in workload. Drawing on the theoretical frameworks of Yerkes-Dodson law, the stress-buffering effect of coping resources, and established crisis management models, the authors examine the hypotheses of curvilinear and interactional influence of single and double-loop learning on stress levels during crises. Using a simulation model, we identify thresholds in single and double-loop learning environments, where increases in workload lead to dysfunctional effects of stress. The findings indicate support for the hypothesis that an organization that employs double-loop learning is less susceptible to negative stress in times of a crisis. Overall, the study highlights the characteristics of different learning types and its effects on stress. It is suggested that experiments with a simulation model lead to a better understanding of how information processing resources that people have access to in stress events, buffers or protects them from negative effects.
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Martin Smits, & Bartel A. Van De Walle. (2006). A framework to evaluate how management games improve knowledge management effectiveness. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 605–614). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Knowledge-intensive organizations realize that 'knowledge' is a strategic resource that gives them sustainable competitive advantage and helps them achieve long-term organizational goals. These organizations use knowledge management (KM) to encourage the creation and sharing of knowledge resulting in improvements in productivity, innovation, competitiveness, and relationships among people. This paper investigates what role management games play in knowledge-intensive organizations and how they can be used to improve KM effectiveness. We present a theoretical framework that allows answering the following question: 'How can management games be used to improve the effectiveness of KM in knowledge-intensive organizations'.
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Simone Wurster, & Ulrich Meissen. (2014). Towards an economic assessment approach for early warning systems: Improving cost-avoidance calculations with regard to private households. 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. 439–443). University Park, PA: The Pennsylvania State University.
Abstract: In recent years, Early Warning Systems (EWS) have proven their value by saving many lives. However, most in-vestments into EWS were motivated directly by experienced disaster events and rarely pro-actively by possible up-coming threats. In order to change that we think that besides ethical and humanitarian reasons also the positive economic effects should be analyzed. EWS also help to protect property, but their contribution is not as obvious in that field due to the lack of quantitative models. This paper presents a disaster-independent formula that shows the benefits of EWS. Additional value to existing approaches is based on its advanced focus on behavioral aspects and the benefits of EWS in comparison to warnings issued via social media. We consider this work as an important contribution for future investments into warning technologies. However, yet this model just provides a theoretical framework for necessary empirical studies that are subject of further research.
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