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Tina Comes, Niek Wijngaards, & Frank Schultmann. (2012). Efficient scenario updating in emergency management. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Emergency managers need to assess, combine and process large volumes of information with varying degrees of (un)certainty. To keep track of the uncertainties and to facilitate gaining an understanding of the situation, the information is combined into scenarios: stories about the situation and its development. As the situation evolves, typically more information becomes available and already acknowledged information is changed or revised. Meanwhile, decision-makers need to keep track of the scenarios including an assessment whether the infor-mation constituting the scenario is still valid and relevant for their purposes. Standard techniques to support sce-nario updating usually involve complete scenario re-construction. This is far too time-consuming in emergency management. Our approach uses a graph theoretical scenario formalisation to enable efficient scenario updating. MCDA techniques are employed to decide whether information changes are sufficiently important to warrant scenario updating. A brief analysis of the use-case demonstrates a large gain in efficiency. © 2012 ISCRAM.
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Ur?ka Demsar, Olga Patenková, & Kirsi Virrantaus. (2007). Centrality measures and vulnerability of spatial networks. 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. 201–209). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause most damage and disruption. This paper presents a preliminary study into how a graph theoretic structural analysis could be used for this purpose. Centrality measures are combined with a dual graph modelling approach in order to identify critical locations in a spatial network. The results of a case study on a street network of a small area in the city of Helsinki indicate that 'betweenness' is the most promising centrality measure for this purpose. Other measures and properties of graphs are under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks.
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Till Sahlmüller, & Bernd Hellingrath. (2022). Measuring the Resilience of Supply Chain Networks. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 55–67). Tarbes, France.
Abstract: With increasing supply chain complexity, it gets more likely that disruptions ripple through the supply chain network, affecting supply chain performance. As the severity of disruptions depends on the supply chain network structure, it is important to assess the network structure in terms of its resilience. This article presents the results of a literature review (LR) to provide a comprehensive overview of measures used for evaluating the resilience of supply chain networks. The results indicate a wide range of measures applied in literature, focusing on either nodes, paths, or subgraphs of the network. The identified measures are compared regarding the structural characteristics they study and the aspects of supply chain performance they investigate.
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