Andreas Lotter, Florian Brauner, Alexander Gabriel, Frank Fiedrich, & Stefan Martini. (2017). New Decision-Support Framework for Strengthening Disaster Resilience in Cross-Border Areas. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 412–419). Albi, France: Iscram.
Abstract: The improvement of disaster resilience in cross-border areas causes special challenges. Involved countries use different structures in their civil protection systems and have to work together facing more difficult conditions than in local incidents. Furthermore, in the past involved countries mainly worked individually and focused on the concerned areas in their territories regardless transnational activities. The project INCA will develop a resilience framework to support decision-makers. The framework will focus on information management, the implementation of volunteers and the needs of citizens who are receiving medical care. Therefore, a case study region on the German-French border was defined and a scenario-based approach will be used to investigate resilience opportunities through disaster collaboration. The tested scenario is a transnational long-lasting power-outage in the German-French region.
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Tina Comes, & Bartel A. Van De Walle. (2014). Measuring disaster resilience: The impact of hurricane sandy on critical infrastructure systems. 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. 195–204). University Park, PA: The Pennsylvania State University.
Abstract: Modern critical infrastructure (CI) systems are tightly coupled, resulting in unprecedented complexity and difficulty to predict, limit and control the consequences of disruptions caused by hazards. Therefore, a paradigm shift in disaster risk management is needed: instead of focusing on predicting events, resilience needs to be improved as a basis for adequate response to any event. This paper starts from a definition of CI resilience that provides a basis for quantitative and qualitative decision support. For the quantitative modelling approach, which aims at measuring the resilience of individual CIs, we focus on two CIs of fundamental importance for disaster response: transportation and power supply. The qualitative framework details relations between CIs. The results of this research are illustrated by a case study that analyses the impact of Hurricane Sandy. The findings highlight the need for a framework that combines qualitative and quantitative information from heterogeneous sources to improve disaster resilience.
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Hussain A. Syed, Marén Schorch, & Volkmar Pipek. (2020). Disaster Learning Aid: A Chatbot Centric Approach for Improved Organizational Disaster Resilience. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 448–457). Blacksburg, VA (USA): Virginia Tech.
Abstract: The increasingly frequent occurrence of organizational crises exemplifies the need to strengthen organizational resilience. An example of business organizations is small and medium enterprises (SMEs) which contribute largely to the economic growth. But often, their limited resources (manpower, time, financial capital), organizational structure, focus on operational routines and less priority towards disaster resilience make them more vulnerable to crisis than bigger companies. The proposed solution addresses this dilemma by establishing a collaborative medium within the organization to improve disaster resilience by raising awareness and self-learning in employees without overburdening their constrained routines and resources. Our work in progress demonstrates a conceptual model of a learning aid (collaboration channel and a chatbot) that supports the pedagogical methodologies and employs them for enhancing learnability and awareness and elaborates the usability of interactive learning instilling disaster resilience in employees and hence in an organization.
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Miriam Klein, Eric Rigaud, Marcus Wiens, Anouck Adrot, Frank Fiedrich, Nour Kanaan, et al. (2018). A Multi-Agent System for Studying Cross-Border Disaster Resilience. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 135–144). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Resilience to disasters depends on measures taken before, during and after the occurrence of adverse events. These measures require interactions between people belonging to different organizations (public, private, non-profit) and citizens in normal and stressful situations. The efficiency of resilience measures results from the collective interaction of individuals, groups of individuals, and organizations, as well as the situational characteristics of the decision environment. The aim of the French-German research project INCA is to develop a decision support framework for improving cross-border area resilience to disasters. This project comprises the design and the implementation of a multi-agent system with the objective to study the behavioral and organizational implications of cross-border cooperation for crisis management and disaster resilience. The analyzed measures focus on citizens who require medical support and the integration of volunteers into the crisis management procedure. This paper outlines the potentials of the multi-agent system and provides first implementation insights.
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Ramakrishnan, T., & Zou, L. (2023). Investigating the Role of Digital Divide and Social Media Use (SMU) to Improve Disaster Resilience in Vulnerable Communities. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (p. 1073). Omaha, USA: University of Nebraska at Omaha.
Abstract: Disasters are unexpected large-scale events accompanied by trauma, death, and destruction. Disaster resilience varies by location and can be significantly improved through effective management. Real-time information describing the on-site impacts of disasters plays an important role in managing disasters. Social media provides a convenient platform where users in disaster-affected areas can access disaster information, report local damages, and ask for assistance. However, a widespread spatially uneven flow in online activities requesting for food, shelter, and medical assistance among people in disaster-affected areas through social media is seen during any disaster. Digital divide Influences social media use. Before probing the social media data for inspecting the affected population and prioritizing the relief operations, the social inequality in the social media use has to be considered. In this study, we examine the role of digital divide and its influence in social media use with aim of improving disaster resilience in vulnerable communities.
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Restel, H. (2023). SimulationOps – Towards a Simulation as-a-Service Platform for Resilient Societies Using a Cross-domain Data Mesh. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 575–585). Omaha, USA: University of Nebraska at Omaha.
Abstract: Cross-domain simulations can be a feasible approach for enhancing disaster resilience as well as promoting resilient societies. This work-in-progress proposes a data-centric process model and software platform architecture called “SimulationOps” aimed at improving cross-domain collaboration between researchers (simulation analysts, simulation modelers) and stakeholders (disaster responders, decision makers) throughout the simulation life cycle for combined simulation artifacts. This way, stakeholders are supported in mitigating disasters, improving overall resilience by gained insights, and improvements in quality and velocity. Applying a four-cycle Design Science Research model to the simulation lifecycle, it combines ideas from modern and agile software engineering practices, simulation-as-a-service approach, and the Data Mesh approach. It combines the technical IT level with the organizational process level to smoothen the workflow for creating, running, and improving cross-domain computer simulation components for both producers as well as consumers of the simulation life cycle.
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Yan Wang, Qi Wang, & John Taylor. (2021). Loss of Resilience in Human Mobility across Severe Tropical Cyclones of Different Magnitudes. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 755–765). Blacksburg, VA (USA): Virginia Tech.
Abstract: Severe tropical cyclones impose threats on highly populated coastal urban areas, thereby, understanding and predicting human movements plays a critical role in evaluating disaster resilience of human society. However, limited research has focused on tropical cyclones and their influence on human mobility resilience. This preliminary study examined the strength and duration of human mobility perturbation across five significant tropical storms and their affected eight urban areas using Twitter data. The results suggest that tropical cyclones can significantly perturb human movements by changing travel frequencies and displacement probability distributions. While the power-law still best described the pattern of human movements, the changes in the radii of gyration were significant and resulted in perturbation and loss of resilience in human mobility. The findings deepen the understanding about human-environment interactions under extreme events, improve our ability to predict human movements using social media data, and help policymakers improve disaster evacuation and response.
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Yang Zhang, William Drake, Yuhong Li, Christopher Zobel, & Margaret Cowell. (2015). Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience.
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Christopher W. Zobel. (2010). Comparative visualization of predicted disaster resilience. 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: The disaster resilience triangle is a simple but effective tool for illustrating the relationship between the initial impact of a disaster event and the subsequent time to recovery. This tool can also be expanded, however, to provide an analytic measure of the level of resilience exhibited by a particular entity in a given disaster situation. We build upon the previous work in this area by developing a new approach for visualizing and analyzing the tradeoffs between the two primary defining characteristics of the disaster resilience triangle. This new approach supports strategic decision making in a disaster planning environment by providing a straightforward means for directly comparing the relative predicted resilience of different critical facilities within an organization, with respect to both location and type of risk.
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Christopher W. Zobel. (2011). Representing the multi-dimensional nature of disaster resilience. 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: Although quantitative analytical information systems are an important resource for supporting decision-making in disaster operations management, not all aspects of a disaster situation can be easily quantified. For example, although the concept of the disaster resilience of a community has a technical dimension within which one can measure the resistance of the infrastructure against, and the speed of its recovery from, a disaster event, it also has social, organizational, and economic dimensions within which these characteristics may be more difficult to measure. This work-in-progress paper introduces a quantitative framework within which the multi-dimensional nature of such disaster resilience can be represented in a concise manner. This can help to improve understanding of the complexities associated with the concept, and thus directly support decision-making in disaster operations planning and management.
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Christopher W. Zobel, Stanley E. Griffis, Steven A. Melnyk, & John R. MacDonald. (2012). Characterizing disaster resistance and recoveryusing outlier detection. 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: Most definitions of disaster resilience incorporate both the capacity to resist the initial impact of a disaster and the ability to recover after it occurs. Being able to characterize and analyze resilient behavior can lead to improved understanding not only of the capabilities of a given system, but also of the effectiveness of different strategies for improving its resiliency. This paper presents an approach for quantifying the transient behavior resulting from a disaster event in a way that allows researchers to not only describe the transient response but also assess the impact of various factors (both main and interaction effects) on this response. This new approach combines simulation modeling, time series analysis, and statistical outlier detection to differentiate between disaster resistance and disaster recovery. Following the introduction of the approach, the paper provides a preliminary look at its relationship to the existing concept of predicted disaster resilience. © 2012 ISCRAM.
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