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Lennart Landsberg, Alexandra Braun, Ompe Aimé Mudimu, & Klaus-Dieter Büttgen. (2021). Considering end user needs when developing new technologies – a new plug and play sensor technology for locating trapped victims. 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. 922–928). Blacksburg, VA (USA): Virginia Tech.
Abstract: Building collapses often happen unexpectedly and suddenly. Consequently, people are often buried under the debris. What follows is a complicated search by first responders, which is characterized by time pressure and danger. In the research project SORTIE, a modular and UAV-based technical system is being developed to support the first responders in their search efforts. During the first phase of this project, an extensive requirements analysis was conducted with the involvement of end users. This ensures that the developed technology meets the requirements for later use under realistic circumstance. The project consortium has good experience with this operational approach and is in close cooperation with end users who are part of the consortium. In addition to a comprehensive understanding of building collapses and prevailing conditions, the technical partners were also able to identify requirements that they might not have discovered without the involvement of end users and the appropriate methods.
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Lida Huang, Guoray Cai, Hongyong Yuan, Jianguo Chen, Yan Wang, & Feng Sun. (2018). Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 121–134). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
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P. Lin, & S.M. Lo. (2005). The application of quickest flow problem in urban evacuation planning. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 129–130). Brussels: Royal Flemish Academy of Belgium.
Abstract: The provision of evacuation plan for people living in populated urban area is necessary to reduce the possible casualties under disasters. Time-varying quickest flow problem (TVQFP), which can simultaneously optimize the evacuation schedule, evacuation locations and evacuation routes, is adopted to optimize the evacuation planning of a city to minimize the clearance time of residents in danger. The integration of optimization model with GIS environment enables emergency managers to easily identify possible bottlenecks and to observe evacuation patterns in vivid pictures for further analysis and evaluation.
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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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Loïc Bidoux, Jean-Paul Pignon, & Frédérick Bénaben. (2017). On the use of automated planning for crisis management. 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. 996–1007). Albi, France: Iscram.
Abstract: Automated planning is a domain of Artificial Intelligence which aims to study the deliberation process used to choose and organize actions by anticipating their expected outcomes. In this paper, we discuss the use of automated planning techniques in crisis management contexts. To begin with, the crisis management planning problem is formalized in light of the conceptual model for automated planning. In addition, we describe the conceptual scheme of an information system generating action plans in order to support decision-makers in crisis management. Finally, a proof of concept implementation of the aforementioned system is presented.
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Ma Ma, Shengcheng Yuan, H. Zhang, & Yi Liu. (2013). Framework design for operational scenario-based emergency response system. 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. 332–337). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The present paper introduces a scenario-based framework design for connecting emergency response system with human behavior analysis and social information processing, which aims at improving its comprehensive capability in dealing with unexpected situations caused by physical, social and psychological factors during a crisis. The overall framework consists of four function modules: Scenario awareness, scenario analysis, scenario evolvement and scenario response. A detailed function design for each module is presented as well as the related methodologies used for integration of four modules. The contribution of this paper includes two aspects. One is realizing the integration of incident evolution, information-spreading and decision-making by taking account of physical, social and psychological effects during emergency. The other is improving the efficiency of decisionmaking through dynamic optimization process.
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Aamir Mahmood, Konstantinos Koufos, & Krisztina Cziner. (2008). Multicast voice performance within a public safety cell. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 18–24). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In public safety communications the first responders are getting directions about the tactical action plan with multicast voice whereas they can report back to the dispatcher with unicast voice. In this paper, the aim is to find the maximum number of voice calls for situation reporting in the presence of multicast voice for tactical coordination. In order to increase the reliability of our analysis we verify our simulator against a test bed prototype consisting of three 802.11 terminals. The simulation study is applied within a mobile cell. The proposed mobility model applies for initial deployment in emergency scenarios. We investigate the statistical properties of the model by simulations.
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Marcus Dombois, Timo Bittner, & Uwe Rüppel. (2018). Approaching the criticality of information for emergency response and control center operations. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 388–397). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Successful emergency response and control center operations rely on a great number of information sources. The importance of said information becomes immediately obvious if it is not available when required during an emergency situation. This can be described as the criticality of information, signifying a potential need for action to prepare for functional failures. The concept described in this paper approaches the criticality via an analysis that examines various combinations of information sources and situations in order to identify weaknesses and improve existing procedures. The proposed semi-quantitative assessment was developed taking several attributes and characteristics of criticality into account and afterwards conducted in close cooperation with emergency response institutions.
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Marian Zulean, Gabriela Prelipcean, & Costinel Anuta. (2016). Retrospective Analysis of the EU Resilience to a Large-Scale Migration. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The migration issue raises lots of questions regarding the resilience of the EU in front of such large-scale migration. This paper is the introductory part of larger research project that has in view to analyze the EU and some of the national strategic documents in order to detect when and how the migration as a security risk showed up and to clarify if it is a objective risk for EU security or it is just a tool of negotiation. The large-scale migration is a wicked problem that needs a foresight exercise not only to better understand the issue of migration but also to assess Emergency Preparedness of the EU and to prepare a long term strategy or scenarios, with regard to the way the current migration waves will impact the current European architecture. We propose to design a classical Delphi study, as basis for the above-mentioned exercise.
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Marion Lara Tan, Oshada Senaweera, Asanka Gunawardana, Mohamed Rasith, Mohamed Suaib, Theepika Shanthakumar, et al. (2023). New Zealand COVID Tracer App: Understanding Usage and User Sentiments. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 89–102). Palmerston North, New Zealand: Massey Unversity.
Abstract: The NZ COVID Tracer app is a part of Aotearoa New Zealand (NZ) Government’s strategy to manage the COVID-19 pandemic. This paper investigates people’s usage and sentiment on the app from its release in May 2020 to the end of 2021. Descriptive analysis of app data and sentiment analysis on user review data were used. The results show that before March 2021, the overall sentiment on the app was negative but gradually improved over time. The passive Bluetooth-tracing feature is utilised more consistently than the anual features. However, the increased proportion of positive sentiments is seen to increase with active app use. Results highlight the consistency of the Bluetooth-tracing feature but do not discredit the importance of manual interaction, as active use can improve the perception of the app. Insights from this study will be helpful as apps adapt to the changing context of the ongoing COVID-19 pandemic.
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Christoph Markmann, Heiko A. Von Der Gracht, Jonas Keller, & Rixa Kroehl. (2012). Collaborative foresight as a meansto face future risks – An innovative platform conception. 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: Increasing market volatility and disruptions imply risks for companies and governments and have become therefore focus topics. Adequate tools to identify, assess and manage future developments are key to survive in a turbulent environment. In our paper, we present the systematic development process of an innovative, web-based foresight platform, which is a joint research project funded by the German Federal Government and aims to improve the robustness in decision making by collaborative foresight. Its four interlinked applications have the purpose to enable their users a collaborative generation, discussion, evaluation and development of future-oriented knowledge. Thereby, a special emphasis is on the relevance and the timeliness of the provided information. Within the multi-stage requirement analysis of the tool platform we analyzed existing concepts in order to identify strengths and weaknesses and conducted brainstorming sessions and interviews with professionals of 130 companies and organizations to account for different backgrounds, perspectives and intentions. © 2012 ISCRAM.
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Marlen Hofmann, Hans Betke, & Stefan Sackmann. (2015). Automated Analysis and Adaptation of Disaster Response Processes with Place-Related Restrictions. 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: For recent years, disaster response management is considered as a promising field for applying methods and tools from business process management. Especially the development of adaptive workflow management systems (WfMS) brought a process-oriented management of highly dynamic disaster response processes (DRP) within tangible reach. However, time criticality, unpredictability or complex and changing disaster reality make it impossible to analyze and adapt ongoing DRP within reasonable time manually. Hence, to foster the application of disaster response WfMS in practice, it becomes mandatory to develop methods supporting an (semi-)automated analyses and adaption of ongoing DRP. Addressing this research gap, we present a novel method called DRP-ADAPT which analyzes given DRP models with respect to place-related conflicts and resolves inoperable response activities (semi-)automatically by process adaptation.
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Maude Arru, & Elsa Negre. (2017). People Behaviors in Crisis Situations: Three Modeling Propositions. 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. 139–149). Albi, France: Iscram.
Abstract: Warnings can help to prevent damages and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks. These systems have proved to be eective. Unfortunately, as all systems including human beings, a part of unpredictable remains. Indeed, each person behaves dierently when a problem arises. In this paper, we focus on people behaviors in crisis situations: from the definition of factors that impact human behavior to the integration of these behaviors, with three dierent modeling propositions, into a warning system in order to have more and more eÿcient crisis management systems.
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Kenny Meesters, & Bartel A. Van De Walle. (2013). Towards an impact evaluation framework for the collaborative information supply chain in humanitarian crisis response. 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. 536–545). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Emerging technologies provide opportunities for the humanitarian responders' community to enhance the effectiveness of their response to crisis situations. A part of this development can be contributed to a new type of information supply chains -driven by collaboration with digital, online communities- enabling organizations to make better informed decisions. However, how exactly and to what extend this collaboration impacts the decision making process is unknown. To improve these new information exchanges and the corresponding systems, an evaluation method is needed to assess the performance of these processes and systems. This paper builds on existing evaluation methods for information systems and design principles to propose such an impact evaluation framework. The proposed framework has been applied in a case study to demonstrate its potential to identify areas for further improvement in the (online) collaboration between information suppliers and users.
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Ulrich Meissen, Markus Hardt, & Agnès Voisard. (2014). Towards a general system design for community-centered crisis and emergency warning 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. 155–159). University Park, PA: The Pennsylvania State University.
Abstract: Early Warning Systems (EWS) provide an effective measure for better disaster preparedness, response, and mitigation. The effectiveness of EWS depends highly on the ability to distribute alert message to the persons that will be affected. In this context mobile devices play already a vital role in the ability to reach people in time and at the endangered location. Most existing approaches focus on mass dissemination methods via SMS and Cell-Broadcasting. As these approaches are effective to inform masses about a disaster with one message for all they have their weaknesses in telling the people how to respond according to their location and provide individual guidance (e.g. by maps) within specific communities. Research in disaster management gives strong evidence that the later is often crucial for better disaster response. Accordingly, we witness an increasing demand for more community-centered warnings systems solutions. This paper introduces the general foundations and architecture for alert services on mobile devices that adapt incoming alert information to the profile and situation of user groups and even individual users. The approach is scalable for different communitycentered warning systems. Its first applicability and community engagement effects are shown in the example of the community-centered public disaster alert system in Germany and a target group specific weather hazard alert system, KATWARN and WIND with currently over 2.5 million subscribed users, which was developed by the authors.
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Michele Angelaccio, & Daniele Pizziconi. (2008). Adaptive process coordination through mobile file sharing: A crisis management case study analysis. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 242–248). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes an ongoing project that exploits the capability of mobile sharing systems for ad-hoc wireless networks (MANET) operating in a post-emergency scenario. The aim is to support an existing adaptive process management in which users handle multimedia files (e.g. disaster photos) in a nomadic way by exploiting the capability offered by mobile file sharing middleware to reduce the connection time for each nomadic operator performing emergency workflow. The paper compares user activities with and without file sharing capability in order to show the efficiency gain that could be obtained. A preliminary discussion with example of activity diagrams evidences the benefits in terms of workflow efficiency and gives the opportunity in the software project development phase to obtain a more scalable and efficiently performing mobile adaptive process management for crisis scenarios.
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Miguel Ramirez de la Huerga, Victor A. Bañuls, & Murray Turoff. (2015). A Scenario-based approach for analyzing complex cascading effects in Operational Risk Management. 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: This is the first paper to apply Cross Impact Analysis (CIA) and Interpretative Structural Modeling (ISM) methods for analyzing complex cascading effects in Operational Risk Management in an industrial environment. Its main objective is to improve the understanding of the overall picture of an organization?s risks. The paper summarizes the development of a CIA-ISM method of the interaction of 18 critical events of an industrial plant as a first step to improving organizational resilience based on the company?s own estimations as well as the estimates of a panel. The main benefit of using these methods is to know the relationships between different risks and consequences, direct links, indirect and cascading effects. Having the possibility of knowing a full risk map and being able to make a forecast will help to mitigate the unexpected effects and have a better response after an emergency situations is the same as being more resilient.
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Miguel Ramirez de la Huerga, Victor A. Bañuls, Pilar Ortiz Calderon, & Rocio Ortiz Calderon. (2020). A Delphi-Based Approach for Analysing the Resilience Level of Local Goverments in a Regional Context. 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. 602–611). Blacksburg, VA (USA): Virginia Tech.
Abstract: This article shows the research process carried out by Regional Government of southern Europe, with more than 8 million citizens, to create an Information System to serve as a diagnostic and certification model for the resilience level of the municipalities of that region. This Information System will allow the local authorities of the regional governments to know in what situation they are and what they should do to improve their resilience level. The research framework is based on the best practices in urban resilience. One of the relevant characteristics of the work is the integration of the knowledge of a very heterogeneous group of experts for the identification of the special needs of the target region that has been articulated through a Delphi process.
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Monika Magnusson, Lars Nyberg, & Malin Wik. (2018). Information Systems for Disaster Management Training – Establishing User Needs with a Design Science Research Approach. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 841–850). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Societal threats such as global warming and terror attacks make crisis preparedness and crisis training a major priority in governments worldwide. Unfortunately, training is limited, partly due to complex and resource-demanding planning of traditional exercises. Several crisis training software have been developed as a complement. However, reports in research on their usage are rare, which indicates that the diffusion is limited. A potential explanation is that the systems fail to meet important needs in the organizations and/or sound information systems (IS) design principles. This paper describes the first phase of a design science research (DSR) project aiming at developing information systems for disaster management (ISDM) training, and accompanying training methods in local and regional governments. The purpose of this paper is to investigate perceived problems in current crisis training and identify opportunities for ISDM training in the application domain. Another purpose is to outline expected artifacts in the project.
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Sung Pil Moon, Yikun Liu, Steven O. Entezari, Afarin Pirzadeh, Andrew Pappas, & Mark Pfaff. (2013). Top health trends: An information visualization tool for awareness of local health trends. 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. 177–187). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We developed an intelligent information visualization tool to enable public health officials to detect healthrelated trends in any geographic area of interest, based on Twitter data. Monitoring emergent events such as natural disasters, disease outbreaks, and terrorism is vital for protecting public health. Our goal is to support situation awareness (SA) for personnel responsible for early detection and response to public health threats. To achieve this goal, our application identifies the most frequently tweeted illnesses in a ranked chart and map for a selected geographic area. Automated processes mine and filter health-related tweets, visualize changes in rankings over time, and present other keywords frequently associated with each illness. User-centered visualization techniques of monitoring, inspecting, exploring, comparing and forecasting supports all the three stages of SA. An evaluation conducted with experts in health-related domains provided significant insights about awareness of localized health trends and their practical use in their daily work.
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Murray Turoff, Victor A. Bañuls, Linda Plotnick, Starr Roxanne Hiltz, & Miguel Ramirez de la Huerga. (2015). Collaborative Evolution of a Dynamic Scenario Model for the Interaction of Critical Infrastructures. 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: This paper reviews current work on a model of the cascading effects of Critical Infrastructure (CI) failures during disasters. Based upon the contributions of 26 professionals, we have created a reliable model for the interaction among sixteen CIs. An internal CI model can be used as a core part of a number of larger models, each of which are tailored to a specific disaster in a specific location.
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Thomas Münzberg, Tim Müller, Stella Möhrle, Tina Comes, & Frank Schultmann. (2013). An integrated multi-criteria approach on vulnerability analysis in the context of load reduction. 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. 251–260). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Load reduction is an emergency measure to stabilize an electrical grid by decoupling some supply areas to balance the demand and supply of electricity in power grids. In the decoupled areas, power outages may cause important consequences, which may propagate further via the network of interdependent infrastructures. Therefore, support is needed to choose the regions to be decoupled. This paper describes an approach to analyze the risk triggered by load reduction that can be used for disaster management and load reduction scheme optimization. The core of our work is the vulnerability assessment that takes into account the consequences of load reduction on economy and society. The approach facilitates participatory decision support by making the vulnerability of regions especially in urban transparent.
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Thomas Münzberg, Ulrich Berbner, Tina Comes, Hanno Friedrich, Wendelin Groß, Hans-Christian Pfohl, et al. (2013). Decision support for critical infrastructure disruptions: An integrated approach to secure food supply. 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. 312–316). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Supplies of food and water are essential in disaster management, particularly in the very early chaotic phases when demand and available resources are highly uncertain, information systems are disrupted, and communication between communities, food suppliers, retail and emergency authorities is difficult. As many actors and organisations are involved in ever more complex food supply chains, cooperation and collaboration are vital for efficient and effective disaster management. To support decision-makers facing these problems, this paper introduces a scenario-based approach that integrates simulation of disruptions in food supply chains, and qualitative expert assessment to develop consistent scenarios that show the consequences of different strategies. To choose the best individual measures for all relevant actors and to compare it with the best overall strategy approaches from multi-criteria decision analysis are used.
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Nada Matta, Thomas Godard, Guillaume Delatour, Ludovic Blay, Franck Pouzet, & Audrey Senator. (2021). Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling. 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. 17–27). Blacksburg, VA (USA): Virginia Tech.
Abstract: Currently social media are largely used in interactions, especially in crisis situations. We note a big volume of interactions around events. Observing these interactions give information even to alert the existence of an incident, event, or to understand the expansion of a problem. Crisis management actors observe social media to be aware about this type of information in order to consider them in their decisions. Specific organizations are founded in order to observe social media interactions and send their analysis to rescue and crisis management actors. In our work, an experience feedback of this type of organizations (VISOV, a crisis social media analysis association) is capitalized in order to emphasize from one side, main dimensions of this analysis and from another side, to simulate some aspects using TextMining that help to explore big volume of data.
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Nathan Elrod, Pranav Mahajan, Monica Katragadda, Shane Halse, & Jess Kropczynski. (2021). An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic. 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. 345–358). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness.
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