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Hristo Tanev, Vanni Zavarella, & Josef Steinberger. (2017). Monitoring disaster impact: detecting micro-events and eyewitness reports in mainstream and social media. 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. 592–602). Albi, France: Iscram.
Abstract: This paper approaches the problem of monitoring the impact of the disasters by mining web sources for the events, caused by these disasters. We refer to these disaster effects as “micro-events”. Micro-events typically following a large disaster include casualties, damage on infrastructures, vehicles, services and resource supply, as well as relief operations. We present natural language grammar learning algorithms which form the basis for building micro-event detection systems from data, with no or minor human intervention, and we show how they can be applied to mainstream news and social media for monitoring disaster impact. We also experimented with applying statistical classifiers to distill, from social media situational updates on disasters, eyewitness reports from directly affected people. Finally, we describe a Twitter mining robot, which integrates some of these monitoring techniques and is intended to serve as a multilingual content hub for enhancing situational awareness.
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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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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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Sofia Eleni Spatharioti, & Seth Cooper. (2017). On Variety, Complexity, and Engagement in Crowdsourced Disaster Response Tasks. 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. 489–498). Albi, France: Iscram.
Abstract: Crowdsourcing is used to enlist workers as a resource for a variety of applications, including disaster response. However, simple tasks such as image labeling often feel monotonous and lead to worker disengagement. This provides a challenge for designing successful crowdsourcing systems. Existing research in the design of work indicates that task variety is a key factor in worker motivation. Therefore, we asked Amazon Mechanical Turk workers to complete a series of disaster response related subtasks, consisting of either image labeling or locating photographed areas on a map. We varied the frequency at which workers encountered the dierent subtask types, and found that switching subtask type at dierent frequencies impacted measures of worker engagement. This indicates that a certain amount of variety in subtasks may engage crowdsourcing workers better than uniform subtask types.
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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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Philipp Schwarz, Yan Wang, Stephan Lukosch, & Heide Lukosch. (2017). Policy Gaming for Humanitarian Missions. 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. 814–823). Albi, France: Iscram.
Abstract: Aid workers increasingly face risks when working in crisis regions. In order to improve effectiveness and safety of humanitarians, it is of great importance to provide a well thought out real-time socio-technical support. Thus, new policies and innovative technological solutions need to be developed and integrated into humanitarian workflows. For the requirements elicitation process to realize this aspiration, we employ a board game approach that confronts players with situations aid workers experience in the field. From the first game session, we learned that the game is a valuable tool. It raises awareness to important challenges and trade-offs that humanitarians face. In addition, it is an effective catalyst for initiating a discussion on which system requirements are needed. Future work will include an update of the board game as well as sessions with the target group of practitioners to inform the development of a socio-technical system for humanitarian aid work.
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Alexander Gabriel, Simon Schleiner, Florian Brauner, Florian Steyer, Verena Gellenbeck, & Ompe Aimé Mudimu. (2017). Process modelling of physical and cyber terrorist attacks on networks of public transportation infrastructure. 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. 390–399). Albi, France: Iscram.
Abstract: Recent events have demonstrated the vulnerability of IT-systems of different companies, organisations or even governments to hacker attacks. Simultaneously, information technologies have become increasingly established and important for institutions of various branches. With respect to modern terrorism developments, cyber-attacks may be used to physically harm critical infrastructures. This leads to a new dimension of cyber-attacks called “terrorist cyber-attacks”. This research-in-progress paper aims to develop a process model for data acquisition and support of decision making that seeks to enhance the security of public transportation in the context of counterterrorism. Therefore, a generic process model for terrorist cyber-attacks – produced in the research project RE(H)STRAIN1 – is intro-duced as a basis for a decision support system (DSS). In the future, such models could improve the decision process by comparing the effectiveness of different security measures.
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Laura Petersen, Laure Fallou, Paul Reilly, & Elisa Serafinelli. (2017). Public expectations of social media use by critical infrastructure operators in crisis communication. 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. 522–531). Albi, France: Iscram.
Abstract: Previous research into the role of social media in crisis communication has tended to focus on how sites such as Twitter are used by emergency managers rather than other key stakeholders, such as critical infrastructure (CI) operators. This paper adds to this emergent field by empirically investigating public expectations of informatio provided by CI operators during crisis situations. It does so by drawing on key themes that emerged from a review of the literature on public expectations of disaster related information shared via social media, and presenting the results of an online questionnaire-based study of disaster-vulnerable communities in France, Norway, Portugal and Sweden. Results indicate that members of the public expect CI operators to provide disaster related information via traditional and social media and to respond to their queries on social media. CI operators should avail of the opportunities provided by social media to provide real-time information to disaster affected communities.
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Carolin Klonner, Melanie Eckle, Tomás Usón, & Bernhard Höfle. (2017). Quality Improvement of Remotely Volunteered Geographic Information via Country-Specific Mapping Instructions. 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. 939–947). Albi, France: Iscram.
Abstract: Volunteered geographic information can be seen as valuable data for various applications such as within disaster management. OpenStreetMap data, for example, are mainly contributed by remote mappers based on satellite imagery and have increasingly been implemented in response actions to various disasters. Yet, the quality often depends on the local and country-specific knowledge of the mappers, which is required for performing the mapping task. Hence, the question is raised whether there is a possibility to train remote mappers with country-specific mapping instructions in order to improve the quality of OpenStreetMap data. An experiment is conducted with Geography students to evaluate the effect of additional material that is provided in wiki format. Furthermore, a questionnaire is applied to collect participants' socio-demographic information, mapping experience and feedback about the material. This pre-study gives hints for future designs of country-specific mapping instructions as well as the experiment design itself.
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Binxu Zhai, & Jianguo Chen. (2017). Research on the forecasting of Air Quality Index (AQI) based on FS-GA-BPNN: A case study of Beijing, China. 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. 307–321). Albi, France: Iscram.
Abstract: The analysis and forecasting of eminent air quality play a significant role in municipal regulatory planning and emergency preparedness. In this paper, a FS-GA-BPNN model forecasting the daily average Air Quality Index (AQI) is proposed. Special procedures for feature extraction to find more potential significant variables and feature selection to remove redundant information and avoid overfitting are conducted before modelling. Three different models – BPNN, GA-BPNN and FS-GA-BPNN are established to compare the prediction accuracy, generalization ability and reliability. 17 parameters involving pollutant concentration, meteorological elements and surrounding factors are found essential for the method effectiveness. The result shows that the FS-GA-BPNN model generally performs superior to ordinary BPNN, suggesting the necessity of extensive data mining and feature extraction for successful machine learning. The results of this paper can help to conduct air quality pre-warning system and improve the emergency planning process of extreme weather events.
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Nicolas Serrano, Josune Hernantes, Tim A. Majchrzak, & Mihoko Sakurai. (2017). Resilience Information Portal. 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. 445–456). Albi, France: Iscram.
Abstract: The Smart Mature Resilience Project is a European research Project aimed at developing a Resilience Management Guideline. The guideline is composed of five tools developed in the project. They help to determine the level of resilience of a city and how to improve it. The Resilience Information Portal, one of these five tools, must support and integrate the different tools. It is also used as an engagement and communication tool. The tool had to be built before the finalization of the requirements, so a double approach was pursued in this project. First, a fast prototype was built based on a CMS, and second, a solution was built from scratch. The paper explains this process, compare both approaches, and how the long way can be more efficient. The final version has shown to be easy to use, and powerful enough to respond to the requirements of the users of the portal.
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Claire Laudy. (2017). Rumors detection on Social Media during 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. 623–632). Albi, France: Iscram.
Abstract: Social Media monitoring has become a major issue in crisis and emergencies management. Indeed, social media may ease the sharing of information between citizens and Public Safety Organizations, but it also enables the rapid spreading of inaccurate information. As information is now provided and shared by anyone to anyone, information credibility is a major issue. We propose an approach to detect rumor in social media. This paper describes our work on semantic graph based information fusion, enhanced with uncertainty management capabilities. The uncertainty management capability enables managing the dierent level of credibility of actors of an emergency (dierent PSO oÿcers and citizens). Functions for information synthesis, conflicting information detection and information evaluation were developed and test during experimentation campaigns. The synthesis and conflicting information detection functionalities are very welcome by end-users. However, the uncertainty management is a combinatorial approach which remains a limitation for use with large amount of information.
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Christian Reuter, Marc-André Kaufhold, & René Steinfort. (2017). Rumors, Fake News and Social Bots in Conflicts and Emergencies: Towards a Model for Believability in Social Media. 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. 583–591). Albi, France: Iscram.
Abstract: The use of social media is gaining more and more in importance in ordinary life, but also in conflicts and emer-gencies. The social big data, generated by users, is partially also used as a source for situation assessment, e.g. to receive pictures or to assess the general mood. However, the information's believability is hard to control and can deceive. Rumors, fake news and social bots are phenomenons that challenge the easy consumption of social media. To address this, our paper explores the believability of content in social media. Based on foundations of infor-mation quality we conducted a literature study to derive a three-level model for assessing believability. It summa-rizes existing assessment approaches, assessment criteria and related measures. On this basis, we describe several steps towards the development of an assessment approach that works across different types of social media.
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Ilona Heldal, & Cecilia Hammar Wijkmark. (2017). Simulations and Serious Games for Firefighter Training: Users' Perspective. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Informatin Systems for Crisis Response And Management (pp. 868–878). Albi, France: Iscram.
Abstract: Simulation and serious games (SSG) are advocated as promising technologies supporting training in emergency management (EM). Based on an investigation of SSG use for fire fighter training in nine countries, this paper is examining key elements and success factors that can counteract potential obstacles and challenges of SSG implementation. Data comes from interviews and observations with users and responsible managers from user organizations. By contrasting the different incentives and views regarding the SSG use, this paper contributes to a better understanding of SSG integration into organizational practices. Only by connecting the local, organizational strategies and user requirements with technical values and concrete examples can the SSG usage be experienced as successful. This connection requirement is by far not obvious since values are formulated differently by the main stakeholders and the benefits at one organization are not necessarily the same as at another. In this context, the added values of SSG solutions need to be more explicitly connected to the goals of traditional classroom and live training.
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B. Betting, E. Varea, & B. Patte-Rouland. (2017). Smoke dynamics in compartment fires: large scale experiments and numerical simulations. 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. 879–889). Albi, France: Iscram.
Abstract: Today, during compartments fire, the decision-making of the rescue teams is mainly based on human decisions, which are the results of gathered experiences. However, a perfect knowledge of the situation, its evolution over time and the dangers that may appear is impossible. The transition between a localized fire and a generalized fire can take several forms. One of the most important vectors in the propagation of combustion for compartment fires is smoke due to its high temperature and the large amounts of energy it contains. Despite its extreme danger, smoke remains important to study because it convey valuable information, especially on the appearance of thermal phenomena feared by firemen. To carry out this study, a large scale experimental cell is used. A burner fueled with propane produces hot fumes in a so-called “real fire” configuration. All the measurements carried out are compared with LES (Large Eddy Simulation) simulations of the experiment using FDS. The numerical component allows defining scenarios (fire fully developed, fire under ventilated ...), which are verified by the experiments. The dual competence numerical /experimental data is essential in this type of study since the experimental data suffer from a lack of resolution (spatial, temporal) but nevertheless represent information necessary for validating the codes.
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Mahshid Marbouti, Irene Mayor, Dianna Yim, & Frank Maurer. (2017). Social Media Analyst Responding Tool: A Visual Analytics Prototype to Identify Relevant Tweets in Emergency Events. 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. 572–582). Albi, France: Iscram.
Abstract: Public and humanitarian organizations monitor social media to extract useful information during emergencies. In this paper, we propose a new method for identifying situation awareness (SA) tweets for emergencies. We take a human centered design approach to developing a visual analytics prototype, SMA-RT (“Social Media Analyst Responding Tool”), informed by social media analysts and emergency practitioners. Our design offers insights into the main requirements of social media monitoring tools used for emergency purposes. It also highlights the role that human and technology can play together in such solutions. We embed a machine learning classifier to identify SA tweets in a visual interactive tool. Our classifier aggregates textual, social, location, and tone based features to increase precision and recall of SA tweets.
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Briony Gray, Mark J. Weal, & David Martin. (2017). Social Media during a Sustained Period of Crisis: The Case of the UK Storms. 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. 633–644). Albi, France: Iscram.
Abstract: This paper analyses the social media communications surrounding the 2015 – 2016 series of winter storms in the UK. Three storms were selected for analysis over a sustained period of time; these were storms Desmond, Eva and Frank which made landfall within quick succession of one another. In this case study we examine communications relating to multiple hazards which include flooding, evacuation and weather warnings using mainstream media content such as news stories, and online content such as Twitter data. Using a mixed method approach of content analysis combined with the application of a conceptual framework, we present (i.) the network of emergency responders managing events, (ii.) an analysis of crisis communications over time, and (iii.) highlight the barriers posed to effective social media communications during multi-hazard disasters. We conclude by assessing how these barriers may be lessened during prolonged periods of crisis.
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Louis Ngamassi, Abish Malik, Jiawei Zhang, & David Edbert. (2017). Social Media Visual Analytic Toolkits for Disaster Management: A Review of the Literature. 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. 785–797). Albi, France: Iscram.
Abstract: The past decade has seen a significant increase in the use of social media for disaster management. This is due especially to the widespread usage of mobile devices and also to the different data types and data formats that social media supports. In recent years, research in the area of social media visual analytics has also gained interest in the scientific community. Research in this area however, lacks a comprehensive overview on social media visual analytics for disaster management. Hence, this paper presents a synthesis of extant research on social media visual analytic and visualization toolkits for disaster management. We survey available literature on these tools with the goal to outline the major characteristics and features, and to examine the extent to which they cover the full cycle of disaster management. Our main purpose is to provide a foundation based on the current literature that can help to shape future research directions to enhance social media visual analytic tools for full cycle disaster management.
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Rob Grace, Jess Kropczynski, Scott Pezanowski, Shane Halse, Prasanna Umar, & Andrea Tapia. (2017). Social Triangulation: A new method to identify local citizens using social media and their local information curation behaviors. 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. 902–915). Albi, France: Iscram.
Abstract: Local citizens can use social media such as Twitter to share and receive critical information before, during, and after emergencies. However, standard methods of identifying local citizens on Twitter discover only a small proportion of local users in a geographic area. To better identify local citizens and their social media sources for local information, we explore the information infrastructure of a local community that is constituted prior to emergencies through the everyday social network curation of local citizens. We hypothesize that investigating social network ties among local organizations and their followers may be key to identifying local citizens and understanding their local information seeking behaviors. We describe Social Triangulation as a method to identify local citizens vis-à-vis the local organizations they follow on Twitter, and evaluate our hypothesis by analyzing users' profile location information. Lastly, we discuss how Social Triangulation might support community preparedness by informing emergency communications planning.
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Xiujuan Zhao, Graham Coates, & Wei Xu. (2017). Solving the earthquake disaster shelter location-allocation problem using optimization heuristics. 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. 50–62). Albi, France: Iscram.
Abstract: Earthquakes can cause significant disruption and devastation to populations of communities. Thus, in the event of an earthquake, it is necessary to have the right number of disaster shelters, with the appropriate capacity, in the right location in order to accommodate local communities. Mathematical models, allied with suitable optimization algorithms, have been used to determine the locations at which to construct disaster shelters and allocate the population to them. This paper compares the use of two optimization algorithms, namely a genetic algorithm and a modified particle swarm optimization, both of which have advantages and disadvantages when solving the disaster shelter location-allocation problem.
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Neda Mohammadi, John E. Taylor, & Ryan Pollyea. (2017). Spatiotemporal Dynamics of Public Response to Human-Induced Seismic Perturbations. 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. 666–672). Albi, France: Iscram.
Abstract: There is general consensus that subsurface wastewater injections associated with unconventional oil and gas operations are responsible for the rapid increase of earthquake activity in the mid-U.S. Understanding the public response to these earthquakes is crucial for policy decisions that govern developing situational awareness and addressing perceived risks. However, we lack sufficient information on the reactive and recovery response behavior of the public tending to occur in the spatiotemporal vicinity of these events. Here, we review the spatiotemporal distribution of public response to the September 3, 2016, M5.8 earthquake in Pawnee, Oklahoma, USA, via a social media network (Twitter). Our findings highlight a statistically significant correlation between the spatial and temporal distribution of public response; and suggest the possible presence of a spatial distance decay, as well as a temporal far-field eect. Understanding the underlying structure of these correlations is fundamental to establishing deliberate policy decisions and targeted response actions.
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Kouji Kishi, Naoko Kosaka, Tsuneko Kura, & Tomohiro Kokogawa. (2017). Study on Integrated Risk-Management Support System Application to Emergency Management for Cyber Incidents. 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. 432–444). Albi, France: Iscram.
Abstract: We have been studying the standardization of an emergency-management support system mainly for natural disasters at the local-government level. The system provides information from three viewpoints, “Plan: What should we do?”, “Do: What are we doing?”, and “See: What kind of situations are we in?” to support decision making at an emergency operations center. Rapid and accurate judgment prevents the occurrence of new damage and the expansion of damage, and as a result resilience will increase. We investigated its applicability to emergency management for cyber incidents through a cyber-defense exercise.
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Xiaodan Yu, & Deepak Khazanchi. (2017). Studying Virtual Teams during Organizational Crisis from a Sociomaterial Perspective. 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 (1055). Albi, France: Iscram.
Abstract: In this paper, we propose sociomaterialism as a theoretical lens for studying virtual team management during organizational crisis. In applying this lens, we propose the use of pattern theory as the method of choice for documenting effective practices for managing virtual teams in organizational crisis settings.
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Laura Laguna Salvadó, Matthieu Lauras, & Tina Comes. (2017). Sustainable Performance Measurement for Humanitarian Supply Chain Operations. 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. 775–783). Albi, France: Iscram.
Abstract: This paper proposes a performance measurement definition to consider sustainable development principles in the humanitarian supply chain operations (source, make, deliver). Previous research has shown the challenge for humanitarian organizations to consider the three sustainability pillars people, planet and profit in their decision-making processes. Based on field research with the International Federation of the Red Cross and Red Crescent (IFRC) and a literature review on humanitarian performance measurement and sustainability, we define a set of criteria, objectives and Key Performance Indicators that translates sustainability concepts to concrete humanitarian operations. Based on the Triple Bottom Line approach, the environmental and social dimensions are added to the economic dimension, which is standard in HSC literature and practice. The aim of this study is to set the basis for a Decision Support System (DSS) in operations planning.
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Samuel Lee Toepke. (2017). Temporal Sampling Implications for Crowd Sourced Population Estimations from Social Media. 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. 564–571). Albi, France: Iscram.
Abstract: Understanding the movements of a population throughout the 24-hour day is critical when directing disaster response in an urban area. An emergency situation can develop rapidly, and understanding the expected locations of groups of people is required for the success of first responders. Recent advances in modern consumer technologies have facilitated the generation, sharing and mining of an extensive amount of volunteered geographic information. Users leverage inexpensive smart devices, pervasive Internet connections and social media services to provide data about geospatial locations. Using an enterprise system, it is possible to aggregate this freely available, geospatially enabled data and create a population estimation with high spatiotemporal resolution, via a heat map. This investigation explores the effects of different temporal sampling periods when creating such estimations. Time periods are selected, estimations are generated for several large urban areas in the western United States, and comparisons of the results are shown/discussed.
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