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	Author	Cheng Wang; Benjamin Bowes; Arash Tavakoli; Stephen Adams; Jonathan Goodall; Peter Beling
	Title	Smart Stormwater Control Systems: A Reinforcement Learning Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	2-13
	Keywords	Reinforcement Learning, Stormwater, Flooding Control.
	Abstract	Flooding poses a significant and growing risk for many urban areas. Stormwater systems are typically used to control flooding, but are traditionally passive (i.e. have no controllable components). However, if stormwater systems are retrofitted with valves and pumps, policies for controlling them in real-time could be implemented to enhance system performance over a wider range of conditions than originally designed for. In this paper, we propose an autonomous, reinforcement learning (RL) based, stormwater control system that aims to minimize flooding during storms. With this approach, an optimal control policy can be learned by letting an RL agent interact with the system in response to received reward signals. In comparison with a set of static control rules, RL shows superior performance on a wide range of artificial storm events. This demonstrates RL's ability to learn control actions based on observation and interaction, a key benefit for dynamic and ever-changing urban areas.
	Address	Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-1	ISBN	2411-3387	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	cw8xk@virginia.edu			Approved	no
	Call Number				Serial	2202
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	Author	Nilani Algiriyage; Raj Prasanna; Emma E H Doyle; Kristin Stock; David Johnston
	Title	Traffic Flow Estimation based on Deep Learning for Emergency Traffic Management using CCTV Images			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	100-109
	Keywords	CCTV Big Data, YOLOv3, Traffic Flow Estimation.
	Abstract	Emergency Traffic Management (ETM) is one of the main problems in smart urban cities. This paper focuses on selecting an appropriate object detection model for identifying and counting vehicles from closed-circuit television (CCTV) images and then estimating traffic flow as the first step in a broader project. Therefore, a case is selected at one of the busiest roads in Christchurch, New Zealand. Two experiments were conducted in this research; 1) to evaluate the accuracy and speed of three famous object detection models namely faster R-CNN, mask R-CNN and YOLOv3 for the data set, 2) to estimate the traffic flow by counting the number of vehicles in each of the four classes such as car, bus, truck and motorcycle. A simple Region of Interest (ROI) heuristic algorithm is used to classify vehicle movement direction such as \quotes{left-lane} and \quotes{right-lane}. This paper presents the early results and discusses the next steps.
	Address	Joint Centre for Disaster Research, Massey University; Joint Centre for Disaster Research, Massey University; Joint Centre for Disaster Research, Massey University; Institute of Natural and Mathematical Sciences, Massey University; Joint Centre for Disaster Research, Massey University;
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-10	ISBN	2411-3396	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	r.nilani@massey.ac.nz			Approved	no
	Call Number				Serial	2211
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	Author	Hanne Haaland; Hege Wallevik; Erika Frydenlund; Jose J. Padilla
	Title	Modelers and Ethnographers as Co-Creators of Knowledge: Do We Belong Together?			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1113-1121
	Keywords	Social Sciences; Modeling; Interdisciplinarity; Citizen-Based Humanitarian Aid; Refugees; Lesvos; Citizen Initiatives for Global Solidarity (CIGS); Prototype Agent-Based Model
	Abstract	In this paper, we explore the process of co-creation of knowledge between modelers and ethnographers through a project focusing on the role played by CIGS (Citizen initiatives for global solidarity) in the refugee crisis in the island of Lesvos, Greece. We describe the process of collaboration and discuss what this type of interdisciplinary collaboration may bring to the development of a research topic when the initial skepticism and questions of epistemological differences have been overcome. Moreover, we address some of the challenges embedded in this type of research collaboration, particularly the skepticism present within the social sciences.
	Address	University of Agder, Norway; University of Agder, Norway; Old Dominion University, US; Old Dominion University, US
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-100	ISBN	2411-3486	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Hanne.haaland@uia.no			Approved	no
	Call Number				Serial	2301
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	Author	Anne-Marie Barthe-Delanoë; Wenxin Mu
	Title	Towards a Context-Aware Systemic Risk Management Framework for the Crisis Response			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1122-1129
	Keywords	Context-Awareness; Risk Analysis; Risk Evaluation; Knowledge Base; Systemic Risk
	Abstract	Crisis response is, as any other collaborative networked organization, challenged by changes and vulnerabilities. Moreover, as a complex system with distributed activities and numerous interdependencies, considering the risk of such an organization at a systemic level, including time and space dimensions, is necessary. Systemic risk management is a topic traditionally studied in the finance area. Even if a few researches now focus on the supply chain management area (a more relatable domain regarding crisis response), there is even fewer literature regarding systemic risk management for the crisis response. Thus, this paper proposes first to define systemic risk related to the case of the crisis response. Then, a framework for context-aware systemic risk management is presented, to support the design as well as the follow-up of the crisis response, meeting one of the challenges of the Sendai Framework for Disaster Risk Reduction.
	Address	Laboratoire de Génie Chimique, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France; Department of Information Management, Jiao Tong University, Beijing, China
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-101	ISBN	2411-3487	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	annemarie.barthe@ensiacet.fr			Approved	no
	Call Number				Serial	2302
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	Author	Frederick Benaben; Lysiane Benaben
	Title	Science Fiction: Past and Future Trends of Crisis Management			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1130-1139
	Keywords	Information; Decision; Action; Future; Trends; Anticipation; Framework
	Abstract	This paper is a position paper, presenting an original but very anticipative and mainly imaginative vision of the evolution of the crisis management domain. After analyzing the options to make the past evolutions of that domain somehow explainable (mainly by analyzing the data of all the articles of the last fifteen editions of the ISCRAM conference), the paper aims at providing a framework to assess and evaluate the maturity of the domain of crisis management. Moreover, this framework is also used to tentatively infer some future evolutions and some directions that could be relevant, dangerous, tricky or of great benefit for the crisis management domain. These future trends are mainly based on the current maturity of crisis management (according to the proposed framework) and current or future influential practices, technologies or threats. It will be necessary to wait for fifteen years to see if these bets should be considered as accurate.
	Address	IMT Mines Albi; IMT Mines Albi
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-102	ISBN	2411-3488	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	frederick.benaben@mines-albi.fr			Approved	no
	Call Number				Serial	2303
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	Author	Deena Disraelly; Laura Itle
	Title	Providing Reliable Assistance Faster: Secure, Modern, Mission-Capable Credentialing to Support Disaster Operations			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1140-1143
	Keywords	Credentialing; Disaster Support; Clearance; Suitability; Volunteer
	Abstract	The public sector, including state and local government, public health, and emergency management; the private sector; and the Federal Government jointly face challenges with rapidly collecting and validating credentials for individuals applying for employment or volunteering for emergencies, vetting security clearances, and ascertaining suitability. In 2017, for instance, credentialing gaps delayed employees and volunteers from contributing much-needed skills in disaster areas during one of the worst hurricane and wildfire seasons on record while Federal agencies inadvertently issued interim clearances to individuals with criminal records. We propose a secure, modern, mission-capable information technology solution to these with the United States Postal Service hosting this streamlined process by serving as the hub for collection, validation, and transfer of pertinent data. The solution would introduce access points in over 5,000 communities for citizens participating in disaster support operations, as well as those requiring credentialing for employment as part of day-to-day operations.
	Address	Institute for Defence Analysis, Virginia USA; Institute for Defence Analysis, Virginia USA
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-103	ISBN	2411-3489	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	ddisrael@ida.org			Approved	no
	Call Number				Serial	2304
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	Author	Daniel Lichte; Dustin Witte; Kai-Dietrich Wolf
	Title	Comprehensive Security Hazard Analysis for Transmission Systems			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1145-1153
	Keywords	Physical Security; Energy Transmission Systems; Scenario Analysis; Threat Analysis; Risk Assessment
	Abstract	Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.
	Address	German Aerospace Center; University of Wuppertal; University of Wuppertal
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-104	ISBN	2411-3490	Medium
	Track	Open Track	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	daniel.lichte@dlr.de			Approved	no
	Call Number				Serial	2305
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	Author	Cecilia Hammar Wijkmark; Ilona Heldal
	Title	Virtual and Live Simulation-Based Training for Incident Commanders			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1154-1162
	Keywords	Virtual Simulation; Simulation; Serious Games; Training; Live Training; Cost and Benefit; Use; Usability; Incident Command
	Abstract	Computer and virtual simulation-based training (CST) offer several benefits for emergency response and management preparedness. However, organizations responsible for training are often hesitant to use CST, based on cost and perceived lack of benefit when compared to live simulation training (LST). This paper investigates how CST can complement LST, and how it contributes to achieving the necessary learning objectives for level one fire and rescue service incident commanders (ICs). Data and examples come from an experimental study with students from different fire and rescue services trained in the role of the IC in LST and CST, in a similar scenario. Results show the cost and benefits of the CST implementation based on evaluations from learners, instructors and responsible managers. Participants had a positive attitude towards using virtual simulations, but the results also point to barriers regarding the suitable design of learning scenarios and implementation.
	Address	Western Norway University of Applied Sciences; Western Norway University of Applied Sciences
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-105	ISBN	2411-3491	Medium
	Track	Open Track	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Cecilia.hammar.wijkmark@hvl.no			Approved	no
	Call Number				Serial	2306
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	Author	Dashley K. Rouwendal van Schijndel; Jo E. Hannay; Audun Stolpe
	Title	Simulation Vignette Generation from Answer Set Specifications			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	110-121
	Keywords	Exercise Management; Answer Set Programming; Mixed Reality Simulations; Vignette Generation
	Abstract	We investigate an approach that allows exercise managers to design simulations with an explicit focus on building skills, rather than having to focus on all the objects and interactions that a simulation must have. Exercise managers may design exercises at various levels of abstraction and always independently of how those sessions are implemented in simulations, while simulation components that implement the design are assembled and to some extent, automatically, behind the scenes. We outline (1) how Answer Set Programming can assist exercise managers in exercise planning and (2) how automated stage and content generation may be used to invoke appropriate simulation components to realize the design. For deliberate and recurrent training of decision-making skills, stages and content must vary to avoid familiarity (testing effects). We conclude by distilling a main research hypothesis that stipulates how (1) and (2) represent two modes of automated reasoning (so-called deductive versus abductive) and how that distinction clarifies the planning task.
	Address	University of Oslo, Department of Technology Systems; Norwegian Computing Center, Department of Applied Research in Information Technology; University of Oslo, Department of Technology Systems, Norwegian Computing Center, Department of Applied Research in Information Technology
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-11	ISBN	2411-3397	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	d.k.rouwendal@its.uio.no			Approved	no
	Call Number				Serial	2212
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	Author	Md Fitrat Hossain; Thomas Kissane; Priyanka Annapureddy; Wylie Frydrychowicz; Sheikh Iqbal Ahamed; Naveen Bansal; Praveen Madiraju; Niharika Jain; Mark Flower; Katinka Hooyer; Lisa Rein; Zeno Franco
	Title	Implementing Algorithmic Crisis Alerts in mHealth Systems for Veterans with PTSD			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	122-133
	Keywords	Crisis; Machine Learning Algorithms; mHealth; PTSD
	Abstract	This paper seeks to establish a machine learning driven method by which a military veteran with Post-Traumatic Stress Disorder (PTSD) is classified as being in a crisis situation or not, based upon a given set of criteria. Optimizing alerting decision rules is critical to ensure that veterans at highest risk for mental health crisis rapidly receive additional attention. Subject matter experts in our team (a psychologist, a medical anthropologist, and an expert veteran), defined acute crisis, early warning signs and long-term crisis from this dataset. First, we used a decision tree to find an early time point when the peer mentors (who are also veterans) need to observe the behavior of veterans to make a decision about conducting an intervention. Three different machine learning algorithms were used to predict long term crisis using acute crisis and early warning signs within the determined time point.
	Address	Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Mental Health America; Medical College of Wisconsin; Medical College of Wisconsin; Medical College of Wisconsin
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-12	ISBN	2411-3398	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mdfitrat.hossain@marquette.edu			Approved	no
	Call Number				Serial	2213
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	Author	Julien Coche; Aurelie Montarnal; Andrea Tapia; Frederick Benaben
	Title	Automatic Information Retrieval from Tweets: A Semantic Clustering Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	134-141
	Keywords	Information Retrieval; Word Embedding; BERT
	Abstract	Much has been said about the value of social media messages for emergency services. The new uses related to these platforms bring users to share information, otherwise unknown in crisis events. Thus, many studies have been performed in order to identify tweets relating to a crisis event or to classify these tweets according to certain categories. However, determining the relevant information contained in the messages collected remains the responsibility of the emergency services. In this article, we introduce the issue of classifying the information contained in the messages. To do so, we use classes such as those used by the operators in the call centers. Particularly we show that this problem is related to named entities recognition on tweets. We then explain that a semi-supervised approach might be beneficial, as the volume of data to perform this task is low. In a second part, we present some of the challenges raised by this problematic and different ways to answer it. Finally, we explore one of them and its possible outcomes.
	Address	IMT Mines Albi; IMT Mines Albi; Penn State University; IMT Mines Albi
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-13	ISBN	2411-3399	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	julien.coche@mines-albi.fr			Approved	no
	Call Number				Serial	2214
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	Author	Toshihiro Osaragi
	Title	Accessibility Evaluation of Specific Emergency Transportation Roads and Benefits of Seismic Retrofits on Buildings Adjoining Roads			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	143-156
	Keywords	Accessibility of Emergency Vehicle, Specific Emergency Transportation Road, Quake-Resistant-Conversion of Building, Large Earthquake.
	Abstract	Securing the accessibility of emergency vehicles using specific emergency transportation road (SETR) is crucial for the rapid activities of emergency vehicles after a large earthquake. In this paper, we construct a simulation model that describes collapse of roadside buildings and following street blockages, and evaluate the accessibility of emergency vehicles. Performing the simulations, we demonstrate the effects of quake-resistant-conversion of roadside buildings as follows: (1) the accessibility of emergency vehicles using SETR is not good enough under the current situation, but (2) can be significantly improved by performing seismic retrofit of buildings according to seismic index of building structure.
	Address	Tokyo Institute of Technology
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-14	ISBN	2411-3400	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	osaragi.t.aa@m.titech.ac.jp			Approved	no
	Call Number				Serial	2215
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	Author	Flavio Dusse; Renato Novais; Manoel Mendonça
	Title	A Visual Analytics Based Model for Crisis Management Decision-Making			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	157-166
	Keywords	Crisis Management, Decision-Making, Visual Analytics, Model.
	Abstract	Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under pressure to make the right decision at the right time. They must process large amounts of data and assimilate the received information in an intuitive way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We propose a model based on VA to support decision-making in CM. The aim of the model is to help visualization designers to create effective VA interfaces, to help crisis managers to make quick and assertive decisions with them. In previous studies, we carried out a survey protocol with a multi-method approach to collect data on crisis related decision-making and analyze all these data qualitatively with formal techniques during the large events held in Brazil in recent years. In this work, we used our previous findings to develop the proposed model. We validated it using the focus group technique. With the new findings, we identified relevant insights on the use of VA for crisis management. We hope that, with these continuous cycles of validation and improvement, the agencies that manage crises might use our model as a reference for building more effective IT decision-making infrastructures based on VA.
	Address	Federal University of Bahia; Federal Institute of Bahia; Federal University of Bahia
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-15	ISBN	2411-3401	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	dussebr@dcc.ufba.br			Approved	no
	Call Number				Serial	2216
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	Author	Erik Prytz; Anna-Maria Grönbäck; Krisjanis Steins; Craig Goolsby; Tobias Andersson Granberg; Carl-Oscar Jonson
	Title	Evaluating the Effect of Bleeding Control Kit Locations for a Mass Casualty Incident Using Discrete Event Simulation			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	167-178
	Keywords	Simulation, Mass Casualty Incident, Tourniquet, Stop the Bleed, Bleeding Control Kit Placement.
	Abstract	The purpose of this study was to develop a simulation model to evaluate bleeding control kit location strategies for a mass casualty incident scenario. Specifically, the event simulated was an explosion at a large sports arena. The model included a representation of the arena itself, simulated crowd movements following the detonation of an improvised explosive device, injuries and treatments, and different ways for immediate responders to help injured patients using tourniquets. The simulation model gave logically consistent results in the validation scenarios and the simulation outcomes were in line with the expected outcomes. The results of the different tourniquet location scenarios indicated that decentralized placement (more than one location) is better, easy access is important (between rather than at emergency exits) and that an increased number of available tourniquets will result in an increased number of survivors.
	Address	Department of Computer and Information Science, Linköping University; Linköping University; Department of Science and Technology, Linköping University; Uniformed Services University of the Health Sciences; Department of Science and Technology, Linköping University; Center for Disaster Medicine and Traumatology, and Department of Biomedical and Clinical Sciences, Linköping University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-16	ISBN	2411-3402	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Erik.prytz@liu.se			Approved	no
	Call Number				Serial	2217
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	Author	Laura Szczyrba; Yang Zhang; Duygu Pamukcu; Derya Ipek Eroglu
	Title	A Machine Learning Method to Quantify the Role of Vulnerability in Hurricane Damage			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	179-187
	Keywords	Vulnerability, Impact, Damage, Machine Learning, Hurricane María.
	Abstract	Accurate pre-disaster damage predictions and post-disaster damage assessments are challenging because of the complicated interrelationships between multiple damage drivers, including various natural hazards, as well as antecedent infrastructure quality and demographic characteristics. Ensemble decision trees, a family of machine learning algorithms, are well suited to quantify the role of social vulnerability in disaster impacts because they provide interpretable measures of variable importance for predictions. Our research explores the utility of an ensemble decision tree algorithm, Random Forest Regression, for quantifying the role of vulnerability with a case study of Hurricane Mar\'ia. The contributing predictive power of eight drivers of structural damage was calculated as the decrease in model mean squared error. A measure of social vulnerability was found to be the model's leading predictor of damage patterns. An additional algorithm, other methods of quantifying variable importance, and future work are discussed.
	Address	Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-17	ISBN	2411-3403	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	lszczyrba@vt.edu			Approved	no
	Call Number				Serial	2218
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	Author	Xiaoyan Zhang; Graham Coates; Sarah Dunn; Jean Hall
	Title	Emergency Evacuation from a Multi-floor Building using Agent-based Modeling			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	188-199
	Keywords	Emergency Evacuation, Agent-based Modeling and Simulation, Multi-floor Building.
	Abstract	This paper presents an overview of the ongoing research into the development of an agent-based model to enable simulations to be performed of agents evacuating from a multi-floor building with a complex layout, including staircases. Specifically, a flow field of navigation objects is constructed pre-computation, which stores the directions and shortest distances to all exits and staircases. Using the flow field, a navigation method is proposed for agents familiar with the environment to identify and follow the shortest route to a chosen exit. Preliminary simulations have been performed to investigate the effect on evacuation time of (i) exit configurations and (ii) familiarity of agents with the building layout. In assessing the effect of exit configurations, results show that the location of the main entrance has a significant influence on evacuation time. In addition, having more exits does not necessarily lead to a shorter evacuation time. In terms of the effect of familiarity of agents, having more agents with a greater level of familiarity does not significantly reduce evacuation time in most cases.
	Address	Newcastle University; Newcastle University; Newcastle University; Newcastle University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-18	ISBN	2411-3404	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	X.Zhang110@newcastle.ac.uk			Approved	no
	Call Number				Serial	2219
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	Author	Anying Chen; Zhongliang Huang; Manchun Liang; Guofeng Su
	Title	Empirical Study of Individual Evacuation Decision-making in Fire Accidents: Evacuate Intention and Herding Effect			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	200-209
	Keywords	Fire Accidents, Evacuation Experiment, Evacuate Intention, Herding Behaviors.
	Abstract	People's decision of evacuating or not could greatly influence the final losses in fire accidents. In order to study people's response under emergent occasions, a fire accident evacuation drill experiment was conducted in an office building without advance notice. 113 Participants' response and their decision-making process were collected by questionnaire survey right after the experiment. In this study, we mainly focused on two aspects of people's response, including participants' evacuate intention and their herding tendency during evacuate decision-making. It is found that the classical Expected Utility Theory (EUT) has certain limitation in explaining individual's evacuation intention, but the relationship between the expected utility and the evacuation intention could be represented with a modified model based on EUT. Furthermore, the herding tendency is found to be different for the two groups of people who intend to evacuate and not to evacuate. People who firstly intend not to evacuate are more easily to form herding behavior and change their minds to evacuate. Based on these findings, models of individual evacuation intention and herding tendency for two groups of people are put forward. Simulation is conducted to investigate the effect of these two changes in people's evacuation decision-making process, and results show that they both increase the final evacuation rate, reflecting the majority's risk aversion characteristics.
	Address	Tsinghua University;Tsinghua University; Tsinghua University; Tsinghua University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-19	ISBN	2411-3405	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	chenay15@mails.tsinghua.edu.cn			Approved	no
	Call Number				Serial	2220
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	Author	Mehdi Ben Lazreg; Usman Anjum; Vladimir Zadorozhny; Morten Goodwin
	Title	Semantic Decay Filter for Event Detection			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	14-26
	Keywords	String Metric, Event Detection, Crisis Management.
	Abstract	Peaks in a time series of social media posts can be used to identify events. Using peaks in the number of posts and keyword bursts has become the go-to method for event detection from social media. However, those methods suffer from the random peaks in posts attributed to the regular daily use of social media. This paper proposes a novel approach to remedy that problem by introducing a semantic decay filter (SDF). The filter's role is to eliminate the random peaks and preserve the peak related to an event. The filter combines two relevant features, namely the number of posts and the decay in the number of similar tweets in an event-related peak. We tested the filter on three different data sets corresponding to three events: the STEM school shooting, London bridge attacks, and Virginia beach attacks. We show that, for all the events, the filter can eliminate random peaks and preserve the event-related peaks.
	Address	Dept. of Information and Communication Technology, University of Agder,Grimstad, Norway; Dept. of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, USA; Dept. of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, USA; Dept. of Information and Communication Technology, University of Agder,Grimstad, Norway
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-2	ISBN	2411-3388	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mehdi.ben.lazreg@uia.no			Approved	no
	Call Number				Serial	2203
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	Author	Milad Baghersad; Christopher W. Zobel; Ravi Behara
	Title	Evaluation of Local Government Performance after Disasters			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	210-217
	Keywords	311 Services, Disaster, Municipal Departments, Resilience.
	Abstract	Monitoring and evaluation can help organizations involved in disasters learn from their responses to prior events and improve their performance over time. Using a data set of non-emergency service requests in New York City (NYC), this paper provides a method to evaluate and compare the performance of local governments in terms of service request response times after different disaster events. In particular, the proposed method can be used to compare such performance across divisions or boroughs in a city. To illustrate this, we evaluate the performance in five of NYC's boroughs: the Bronx, Brooklyn, Manhattan, Queens, and Staten Island, across seven major natural disaster events from 2010 to 2012. Our analyses show that Queens and Brooklyn demonstrate better performance than the other boroughs in almost all of the seven events under consideration.
	Address	Florida Atlantic University; Virginia Tech; Florida Atlantic University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-20	ISBN	2411-3406	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mbaghersad@fau.edu			Approved	no
	Call Number				Serial	2221
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	Author	Eva Petitdemange; Elyes Lamine; Franck Fontanili; Matthieu Lauras
	Title	Enhancing Emergency Call Centers' Performance Through a Data-driven Simulation Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	218-227
	Keywords	Emergency Call Center, Performance, Simulation, Data-Driven, Continuous Improvement, Organization.
	Abstract	Emergency Call Centers (ECCs) can be considered as the starting point of the pre-hospital emergency medical system. Although, ECCs exist everywhere, their business processes and their performance levels differ from one place to another, even sometimes in a same country. By definition, users expect a high level of performance, particularly regarding the waiting time and the processing time of the calls. Additionally, ECCs might have difficulties to manage sudden rise of activities following disasters impacting huge number of victims for instance. To support ECCs in their continuous improvement steps, this paper suggests an innovative framework and its associated tools to support both diagnosis of current organizations and enhancement of their performance. Concretely, the proposal is data-driven and simulation oriented. First experiments are shown in order to demonstrate the potential benefits of such an approach. Avenues for further research are also discussed.
	Address	IMT Mines Albi, University of Toulouse; IMT Mines Albi, University of Toulouse; IMT Mines Albi, University of Toulouse; IMT Mines Albi, University of Toulouse
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-21	ISBN	2411-3407	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	eva.petitdemange@mines-albi.fr			Approved	no
	Call Number				Serial	2222
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	Author	Duygu Pamukcu; Christopher W. Zobel; Andrew Arnette
	Title	Characterizing Social Community Structures in Emergency Shelter Planning			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	228-236
	Keywords	Evacuation Planning; Sheltering; Simulation; Social Network; Group Behavior
	Abstract	During emergencies, it is often necessary to evacuate vulnerable people to safer places to reduce loss of lives and cope with human suffering. Shelters are publically available places to evacuate, especially for people who do not have any other choices. This paper overviews emergency shelter planning in disaster mitigation and preparation and discusses the need for better responding to people who need to evacuate during emergencies. Recent evacuation studies pay attention to integrating social factors into evacuation modeling for better prediction of evacuation decisions. Our goal is to address the impact of social behavior on the sheltering choices of evacuees and to explore the potential contributions of including social network characteristics in the decision-making process of authorities. We present the shelter utilization problem in South Carolina during Hurricane Florence and discuss an agent-based modeling approach that considers social community structures in modeling the shelter choice behavior of socially connected individuals.
	Address	Virginia Tech; Virginia Tech; University of Wyoming
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-22	ISBN	2411-3408	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	duygu@vt.edu			Approved	no
	Call Number				Serial	2223
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	Author	Andrew Arnette; Christopher W. Zobel; Duygu Pamukcu
	Title	Post-Impact Analysis of Disaster Relief Resource Pre-Positioning After the 2013 Colorado Floods			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	237-243
	Keywords	Disaster Operations Management; Facility Location; Humanitarian Operations
	Abstract	Pre-positioning of supplies is important to facilitate disaster relief operations, however it is only after a disaster event occurs that the effectiveness of the pre-positioning strategy can be properly assessed. With this in mind, this paper analyzes a risk-based pre-positioning algorithm, developed for the American Red Cross, in the context of its actual performance in the 2013 Colorado Front Range floods. The paper assesses the relative effectiveness of the pre-positioning approach with respect to historical asset placements, and it discusses changes to the model that are necessary to support such comparisons and allow for further model extensions.
	Address	University of Wyoming; Virginia Tech; Virginia Tech
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-23	ISBN	2411-3409	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	aarnette@uwyo.edu			Approved	no
	Call Number				Serial	2224
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	Author	Cornelius Dold; Christopher Munschauer; Ompe Aimé Mudimu
	Title	Real-Life Exercises as a Tool in Security Research and Civil Protection – Options for Data Collections			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	244-250
	Keywords	Real-Life Exercises; Data Collection; Emergency Response; Civil Protection; Large-Scale Exercises
	Abstract	A real-life exercise is a scientific method used by the TH Köln to generate data sets of new technologies and operational concepts derived from research projects. The Institute of Rescue Engineering and Civil Protection (German acronym: IRG) uses a real-time locating system (RTLS), video surveillance, observers and a mass casualty incident benchmark to generate motion profiles, information flows and information on the quality of care. In this practitioner paper these different methods will be discussed and the combination of different data is described. Furthermore, an outlook is given on the extent to which the method will be improved and expand-ed in the future. Concluding it can be said that the combination of all collected data is essential for the evalua-tion of a real-life exercise in security research or civil protection.
	Address	TH Köln – University of Applied Sciences, Cologne; TH Köln – University of Applied Sciences, Cologne; TH Köln – University of Applied Sciences, Cologne
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-24	ISBN	2411-3410	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	cornelius.dold@th-koeln.de			Approved	no
	Call Number				Serial	2225
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	Author	Kristine Steen-Tveit
	Title	Identifying Information Requirements for Improving the Common Operational Picture in Multi-Agency Operations			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	252-263
	Keywords	Situational Awareness, Common Operational Picture, Information Sharing, Common Information Requirements, Multi-Agency Emergency Operations.
	Abstract	While there exists a considerable body of literature on the importance of a common operational picture (COP) in multi-agency emergency operations, the COP concept itself still lacks a univocal definition. Despite the lack of consensus regarding the mechanisms underlying the COP, the literature implies a level of consistency in the focus on sharing critical information. Based on interviews with Norwegian emergency management stakeholders, this study investigates common information requirements for emergency management services and presents an example of a framework for structuring the sharing of critical information and building a COP. Termed 'the window report', this framework is used among emergency stakeholders in Norway and Sweden. The study identified eight common information requirement categories for managing extreme weather scenarios. With a focus on common information needs and a process for structured information sharing, future strategic emergency management planning might take a more holistic perspective on cross-sectoral operations than in current practice.
	Address	Centre for Integrated Emergency Management, University of Agder
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-25	ISBN	2411-3411	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	kristine.steen-tveit@uia.no			Approved	no
	Call Number				Serial	2226
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	Author	Björn JE Johansson; Amanda Jaber; Joeri van Laere; Peter Berggren
	Title	Crisis Response During Payment Disruptions – The Themes of TRAMS			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	264-275
	Keywords	Crisis Management, Payment Disruptions, Resilience, Thematic Analysis.
	Abstract	A qualitative analysis of observation protocols and audio recordings from 14 crisis response exercises has been conducted revealing eight themes reoccurring in multi-disciplinary team discussions about crisis response to large disruptions to the card payment system. The themes were: Coordinate and collaborate, Payment options, Cash circulation, Fuel and transportation, Security, Inform, communicate and the media, Hoarding and rationing, and Vulnerable groups. The analysis suggest that Swedish society is vulnerable to disruptions in the card payment services, largely due to a low diversity in payment options, the lack of prepared back up solutions for payment, and insufficient cash flows to support a cash only scenario. A longer (several days) disruption in the card payment system will demand coordinating mechanisms for information management, available payment options, and preparedness for rapid establishment of cash flows. Today, these mechanisms do not exist. Simulation exercises with stake-holders are an important mean for increasing awareness about these vulnerabilities and the challenges associated with coping with them.
	Address	Linköping University; Linköping University; Skövde University; Linköping University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-26	ISBN	2411-3412	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	bjorn.j.johansson@liu.se			Approved	no
	Call Number				Serial	2227
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