Murray Turoff, Connie White, Linda Plotnick, & Starr Roxanne Hiltz. (2008). Dynamic emergency response management for large scale decision making in extreme events. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 462–470). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of a large-scale extreme event requires a system that can quickly adapt to changing needs of the users. There is a critical need for fast decision-making within the time constraints of an ongoing emergency. Extreme events are volatile, change rapidly, and can have unpredictable outcomes. Large, not predetermined groups of experts and decision makers need a system to prepare for a response to a situation never experienced before and to collaborate to respond to the actual event. Extreme events easily require a hundred or more independent agencies and organizations to be involved which usually results in two or more times the number of individuals. To accomplish the above objectives we present a philosophical view of decision support for Emergency Preparedness and Management that has not previously been made explicit in this domain and describe a number of the current research efforts at NJIT that fit into this framework.
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Chris J. Van Aart, & Stijn Oomes. (2008). Real-time organigraphs for collaboration awareness. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 651–659). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Collaboration awareness, as extension to organization awareness, is knowing how organizations do work and achieve their goals. This knowledge moves on a scale from stated prescribed ways of acting (such as procedures and protocols) to informal channels of communication, teamwork and decision-making. Based on available static and dynamic data, standardized insights can be given about collaboration in emergency situations in the form of organigraphs. We argue that for gaining practical collaboration awareness, both the formal structure of an organization as well as informal interactions should be inspected. Informal interaction includes informal communication channels, actual decision making on the spot and multi-disciplinary joint activities. We have implemented our system in the form of a web-based visualization tool. This tool would have been useful in the Hercules disaster, giving insights in informal information exchange, possibly preventing fatal decisions.
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Josine Van De Ven, & Martijn Neef. (2006). A critical thinking environment for crisis response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 223–229). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Building up a proper understanding of a large-scale incident is an important and difficult process. We envision a working environment for decision makers in crisis management situations that allows them to work with information in various ways. That will stimulate them to think critically in processing the information they receive-All in support of rapid sensemaking and decision making. To realize this ambition, we combine various technologies into an integrated support concept called the Critical Thinking Environment (CTE), aimed at tackling critical issues in sensemaking.
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Willem Van Santen, Catholijn M. Jonker, & Niek Wijngaards. (2009). Crisis decision making through a shared integrative negotiation mental model. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Decision making during crises takes place in (multi-agency) teams, in a bureaucratic political context. As a result, the common notion that during crises decision making should be done in line with a Command & Control structure is invalid. This paper shows that the best way for crisis decision making teams in a bureaucratic political context is to follow an integrative negotiation approach as the shared mental model of decision making. This conclusion is based on an analysis of crisis decision making by teams in a bureaucratic political context. First of all this explains why in a bureaucratic political context the Command & Control adage does not hold. Secondly, this paper motivates why crisis decision making in such context can be seen as a negotiation process. Further analysis of the given context shows that an assertive and cooperative approach suits crisis decision making best.
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Rebecca Walton, Robin E. Mays, & Mark P. Haselkorn. (2011). Defining fast: Factors affecting the experience of speed in humanitarian logistics. 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: Speed is a central value for emergency logistics stakeholders. Emergency response literature makes a compelling case for rapid logistics processes to provide goods and services in humanitarian emergencies. However, speed is not well-defined concept. While situational demand contributes to the need for speed, an important factor is the perception of speed given the experience of the response stakeholders. Unfortunately, the literature lacks complex, situated pictures of how logistics stakeholders experience speed (i.e., what does it mean for a logistics process to be “fast”? What factors affect whether stakeholders perceive a logistics experience as fast?) To address this gap, we explored how logistics stakeholders in a large international humanitarian organization experience and perceive speed of operations. Our findings suggest that (1) the experience of speed is often comparative, not solely objective; (2) close communication between internal clients (field requestors) and service providers (logistics team) can make clients more likely to experience the logistics process as fast; and (3) feeling in control of decision-making can make both clients and service providers more likely to experience the logistics process as fast.
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Kui Wang, Jose Marti, Ming Bai, & K.D. Srivastava. (2012). Optimal decision maker algorithm for disaster response management with I2Sim applications. 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: Disaster response management has become an important area of research in recent years, with authorities spending more resources in the area. Infrastructure resource interdependencies are key critical points for a system to operate optimally. After a disaster occurs, infrastructures would have sustained certain degrees of damage, the allocation of limited resources to maximize human survival becomes a top priority. The I2Sim (Infrastructures Interdependencies Simulator) research group at the University of British Columbia (UBC) has developed a software simulation toolbox to help authorities plan for disaster responses. This paper presents an optimization decision algorithm based on Lagrange multipliers, which provides the theoretical basis for I2Sim software decision maker layer. There is a simple scenario of three hospitals constructed with the I2Sim toolbox to illustrate the interdependencies of water and electricity. © 2012 ISCRAM.
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Connie White, Murray Turoff, & Starr Roxanne Hiltz. (2010). A real time online Delphi Decision System, V 2.0: Crisis management support during extreme events. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The Delphi Decision Maker system has been designed to support the decision making needs of crisis managers, considering factors such as stress, time pressure, information overload, and uncertainty. It has been built as a module for the Sahana Disaster Management system, a free and open source system. The Design Science research paradigm was used in an iterative development process. Triangulation was employed in the evaluation, analyzing the system against the research questions using both qualitative and quantitative statistics as well as proof of concept. Modifications need to be made for real world use. A second version of the system is under development. Research findings and future research are outlined in this work in progress.
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Yaping Ma, Hui Zhang, Tao Chen, & Rui Yang. (2015). Decentralized Evacuation System Based on Occupants Distribution and Building Information. 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: Effective evacuation is critical for safety of occupants. The exiting evacuation systems lack flexibility and don?t consider the distribution of occupants. It is possible to direct occupants to danger areas or cause congestion in certain areas. In this paper, a decentralized evacuation system is proposed to compute the safest path in real time. The system is composed of fire detection sensors, zone controllers, elevator sensors, human tracking and monitoring systems and dynamic egress signs. All devices are placed at the predetermined locations based on integrated design of the building. The entire building is divided into many basic zones which are operating quite independently, and global information is communicated to neighboring zones and consequently to entire network by zone controllers. The system acts in decentralized fashion. The elevator and dynamic factors are considered in guidance system. Simulations are performed to determine the advantage of the system.
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Yikun Liu, Sung Pil Moon, Mark Pfaff, Jill L. Drury, & Gary L. Klein. (2011). Collaborative option awareness for emergency response decision making. 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: We have been using exploratory modeling to forecast multiple plausible outcomes for a set of decision options situated in the emergency response domain. Results were displayed as a set of box-plots illustrating outcome frequencies distributed across an evaluative dimension (e.g., cost, score, or utility). Our previous research showed that such displays provide what we termed “option awareness” – an ability to determine robust options that will have good outcomes across the broadest number of plausible futures. This paper describes an investigation into extending this approach to collaborative decision making by providing a visualization of both collaborative and individual decision spaces. We believe that providing such visualizations will be particularly important when each individuals decision space does not account for the synergy that may emerge from collaboration. We describe how providing collaborative decision spaces improves the robustness of joint decisions and engenders high confidence in these decisions.
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Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. 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. 240–244). University Park, PA: The Pennsylvania State University.
Abstract: The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
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Shengcheng Yuan, Ma Ma, H. Zhang, & Yi Liu. (2013). An urban traffic evacuation model with decision-making capability. 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. 317–321). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Traffic evacuation is one of the most challenging problems in a mega city due to crowded road conditions. This study focuses on developing a traffic evacuation model with decision-making capability. The model basically consists of two modules. The first one is a decision-making support module which runs very fast and provides short-forecast. The second one is a simulation module, which is used for simulating real evacuation process and for overall performance evaluation with vehicle tracking model. The first module can be considered as a “local” module as only partial information, such as traffic information in certain junctions is available. The second module can be considered as a global module which provides traffic directions for junction, and effective using of road-nets. With integration of two modules, overall system optimization may be achieved. Simulation cases are given for model validation and results are satisfied.
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Shengcheng Yuan, Yi Liu, Gangqiao Wang, Hongshen Sun, & H. Zhang. (2014). A dynamic-data-driven driving variability modeling and simulation for emergency evacuation. 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. 70–74). University Park, PA: The Pennsylvania State University.
Abstract: This paper presents a dynamic data driven approach of describing driving variability in microscopic traffic simulations for both normal and emergency situations. A four-layer DGIT (Decision, Games, Individual and Transform) framework provides the capability of describing the driving variability among different scenarios, vehicles, time and models. A four-step CCAR (Capture, Calibration, Analysis and Refactor) procedure captures the driving behaviors from mass real-time data to calibrate and analyze the driving variability. Combining the DGIT framework and the CCAR procedure, the system can carry out adaptive simulation in both normal and emergency situations, so that be able to provide more accurate prediction of traffic scenarios and help for decision-making support. A preliminary experiment is performed on a major urban road, and the results verified the feasibility and capability of providing prediction and decision-making support.
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Nan Zhang, Clare Bayley, & Simon French. (2008). Use of web-based group decision support for crisis management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 55–58). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Web-based group decision support systems (wGDSS) are becoming more common in organizations. In this paper, we provide a review and critique of the literature on wGDSS, raising a number of issues that need addressing. Then we report on a small scale experiment using Groupsystems ThinkTank to manage an issue to do with food safety. We also describe how we propose to use ThinkTank in a crisis situation.
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Christopher W. Zobel. (2010). Comparative visualization of predicted disaster resilience. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The disaster resilience triangle is a simple but effective tool for illustrating the relationship between the initial impact of a disaster event and the subsequent time to recovery. This tool can also be expanded, however, to provide an analytic measure of the level of resilience exhibited by a particular entity in a given disaster situation. We build upon the previous work in this area by developing a new approach for visualizing and analyzing the tradeoffs between the two primary defining characteristics of the disaster resilience triangle. This new approach supports strategic decision making in a disaster planning environment by providing a straightforward means for directly comparing the relative predicted resilience of different critical facilities within an organization, with respect to both location and type of risk.
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Christopher W. Zobel. (2011). Representing the multi-dimensional nature of disaster resilience. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Although quantitative analytical information systems are an important resource for supporting decision-making in disaster operations management, not all aspects of a disaster situation can be easily quantified. For example, although the concept of the disaster resilience of a community has a technical dimension within which one can measure the resistance of the infrastructure against, and the speed of its recovery from, a disaster event, it also has social, organizational, and economic dimensions within which these characteristics may be more difficult to measure. This work-in-progress paper introduces a quantitative framework within which the multi-dimensional nature of such disaster resilience can be represented in a concise manner. This can help to improve understanding of the complexities associated with the concept, and thus directly support decision-making in disaster operations planning and management.
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