Alayne Da Costa Duarte, Marcos R. S. Borges, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2013). ASC model: A process model for the evaluation of simulated field exercises in the emergency domain. 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. 551–555). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The undefined flow of execution of activities in an evaluation process hampers its implementation. A consistent evaluation process defines interrelated methodological steps that make it easier for the evaluator to lead the process. This article presents a process model for the evaluation of simulated field exercises in the emergency domain, including their sub processes and activities. The proposed model was derived from observations made during real situations of a simulated evacuation exercise of communities in high-risk areas in Rio de Janeiro (Brazil). The motivation came from the finding that the assessment of simulated field exercises is conducted by completing an activity report that does not follow a structural model, an evaluation program or a formal standard. The results of this research show the experts' satisfaction with the application of the model proposed for the development of an evaluation process. The same occurs when comparing to reports currently used by them for this purpose.
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Hüseyin Can Ünen, Muhammed Sahin, & Amr S. Elnashai. (2011). Assessment of interdependent lifeline networks performance in earthquake disaster management. 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: Several studies and observations regarding past earthquakes such as 1989 Loma Prieta, 1994 Northridge, or 1999 Marmara earthquakes have shown the importance of lifeline systems functionality on response and recovery efforts. The general direction of studies on simulating lifelines seismic performance is towards achieving more accurate models to represent the system behavior. The methodology presented in this paper is a product of research conducted in the Mid-America Earthquake Center. Electric power, potable water, and natural gas networks are modeled as interacting systems where the state of one network is influenced by the state of another network. Interdependent network analysis methodology provides information on operational aspects of lifeline networks in post-seismic conditions in addition to structural damage assessment. These results are achieved by different components of the tool which are classified as structural and topological. The topological component analyzes the post seismic operability of the lifeline networks based on the damage assessment outcome of the structural model. Following an overview of the models, potential utilizations in different phases of disaster management are briefly discussed.
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Lida Huang, Guoray Cai, Hongyong Yuan, Jianguo Chen, Yan Wang, & Feng Sun. (2018). Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 121–134). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
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Miguel Ramirez de la Huerga, Victor A. Bañuls, & Murray Turoff. (2015). A Scenario-based approach for analyzing complex cascading effects in Operational Risk Management. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: This is the first paper to apply Cross Impact Analysis (CIA) and Interpretative Structural Modeling (ISM) methods for analyzing complex cascading effects in Operational Risk Management in an industrial environment. Its main objective is to improve the understanding of the overall picture of an organization?s risks. The paper summarizes the development of a CIA-ISM method of the interaction of 18 critical events of an industrial plant as a first step to improving organizational resilience based on the company?s own estimations as well as the estimates of a panel. The main benefit of using these methods is to know the relationships between different risks and consequences, direct links, indirect and cascading effects. Having the possibility of knowing a full risk map and being able to make a forecast will help to mitigate the unexpected effects and have a better response after an emergency situations is the same as being more resilient.
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Murray Turoff, & Victor A. Bañuls. (2011). Major extensions to Cross-Impact Analysis. 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: In recent years Cross-Impact Analysis (CIA) has resurged as a powerful tool for forecasting the occurrence or not of a set of interrelated events in complex situations, such as emergencies. In this sense, CIA can be used for creating working models out of significant events and crisis scenarios. CIA has been combined with other methodological approaches in order to increase its functionality and improve its final outcome. This is the case of the merger of CIA and the technique called Interpretive Structural Modeling (ISM). The CIA-ISM approach aims at contributing to CIA with tools for detecting critical events and supporting graphical representation of scenarios. In this paper, major extensions to CIA-ISM are presented. These extensions are based on the inclusion of initial condition events and outcome events as two new event types that make CIA-ISM much richer in its potential span of application areas. The practical implications of these major extensions to CIA-ISM are illustrated with an example. The usefulness of this contribution to researchers and practitioners concerned with emergency planning and preparedness is also discussed.
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Murray Turoff, Victor A. Bañuls, Linda Plotnick, & Starr Roxanne Hiltz. (2014). Development of a dynamic scenario model for the interaction of critical infrastructures. 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. 414–423). University Park, PA: The Pennsylvania State University.
Abstract: This paper summarizes the development of a Cross Impact and Interpretive Structural Model of the interactions of 16 critical infrastructures during disasters. It is based on the estimates of seven professionals in Emergency Management areas and was conducted as an online survey and Delphi Process. We describe the process used and the current results, indicating some of the disagreements in the estimates. The initial results indicate some very interesting impacts of events on one another, resulting in the clustering of events into mini-scenarios.
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Victor A. Bañuls, Cristina López-Vargas, Fernando Tejedor, Murray Turoff, & Miguel Ramirez de la Huerga. (2016). Validating Cross-Impact Analysis in Project Risk Management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Companies work increasingly more on projects as a means of executing organizational decisions. However, too many enterprise projects result in failure. Hence, firms should follow a risk management method that drives their projects toward success. Nevertheless, project managers often deal with risks intuitively. This is partly because they lack the proper means to correctly manage the underlying risks which affect the entire cycle of their projects. Therefore, one purpose is to identify the critical events that managers may encounter before the beginning of the project and during its development. In addition, we propose CIA-ISM to represent existing relationships between the unforeseen events in the project?s lifetime and their key performance indicators. This also predicts the influence of risks on project performance over time by means of scenarios. The tool proposed would thus help practitioners to manage enterprise projects risks in a more effective and proactive way. We have validated the predictive capability of the CIA-ISM model with 22 real projects. The results show a high level of predictive capability in terms of risk analysis and key performance indicators.
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Victor A. Bañuls, Murray Turoff, & Joaquin Lopez. (2010). Clustering scenarios using cross-impact analysis. 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: Scenarios are frequently used in Emergency Planning and Preparedness. These scenarios are developed based on the hypothesis of occurrence or not of significant events. This is a complex process because of the interrelations between events. This fact, along with the uncertainty about the occurrence or non-occurrence of the events, makes the scenario generation process a challenging issue for emergency managers. In this work a new step-by-step model for clustering scenarios via cross-impact is proposed. The authors. proposal adds tools for detecting critical events and graphical representation to the previous scenario-generation methods based on Cross-Impact Analysis. Moreover, it allows working with large sets of events without using great computational infrastructures. These contributions are expected to be useful for supporting the analysis of critical events and risk assessment tasks in Emergency Planning and Preparedness. Operational issues and practical implications of the model are discussed by means of an example.
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