Aarland, M., Radianti, J., & Gjøsæter, T. (2023). Using System Dynamics to Simulate Trust in Digital Supply Chains. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 516–529). Omaha, USA: University of Nebraska at Omaha.
Abstract: The power industry is outsourcing and digitalising their services to provide better, faster, and more reliable supply of electric power to the society. As a result, critical infrastructure increases in complexity and tight couplings between multiple suppliers and systems in digital supply chains. It also introduces new risks and challenges that are difficult to manage for critical infrastructure owners. To address the vulnerability in digital supply chains, we have developed a system dynamics model that represent important challenges to manage cybersecurity in digital supply chains, based on input from an expert group in the power industry. The system dynamics model illustrates how trust in suppliers as well as the need for control play important roles in outsourcing. Scenarios were developed and simulated.
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Abdelgawad, A. A. (2023). An Updated System Dynamics Model for Analysing the Cascading Effects of Critical Infrastructure Failures. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 595–608). Omaha, USA: University of Nebraska at Omaha.
Abstract: Aiming at examining the cascading effects of the failure of Critical Infrastructure (CI), this work-in-progress research introduces an improved System Dynamics model. We represent an improvement over the previous models aimed at studying CIs interdependencies and their cascading effects. Our model builds on earlier models and corrects their flaws. In addition to introducing structural enhancements, the improvements include using unpublished data, a fresh look at a previously collected dataset and employing a new data processing to address and resolve some longstanding issues. The dataset was fed to an optimisation model to produce a new dataset used in our model. The structure of our SD model, its dataset and the data processing techniques we employed to create this dataset are all described in the study. Although the model has passed the fundamental validation criteria, more validation testing and scenario exploration are yet to be conducted.
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Kpotissan Adjetey-Bahun, Babiga Birregah, Eric Châtelet, Jean-Luc Planchet, & Edgar Laurens-Fonseca. (2014). A simulation-based approach to quantifying resilience indicators in a mass transportation system. 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. 75–79). University Park, PA: The Pennsylvania State University.
Abstract: A simulation-based model used to measure resilience indicators of the railway transportation system is presented. This model is tested through a perturbation scenario: the inoperability of a track which links two stations in the system. The performance of the system is modelled through two indicators: (a) the number of passengers that reach their destination and (b) the total delay of passengers after a serious perturbation. The number of passengers within a given station at a given time is considered as early warning in the model. Furthermore, a crisis management plan has been simulated for this perturbation scenario in order to help the system to recover quickly from this perturbation. This crisis management plan emphasizes the role and the importance of the proposed indicators when managing crises.
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Michael R. Bartolacci, Christoph Aubrecht, & Dilek Ozceylan Aubrecht. (2014). A portable base station optimization model for wireless infrastructure deployment in disaster planning and management. 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. 50–54). University Park, PA: The Pennsylvania State University.
Abstract: Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts.
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Josey Chacko, Loren P Rees, & Christopher W. Zobel. (2014). Improving resource allocation for disaster operations management in a multi-hazard context. 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. 85–89). University Park, PA: The Pennsylvania State University.
Abstract: The initial impact of a disaster can lead to a variety of associated hazards. By taking a multi-hazard viewpoint with respect to disaster response and recovery, there is an opportunity to allocate limited resources more effectively, particularly in the context of long-term planning for community sustainability. This working paper introduces an approach for extending quantitative resource allocation models to consider multiple interrelated hazards. The discussion is motivated by a literature review of existing models and then focuses on changes necessary to take the multiplicity of hazards into consideration in the context of decision support systems for disaster operations management.
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Ahmed T. Elsergany, Amy L. Griffin, Paul Tranter, & Sameer Alam. (2014). Descriptive and Geographical Analysis of Flood Disaster Evacuation Modelling. 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. 55–59). University Park, PA: The Pennsylvania State University.
Abstract: The planning of evacuation operations for a riverine flood disaster is vital for minimizing their negative impacts on human lives. This paper aims to develop a systematic method to model and plan evacuation trip generation and distribution for riverine floods. To achieve this aim, it adapts the transportation or Hitchcock problem, an operations research technique employed in conventional four-stage transportation modeling, and that is used to plan and model transport in normal situations, so that it is appropriate for flood disaster situations focusing on the first two stages. Concentrating on pre-flood hazard planning, our evacuation modelling considers two types of flood disaster data environments: certain environs, in which all decision variables are known, and uncertain environs, when probabilities of decision variables are considered in the evacuation plans.
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Janine Hellriegel, & Michael Klafft. (2014). A tool for the simulation of alert message propagation in the general population. 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. 65–69). University Park, PA: The Pennsylvania State University.
Abstract: Informing and alerting the population in disaster situations is a challenging task. Numerous situational factors have to be considered, as well as the impact of a plethora of communication channels, and multiplication effects in the population. In order to optimize the alerting strategies and enhance alert planning, it would be beneficial to model the dissemination of alerts. In this paper, we present a general overview of an alert dissemination model as well as its prototypical implementation in a simulation software. The software takes situational parameters such as time of day and location into account and can even infer characteristics of the alerting infrastructure from geospatial information.
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Theresa I. Jefferson, & John R. Harrald. (2014). Estimating the impacts associated with the detonation of an improvised nuclear device. 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. 80–84). University Park, PA: The Pennsylvania State University.
Abstract: The explosion of an improvised nuclear device (IND), in any American city, would cause devastating physical and social impacts. These impacts would exceed the response capabilities of any city, state or region. The potential loss and suffering caused by an IND detonation can be dramatically reduced through informed planning and preparedness. By incorporating estimates of the impacts associated with the detonation of an IND into the planning process, jurisdictions can estimate the scale and scope of their response requirements. A prototype, computer-based tool was developed to quantify the human impacts associated with an IND detonation. Using various types of information such as the approximation of the prompt radiation footprint, blast footprint, and thermal footprint of the detonation, along with an estimation of the level of protection provided by building structures the system calculates the number and type of injuries that can be expected in a monocentric urban area.
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Abdullah Konak. (2014). Improving network connectivity in emergency ad hoc wireless networks. 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. 36–44). University Park, PA: The Pennsylvania State University.
Abstract: Wireless Ad Hoc Networks (MANETs) can to provide first responders and disaster management agencies with a reliable communication network in the event of a large-scale natural disaster that devastates majority of the existing communication infrastructure. Without requiring a fixed infrastructure, MANETs can be quickly deployed after a large-scale natural disaster or a terrorist attack. On the other hand, MANETs have dynamic topologies which could be disconnected because of the mobility of nodes. This paper presents a decentralized approach to maintain the connectivity of a MANET using autonomous, intelligent agents. Concepts from the social network analysis along with flocking algorithms are utilized to guide the deployment decision of agents. Unlike a basic flocking algorithm where all nodes have the same importance, network metrics are used to quantify the relative importance of nodes. Computational results are presented to demonstrate the effect of various local agent behaviors on the global network connectivity.
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Thomas Münzberg, Marcus Wiens, & Frank Schultmann. (2014). A strategy evaluation framework based on dynamic vulnerability assessments. 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. 45–54). University Park, PA: The Pennsylvania State University.
Abstract: Assessing a system's vulnerability is a widely used method to estimate the effects of risks. In the past years, increasingly dynamic vulnerability assessments were developed to display changes in vulnerability over time (e.g. in climate change, coastal vulnerability, and flood management). This implies that the dynamic influences of management strategies on vulnerability need to be considered in the selection and implementation of strategies. For this purpose, we present a strategy evaluation framework which is based on dynamic vulnerability assessments. The key contribution reported in this paper is an evaluation framework that considers how well strategies achieve a predefined target level of protection over time. Protection Target Levels are predefined objectives. The framework proposed is inspired by Goal Programming methods and allows distinguishing the relevance of time-dependent achievements by weights. This enables decision-makers to evaluate the overall performance of strategies, to test strategies, and to compare the outcome of strategies.
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Yixing Shan, Lili Yang, & Roy Kalawsky. (2014). Exploring the prescriptive modeling of fire situation assessment. 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. 60–64). University Park, PA: The Pennsylvania State University.
Abstract: One of the key assumptions in Endsley's three-level Situation Awareness (SA) model is the critical role of mental models in the development and maintenance of SA. We explored a prescriptive way of modeling this essential mental process of the fire incident commanders' fire ground assessment. The modeling was drawn from the Fast and Frugal Heuristics (FFHs) program, given the strong parallels between its contentions on ecological rationality and the environment demanding of the emergency response context. This paper addresses a number of issues being encountered in the attempt of our empirical investigation.
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Tobias Andersson Granberg, Sara Erlander, David Fredman, Lovisa Olovsson, & Emma Persson. (2022). Predicting Volunteer Travel Time to Emergencies. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 44–54). Tarbes, France.
Abstract: A model is developed, which can predict the travel time for volunteers that are dispatched as first responders to emergencies. Specifically, the case of lay responders to out of hospital cardiac arrest is studied. Positions from historical responses is used to estimate the real response times, which are used to train and evaluate the new travel time model. The new model considers the road network and the transport mode most likely used by the volunteers. The results for the new model are compared to a model used in an existing volunteer initiative. They show that the new model can make better predictions in 59.7% of the cases. This can be used directly as a base for improving the travel time estimates in existing volunteer initiatives, and to improve the input data to the continuously evolving volunteer resource management systems.
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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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