Tiago C. De França, Diogo Nolasco, Rafael Lage Tavares, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2014). A critical insight of the pope's visit to Brazil for the world youth day: Resilience or fragility? 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. 463–472). University Park, PA: The Pennsylvania State University.
Abstract: This work proposes a model to evaluate systems regarding their resilience in handling unexpected disturbances. To exemplify the use of the proposed model, we chose to analyze the World Youth Day (WID), an important event on the global scenario that happened this year in Rio de Janeiro, a city which will host big events in the next few years, like the World Cup and the Olympic Games. From this event, we chose two disturbances that stressed the system and had the possibility to cause a lot of problems to the event and the city, like the rains in Guaratiba and the arrival of the Pope's committee. After analyzing how the overall WYD organization deal with these disturbances we conclude that, besides the success of the event, the organization showed much more signs of brittleness than resilience.
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Till Sahlmüller, & Bernd Hellingrath. (2022). Measuring the Resilience of Supply Chain Networks. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 55–67). Tarbes, France.
Abstract: With increasing supply chain complexity, it gets more likely that disruptions ripple through the supply chain network, affecting supply chain performance. As the severity of disruptions depends on the supply chain network structure, it is important to assess the network structure in terms of its resilience. This article presents the results of a literature review (LR) to provide a comprehensive overview of measures used for evaluating the resilience of supply chain networks. The results indicate a wide range of measures applied in literature, focusing on either nodes, paths, or subgraphs of the network. The identified measures are compared regarding the structural characteristics they study and the aspects of supply chain performance they investigate.
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Tina Comes, & Bartel A. Van De Walle. (2014). Measuring disaster resilience: The impact of hurricane sandy on critical infrastructure systems. 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. 195–204). University Park, PA: The Pennsylvania State University.
Abstract: Modern critical infrastructure (CI) systems are tightly coupled, resulting in unprecedented complexity and difficulty to predict, limit and control the consequences of disruptions caused by hazards. Therefore, a paradigm shift in disaster risk management is needed: instead of focusing on predicting events, resilience needs to be improved as a basis for adequate response to any event. This paper starts from a definition of CI resilience that provides a basis for quantitative and qualitative decision support. For the quantitative modelling approach, which aims at measuring the resilience of individual CIs, we focus on two CIs of fundamental importance for disaster response: transportation and power supply. The qualitative framework details relations between CIs. The results of this research are illustrated by a case study that analyses the impact of Hurricane Sandy. The findings highlight the need for a framework that combines qualitative and quantitative information from heterogeneous sources to improve disaster resilience.
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Tina Comes, Valentin Bertsch, & Simon French. (2013). Designing dynamic stress tests for improved critical infrastructure resilience. 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. 307–311). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper outlines an approach to support decision-makers in designing resilient critical infrastructure (CI) networks. As CIs have become increasingly interdependent disruptions can have far-reaching impacts. We focus on the vulnerability of CIs and the socio-economic systems, in which they are embedded, independent from any initial risk event. To determine which disruptions are the most severe and must be avoided, quantitative and qualitative assessments of a disruption's consequences and the perspectives of multiple stakeholders need to be integrated. To this end, we combine the results of consequence models and expert assessments into stress test scenarios, which are evaluated using multi-criteria decision analysis techniques. This approach enables dynamic adaption of the stress tests in the face of a fast changing environment and to take account of better information about interdependencies or changing preferences. This approach helps make trade-offs between costs for resilient CIs and potential losses of disruptions clearly apparent.
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Tracey L. O'Sullivan, Wayne Corneil, Craig E. Kuziemsky, & Daniel E. Lane. (2013). Citizen participation in the specification and mapping of potential disaster assets. 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. 890–895). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Asset-mapping is a strategy used in disaster preparedness planning, however participation is typically limited to a small number of organizations with specific expertise related to disaster response. Broader strategies are needed to ensure identification of assets is comprehensive and to stimulate innovative thinking about which attributes of a community are potential assets for response and recovery. As part of The EnRiCH Project intervention, asset-mapping was used as a collaborative activity to promote identification of a broad range of assets which could be used to enhance resilience and promote preparedness among high risk populations. In this paper we present a study (in progress) which explores innovation and empowerment among a collaborative community group in Canada. Qualitative content analysis was used to analyze focus group transcripts from 2 sessions where the participants (n=18) learned how to use google docs and create a database of community assets, while developing collaborative relationships.
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Vangelis Pitidis, Joao Porto de Albuquerque, Jon Coaffee, & Fernanda Lima. (2022). Enhancing Community Resilience through Dialogical Participatory Mapping. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 495–503). Tarbes, France.
Abstract: Citizen generated data can play an important role in enhancing community resilience. However, the relationship between data and community resilience has only been partly addressed in existing resilience scholarship, predominantly from the perspective of data utilisation in response to unfolding crises. Yet, in this study we attempt to highlight a different pathway for data-enabled contributions to community resilience, focusing on the process of data generation and its capacity to constitute a transformative moment itself. By exploring the case of the marginalized flood-prone community of M’Boi Mirim in São Paulo, Brazil, we introduce the concept of dialogical participatory mapping, and we argue that the process of generating geospatial data can empower local communities and assist in nourishing a resilience spirit among community members.
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Viavattene Christophe, Priest Sally, Owen Damon, Parker Dennis, Micou Paula, & Ly Sophie. (2016). INDRA Model: For A Better Assessment of Coastal Events Disruptions. 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: Natural hazards such as extreme coastal events can generate indirect impacts extending far beyond the exposed areas and the direct aftermath of the event. The recognition of such impacts in risk assessment is essential for preparing, mitigating against such events and for increasing the resilience of coastal communities. However the assessment is often limited to the direct impacts. This paper proposes new methodologies for assessing the indirect impacts of coastal storm events. Eight impacts are considered in the approach: household displacement, a financial recovery of households and businesses, business supply chain disruption, ecosystem recovery, risk to life, utility and transport disruptions. These methodologies are incorporated in the open-source INDRA model (INtegrated DisRuption Assessment) to compare and identify hotspots at a regional using a multi-criteria analysis.
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Victor A. Bañuls Silvera, Rafael Cantueso Burguillos, Fernando Tejedor Panchón, Miguel Ramírez de la Huerga, & Murray Turoff. (2019). A Delphi approach for the establishment of the fundamental principles of an Organizational Security System in Public Administration. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: The aim of this work is defining fundamental principles of an Internal Security System in the presence of intentional risks in Public Administration. The relevance of this object of study has increased even more with the emergence of new terrorist groups and the proliferation of organized crime, which have been categorized as a maximum threat to Security by the government. This context has led to new regulations and legislation on Security matters at the national and international level to protect assets, people and the activity of the Administration itself. Despite the large number of regulations and relevance of this topic, there is not any study which defines in a comprehensive manner the requirements that a security system must have in the presence of intentional risks in Public Administration. The results of this work are intended to be a reference for the Public Administration, for the prevention and reaction to damage to people, property, and operation, intentionally caused by external agents, personnel themselves or users. These principles have been applied and validated through a Delphi process in the Administration of the Regional Government of Andalusia in which more than 40 security-related managers have participated.
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Victor A. Bañuls, Andrzej M. Skulimowski, & José Antonio Román Begines. (2021). Disaster Resilience Modeling of Municipal Water Supply Infrastructures in the Context of Atmospheric Threats. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 198–207). Blacksburg, VA (USA): Virginia Tech.
Abstract: The resilience of water supply infrastructure (WSI) is of utmost importance as threats to predominantly, although not exclusively, urban WSI may accompany virtually all kinds of natural disasters. In this paper, we present some of the challenges posed by climate change in modeling emergencies in WSIs. Climate change is a global phenomenon that significantly impacts global lifestyle. It is expected that increase in global temperatures causes sea levels to rise, increases the number of extreme weather events such as floods, droughts, and storms while highly impacting WSI. In this respect, the challenge is to be prepared for the unexpended by modeling various complex scenarios. Only with a multidisciplinary approach at the global, regional, national, and local levels, can success be achieved. We discuss some of the specific challenges posed by climate change in modeling emergencies in WSIs with a case study modeled using EMERTIC. EMERTIC is a software based on AI and scenarios, that is aimed at supporting decision making at different stages of the Emergency Management cycle.
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Vittorio Nespeca, Kenny Meesters, & Tina Comes. (2018). Evaluating Platforms for Community Sense-making: Using the Case of the Kenyan Elections. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 924–934). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The profusion of information technology has created new possibilities for local communities to self-organize and respond to disruptive events. Along with the opportunities, there is also a series of challenges that need to be addressed in order to improve societal resilience. One of these challenges is to make sense of the continuous stream of information to create a coherent understanding and improve coordination. The research presented in this paper focuses on the socio-technical requirements of IT platforms that support sense-making and coordination. Using a comprehensive evaluation exercise based on real data from the 2017 Kenyan elections, we examine the development, workflows and use of this shared situational awareness in a group decision making process. In this manner, we identify requirements for resilience platforms and identify further research directions.
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Xinyuan Zhang, & Nan Li. (2020). Assessment of the Correlation between Extreme Weather Event-Induced Human Mobility Perturbation in Urban Areas and their Spatial Characteristics based on Taxi Trajectories. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 366–380). Blacksburg, VA (USA): Virginia Tech.
Abstract: Extreme weather events (EWEs) are significant threats to urban regions. One major reflection of such impact is the EWE-induced perturbation to urban human mobility, which has been documented in a number of recent studies. This study aims to examine the spatial distribution of such perturbation within a city among different areas that are characterized by the type of function and the distance to city center. A case study was conducted on a major rainstorm in the City of Nanjing, China in 2017, based on trajectories of all taxis in the city before and during the rainstorm. It was found that the rainstorm caused decrease in people's travel demand throughout the city, although the magnitude of perturbation and level of resilience notably differed among areas of different functional types. In addition, the urban mobility in areas distant from the city center were relatively less influenced by the rainstorm.
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Yan Wang, & John E. Taylor. (2017). Tracking urban resilience to disasters: a mobility network-based approach. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 97–109). Albi, France: Iscram.
Abstract: Disaster resilience is gaining increasing attention from both industry and academia, but difficulties in operationalizing the concept remain, especially in the urban context. Currently, there is scant literature on measuring both spatial and temporal aspects of resilience empirically. We propose a bio-inspired quantitative framework to track urban resilience to disasters. This framework was built upon a daily human mobility network, which was generated by geolocations from a Twitter Streaming API. System-wide metrics were computed over time (i.e. pre-, during and post-disasters). Fisher information was further adopted to detect the perturbation and dynamics in the system. Specifically, we applied the proposed approach in a flood case in the metropolis of São Paulo. The proposed approach is efficient in uncovering the dynamics in human movements and the underlying spatial structure. It adds to our understanding of the resilience process in urban disasters.
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Yan Wang, Qi Wang, & John Taylor. (2021). Loss of Resilience in Human Mobility across Severe Tropical Cyclones of Different Magnitudes. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 755–765). Blacksburg, VA (USA): Virginia Tech.
Abstract: Severe tropical cyclones impose threats on highly populated coastal urban areas, thereby, understanding and predicting human movements plays a critical role in evaluating disaster resilience of human society. However, limited research has focused on tropical cyclones and their influence on human mobility resilience. This preliminary study examined the strength and duration of human mobility perturbation across five significant tropical storms and their affected eight urban areas using Twitter data. The results suggest that tropical cyclones can significantly perturb human movements by changing travel frequencies and displacement probability distributions. While the power-law still best described the pattern of human movements, the changes in the radii of gyration were significant and resulted in perturbation and loss of resilience in human mobility. The findings deepen the understanding about human-environment interactions under extreme events, improve our ability to predict human movements using social media data, and help policymakers improve disaster evacuation and response.
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Yang Zhang, William Drake, Yuhong Li, Christopher Zobel, & Margaret Cowell. (2015). Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy. 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: Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience.
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Yudi Chen, Angel Umana, Chaowei Yang, & Wenying Ji. (2021). Condition Sensing for Electricity Infrastructures in Disasters by Mining Public Topics from Social Media. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 598–608). Blacksburg, VA (USA): Virginia Tech.
Abstract: Timely and reliable sensing of infrastructure conditions is critical in disaster management for planning effective infrastructure restorations. Social media, a near real-time information source, has been widely used in the disaster domain for building timely, general situational awareness, such as urgent public needs and donations. However, the employment of social media for sensing electricity infrastructure conditions has yet been explored. This study aims to address the research gap to sense electricity infrastructure conditions through mining public topics from social media. To achieve this purpose, we proposed a systematic and customized approach wherein (1) electricity-related social media data is extracted by the classifier developed based on Bidirectional Encoder Representations from Transformers (BERT); and (2) public topics are modeled with unigrams, bigrams, and trigrams to incorporate the formulaic expressions of infrastructure conditions in social media. Electricity infrastructures in Florida impacted by Hurricane Irma are studied for illustration and demonstration. Results show that the proposed approach is capable of sensing the temporal evolutions and geographic differences of electricity infrastructure conditions.
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