Abstract: The goal of this industrial PhD is to investigate how to include resilience into a cyber-security strategy to safeguard vital infrastructure. Critical infrastructure is increasingly susceptible since businesses are using technology more often. These infrastructures are also components of a vast, integrated, and increasing digital supply chain that transcends national boundaries, adding to the difficulties. A bigger attack surface where an attacker might use vulnerabilities contained in suppliers' and sub suppliers' chains could come from this extension of the digital supply chain. The study will add to our understanding of how to manage intricate supply chains in critical infrastructure with stringent dependability requirements. The digitalization processes in the supply chain include changes to the organizational structure, necessitating a robust strategy for continual improvement. The research question for this project is as follows: How can a resilience framework contribute to managing the complex digital supply chain for stakeholders in the power industry? The system dynamic (SD) approach will be used to generate a simulation based on the findings from each of the methods. Previous supply chain research has demonstrated that SD modelling is an effective strategy for building resilience in supply networks. To comprehend and examine the behavior of dynamic and complex systems, the notion of SD was established. The theory of system dynamics is based on the idea that actions done in systems will change the system, which will then lead to new actions. To collect primary data the qualitative method chosen as most suitable the semi-structured interview. To understand a social phenomenon, one needs to listen to people who reflect on their own experiences, knowledge, and motivation. Through interviews, it is possible to go into depth on the phenomenon and gather complex and rich data that is not available through literature review only. Contributions from this Ph.D. study are grouped into two categories: academia and organization. Further understanding regarding supply chain vulnerability and the implementation of potential techniques and ideas in novel contexts are academic contributions. The development of the resilience framework, which aims to address the difficult problem of managing stakeholders in the digital supply chain, is a contribution made by the organizations. The goal for CIs is to have resilient DSCs that can withstand and improve from high-pressure situations. Improving DSC resilience requires an understanding of the supply chain network that includes suppliers’ and their sub-suppliers’ incentives, all the way to its downstream customers’ incentives. By understanding the structure of the system, the ability to ascertain the behavior of the system increases, providing opportunities to better manage the system. If we can harness the positive incentives for collaboration and social connection the road to a more resilient CI that is available when the society require it becomes easier.

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.

Abstract: Cross-border regions are particularly exposed to hazards and require cooperation for Disaster Risk Reduction (DRR). Accordingly, multiple countries have been investing in technology and jointly innovate to share and process data against disasters. However, these countries’ capacity to share data depends on the history and the context of the border itself. Going further, conflicts between countries – may they be past, present or future – can radically question and endanger collaborative efforts to share data for DRR. This collaborative research, involving a cohort of master students and an NGO, explores the influence of conflicts on data sharing and cooperation for DRR. Still in progress, this research examines how conflicts affect data sharing and how DRR actors manage them. It is based on exploratory archive analysis of three distinct cases of cross-border DRR collaboration within the EU borders, as well as experts and actors interviewing. Preliminary findings reveal that conflicts affect DRR at three levels: i) actors, ii) interactions with DRR actors, iii) relations between local DRR actors and institutions. The expected contribution of this research is theoretical, practical and pedagogical.

Abstract: In this paper, we develop a model with neural networks to localize events using microblogging data. Localization is the task of finding the location of an event and can be done by discovering event signatures in microblogging data. We use the deep learning methodology of Bi-directional Long Short-Term Memory (Bi-LSTM) to learn event signatures. We propose a methodology for labeling the Twitter date for use in Bi-LSTM However, there might not be enough data available to train the Bi-LSTM and learn the event signatures. Hence, the data is augmented using generative adversarial networks (GAN). Finally, we combine event signatures at different temporal and spatial granularity to improve the accuracy of event localization. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.

Abstract: Virtual Reality (VR) is often used for its ability to mimic reality. However, VR can also be used for its ability to escape reality. In that case, on the one hand VR provides a visualization environment where the user’s senses are still in a familiar context (one can see if something is in front, behind, up, down, far or close), yet on the other hand, VR allows to escape the usual limits of reality by providing a way to turn abstract concepts into concrete and interactive objects. In this paper, the dynamic management of a complex industrial system (a supply chain) is enabled in a VR prototypical environment, through the management of a physical trajectory that can be deflected by the impact of any potentialities such as risks or opportunities, seen as physical objects in the performance space.

Abstract: Many organizations train and educate their staff to prepare for crisis. One approach is train-the-trainer (ToT; Training of trainers) concept. It is based on the idea that someone can be trained as a trainer, who in turn train their colleagues. The philosophy resembles a pyramid scheme that allows for a fast and efficient spread of knowledge and skills. This study focused on perceptions of the ToT concept through interviews with ToT trainers. Two learning theories, organizational learning (4I) and experiential learning theory (ELT) were used to conceptualize the ToT-concept. It was found that the ToT-concept can be used as the method to conduct ELT to achieve organizational learning and knowledge (4I). Furthermore, the study also presents how participants perceives ToT using thematic analysis. This resulted in four themes: Common understanding of ToT, Learn-by doing, No grounding in ToT, and Difficult to ensure quality.

Abstract: This paper presents an ethnographic study consisting of non-participatory observations of a Swedish regional medical command and control team during their crisis response to the COVID-19 pandemic. The field-notes from the observations were analyzed using a deductive content analysis with categories representing teamwork processes. The content analysis showed that the studied regional medical command and control team was engaged in all but one of the predefined teamwork processes. Furthermore, the content analysis also added to the understanding of the regional medical command and control team’s work procedures by emphasizing how the team was engaged in the different processes. Lastly, the content analysis also made it possible to identify potential developmental needs of the studied regional medical command and control team.

Abstract: An active shooter event is one of the most complicated situations a police officer could face. Today the standard procedure for an active shooter event is to enter the scene and try to prevent casualties. This involves taking great risks and puts the police officers in a situation they have not been trained for. This is a work in progress paper where the long-term goal is to develop modern technology that could increase the chance of saving lives and decrease the risk of being injured or killed during an active shooter event. Six active shooter event exercises taking place in Sweden have been studied using an ethnographic field study approach. Four themes have been identified where we argue that technology could enhance the police mission: A) Situational awareness; B) Decision making/prioritization; C) Localization of both sound and people; D) Decreasing time of intervention.

Abstract: The proliferation of natural and artificial disasters in the last decades has made urban resilience enforcement a strategic goal of city governments worldwide and a hot research topic for academics and practitioners. Consequently, several urban resilience assessment and improvement frameworks have been proposed. Some frameworks have associated operational tools, but these systems are not interoperable with other frameworks' utilities, forcing cities to use different tools for evaluating various aspects of resilience. Since data must be converted manually from one tool to another, the conversion may be error-prone and tedious. In this paper, we report the steps toward defining an urban resilience metamodel that intends to be at the core of a multi-framework urban resilience management portal. Our goal is to provide city administrators with a single operational tool able to evaluate resilience according to different frameworks, thanks to the definition of semantic interoperability mechanisms between the frameworks and the metamodel

Abstract: Crisis Named Resources (or CNRs) are social media pages and accounts named after a crisis event. Using the COVID-19 Pandemic as a case study, we identified and examined the role of CNRs that shared humor on Twitter. Our analyses showed that humor-based CNRs shared virus-related rumors, stigma, safety measures, opinions, sarcasm, and news updates. These resources also shared the overall anger and frustration over the year 2020. We conclude by discussing the critical role of humor based CNRs in crisis response.

Abstract: Disaster risk management practitioners have the responsibility to make decisions at every phase of the disaster risk management cycle: mitigation, preparedness, response and recovery. The decisions they make affect human life. In this paper, we consider the current state of the use of AI in information extraction (IE) for disaster risk management (DRM), which makes it possible to leverage disaster information in social media. We consolidate the challenges and concerns of using AI for DRM into three main areas: limitations of DRM data, limitations of AI modeling and DRM domain-specific concerns, i.e., bias, privacy and security, transparency and accountability, and hype and inflated expectations. Then, we present a systematic discussion of how explainable AI (XAI) can address the challenges and concerns of using AI for IE in DRM.

Abstract: While multilingual translation needs (from one or more language(s) to one or more others) in disaster events are a “perennial issue” among responders in crisis-affected communities (Crowley & Chan, 2011) and calls are being made to consider the access to (and translation of) information during crisis a human right (Greenwood et al., 2017), the literature that deals with intralingual translation in disaster is limited in places where it should thrive, such as crisis communication, translation studies, and rhetoric. Intralingual translation is of increasing relevance in disaster not only because of potential variability in literacy levels among those affected (O’Brien, 2020) but because responding to/planning for disaster requires an understanding of the ‘operational’ terms used (but not always shared) by other responding agencies in the field. This paper calls for increased attention to intralingual translation needs in disaster and introduces a translation technology (“Aphorme”) designed to mitigate those needs.

Abstract: Emergency managers rely on formal and informal communication channels to identify needs in post-disaster environments. Message retransmission is a critical factor to ensure that help-seekers are identified by disaster responders. This paper uses a novel annotated dataset of Twitter posts from four major disasters that impacted the United States in 2021, to quantify the effect that expressed emotions and support typology have on retransmission. Poisson regression models are estimated, and the results show that messages seeking instrumental support are more likely to be retransmitted. Expressions of anger, fear, and sadness increase overall retweets. Moreover, expressions of anger, anticipation, or sadness increase the likelihood of retransmission for messages that seek instrumental help.