Alkusaibati, W., & Pilemalm, S. (2023). Digitalized Co-production and Volunteerism in Emergency Response: a Literature Review. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 738–750). Omaha, USA: University of Nebraska at Omaha.
Abstract: ICT-enabled or digitalized co-production of public services has become increasingly relevant to emergency response and crisis management. This study provides a literature review on this phenomenon, exploring both large-scale crises and frequent emergencies. We found that research in the domain is scarce and focuses mainly on the phenomenon in terms of digital volunteerism. In large-scale crises, they mostly refer to spontaneous forms of volunteering, and in smaller emergencies, to more organized volunteers that collaborate with a response organization over time. Similarities to digitalized co-production in the public sector generally include financial, administrative, ICT, and demographic factors. Differences include, e.g., aspects of coordination, support, and processing by formal actors. We argue that there are benefits of adding a theoretical co-production perspective to digital volunteerism in emergency response and that our literature review can guide future research on models and (the double) use of volunteers in both kinds of emergencies.
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Björnqvist, A., Brodin, W., Friberg, M., & Berggren, P. (2023). Identifying Teamwork Processes in a Medical Command and Control Team During the COVID-19 Pandemic. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 711–720). Omaha, USA: University of Nebraska at Omaha.
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.
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Tikka, M., Ahsanullah, R., Varanasi, U., Härmä, V., Sawhney, N., & Leinonen, T. (2023). Contextual Inquiry of Affordances for Collaboration in Crisis: Lessons from the Finnish Context. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 33–42). Omaha, USA: University of Nebraska at Omaha.
Abstract: The COVID-19 pandemic followed by the energy crisis in Europe demonstrates how complex crises can be. Being embedded in a digital media environment and global interdependencies, complex crises elude straightforward interpretations and explanations. Nonetheless, crises require fast and coordinated response from multiple public authorities. In recent years, advances in computational methods and information technology have influenced the field of crisis and disaster management, and diverse technical approaches have been developed to enhance authorities’ response to crises. Drawing on a relational approach to crises, we investigate the socio-technical affordances emerging in Finland to facilitate multi-actor collaboration in crises. Based on our analysis, we argue that contemporary practices and technologies do not match with the complexity of recent crises. Taken together, we consider the role of digital technologies and socio-technical practices to better support multi-actor sensemaking and collaboration in future crises.
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Kees Boersma, & Robert Larruina. (2021). Restoring the Medical Supply Chain from Below: The Role of Social Entrepreneurship in the Production of Face Masks during the Covid-19 Crisis. 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. 260–269). Blacksburg, VA (USA): Virginia Tech.
Abstract: The COVID-19 pandemic hit societies all over the world deeply. Since it has affected societies worldwide and compromised socio-technical systems across geographical, judicial and administrative borders it can be considered a cross-border, transboundary crisis. This dimension has exposed the global medical supply chain's vulnerability. Due to its 'lean and mean' characteristics the supply chain was unable to function adequately during the crisis and formal authorities struggled to restore it, causing serious problems in the response to the pandemic. At the same time, numerous initiatives from below tried to give a (partial) answer on how to restore the broken supply chain. This paper presents a case study about a Dutch social enterprise (i.e. the Refugee Company) engaged with the cross-border dimension of the COVID-19 crisis. The Refugee Company set up a supply chain, operation and (domestic) production of personal protection equipment (PPE) materials, in particular face masks. The paper draws on data collected through qualitative methods, including document analysis (secondary sources), interviews and observations. The conclusion is that social entrepreneurs and enterprises played a crucial role in restoring the supply chain. The paper provides valuable lessons for both policy makers and crisis managers: there is great potential in recognizing the entrepreneurial activities from below in strengthening supply chains at times of crisis, potentially making them more sustainable and resilient.
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Alan Aipe, Asif Ekbal, Mukuntha NS, & Sadao Kurohashi. (2018). Linguistic Feature Assisted Deep Learning Approach towards Multi-label Classification of Crisis Related Tweets. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 705–717). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Micro-blogging site like Twitter, over the last decade, has evolved into a proactive communication channel during mass convergence and emergency events, especially in crisis stricken scenarios. Extracting multiple levels of information associated with the overwhelming amount of social media data generated during such situations remains a great challenge to disaster-affected communities and professional emergency responders. These valuable data, segregated into different informative categories, can be leveraged by the government agencies, humanitarian communities as well as citizens to bring about faster response in areas of necessity. In this paper, we address the above scenario by developing a deep Convolutional Neural Network (CNN) for multi-label classification of crisis related tweets.We augment deep CNN by several linguistic features extracted from Tweet, and investigate their usage in classification. Evaluation on a benchmark dataset show that our proposed approach attains the state-of-the-art performance.
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