Introduction to Communication and Information Systems Technology for Crisis and Disaster Management Minitrack

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Crowd sourcing challenges assessment index for disaster management

Emergency agencies (EA) rely on inter-agency approaches to information management during disasters. EA have shown a significant interest in the use of cloud-based social media such as Twitter and Facebook for crowd-sourcing and distribution of disaster information. While the intentions are clear, the question of what are its major challenges are not. EA have a need to recognise the challenges in the use of social media under their local circumstances. This paper analysed the recent literature, 2010 Haiti earthquake and 2010-11 Queensland flood cases and developed a crowd sourcing challenges assessment index construct specific to EA areas of interest. We argue that, this assessment index, as a part of our large conceptual framework of context aware cloud adaptation (CACA), can be useful for the facilitation of citizens, NGOs and government agencies in a strategy for use of social media for crowd sourcing, in preventing, preparing for, responding to and recovering from disasters. © (2012) by the AIS/ICIS Administrative Office All rights reserved

From knowledge co-creation to value co-creation and beyond: challenging global emergency in smart service systems.

The study seeks to investigate the impact of pandemic on teaching and learning processes involved in Higher Education (HE) by analysing the way in which knowledge exchange and value co-creation are reframed through ICTs and technology. The adoption of the interpretative lens of Service Science permits to reread HE as a smart service system. The empirical research, based on content analysis as an inquiry, analyses: 1) the transformations introduced in technology adoption, information sharing, knowledge and value co-creation to comply with the disruption “imposed” by the the sanitary emergency; 2) the way in which this transformation can introduce novelties in Higher education system. The results identify the different drivers for value and knowledge co-creation that can be implemented in technology-enhanced teaching and learning and the different novelties that can be generated from the emergence of innovation

Knowledge, Innovation, and Entrepreneurial Systems at HICSS

This paper presents an overview and history of the knowledge, innovation, and entrepreneurial systems (KIES) track and the knowledge and related systems research community at the Hawaii International Conference on System Sciences (HICSS). This community began as a task force that examined organizational memory in HICSS-27. It has since evolved into a mini-track, a research cluster, and, finally, a full research track that encompasses research knowledge, innovation, and entrepreneurial systems. In this paper, we acquaint knowledge system researchers with a research community that has leveraged HICSS to develop a rich history of high-quality scholastic inquiry in the knowledge system, knowledge management, innovation systems, entrepreneurial systems, organizational memory, and organizational learning research areas

Go for it: Where IS researchers aren’t researching

This viewpoint article describes two research topics under-researched by Information Systems (IS) researchers: Robotics and IT addiction. These topics offer great potential for IS researchers in terms of business and societal impacts and it would behoove IS researchers to study them more fully. The aspects of the research topics that are related to IS are discussed and potential research areas and questions are suggested

Go for it: Where IS researchers aren’t researching

This viewpoint article describes two research topics under-researched by Information Systems (IS) researchers: Robotics and IT addiction. These topics offer great potential for IS researchers in terms of business and societal impacts and it would behoove IS researchers to study them more fully. The aspects of the research topics that are related to IS are discussed and potential research areas and questions are suggested

Biology-inspired Architecture for Situation Management

Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft

Towards explaining user satisfaction with contact tracing mobile applications in a time of pandemic: a text analytics approach

This research project investigates the critical phenomenon of the post-adoption use of Contact Tracing Mobile Applications (CTMAs) in a time of pandemic. A panel data set of customer reviews was collected from March 2020 to June 2021. Using sentiment analysis, topic modeling and dictionary-based analytics, 10,337 reviews were analyzed. The results show that after controlling for review sentiment and length, user satisfaction is associated with users’ perception of utilitarian benefits of CTMA, their CTMA-specific privacy concerns, and installation and use issues. Our methodological approach (using various text analysis techniques for analyzing public feedback) and findings (influential factors on consumers’ satisfaction with CTMA) can inform the design and deployment of the next generation of CTMAs for managing future pandemics