2022
The Dark Side of the Metaverse – The development of key challenges and research agenda
Laurie Hughes & Yogesh Dwivedi (Swansea University School of Management UK)
The project explores some of the potential negative aspects of the widespread adoption of the metaverse. The metaverse has been described as a transformational immersive version of the internet that utilises Virtual Reality and avatars, blending the physical and virtual within an integrated ecosystem. Platform providers such as Meta Platforms have declared a commitment to developing a metaverse and have already launched Horizon Worlds in December 2021 – its own social virtual “social experience”. However, although the technical infrastructure has yet to be scaled to create the fully functioning metaverse, the societal impact from a fully functioning multi-platform immersive metaverse, could be far reaching. Researchers have already raised fundamental concerns regarding the potential impact on vulnerable people’s health, safety, and security within this new ecosystem and the risk of the big-tech architects creating the rules and policing infrastructure that could be woefully inadequate. Via the discussions and perspectives of an expert focus group – this project aims to develop a deeper analysis of the critical aspects of the metaverse that could detrimentally affect adults and children as they interact with the transformational features of this new ecosystem. This initiative will focus on the dark side of the metaverse helping to expose the many key vulnerabilities that could impact users and their data. The results from this project will help inform researchers with a clear agenda for future study, exposing the key research themes, contributing to the emerging body of knowledge on this important topic.
Understanding Algorithm Aversion in Medical Decision Making: A large scale cross-culture experiment of patient’s trust in AI.
Stefanie H. Gante & Spyros Angelopoulos (Durham University Business School, Durham University, United Kingdom)
The project explores the factors that can promote or impede the trust of patients in algorithmic solutions for clinical diagnostic decision-making. A frequently highlighted impediment for the adoption of such solutions is their lack of transparency and explainability. Recent studies, however, show that increased transparency on the inner mechanics of algorithms does not always increase the trust of beneficiaries, rather they can enhance their reservations. Such reservations appear to not be grounded in rational argumentation, but mainly in psychological factors. Consequently, whilst transparency and explainability can address the ethical and legal considerations for the use of algorithmic solutions in clinical diagnostic decision-making, they might not always promote the trust of patients in the adoption of such solutions, which questions the imperative of pushing for full enclosure of information to all stakeholders. Evidently, there is a lack of clarity and consensus regarding the concerns and needs of patients towards building their trust in algorithmic solutions for clinical diagnostic decision-making. The project, therefore, draws upon the theoretical underpinnings of algorithm aversion and information processing theory to study the perspective of patients in algorithmic solutions for clinical diagnostic decision-making by conducting large-scale, cross-cultural experiments to uncover factors that can promote or impede their trust in such solutions. The expected findings of the project will contribute to the better understanding of the barriers and drivers for the adoption of algorithmic solutions for clinical diagnostic decision-making, as well as to the discussions on human-algorithm interactions in healthcare, and in general.
2021
The role of Information Technology on the Affective Temporal Experiences of Remote Workers
Efpraxia Zamani (University of Sheffield) and Konstantina Spanaki (Audencia Business School, France)
The project focuses on remote workers and their temporal experience. The temporal dimension of remote work can be viewed through the lens of temporal structuring, which is largely driven by the impact virtuality has on decision-making, trust formation, and knowledge sharing. Existing research has focused on collaboration and coordination, and the role of technology in addressing these challenges. Yet, such practice-based approach emphasis time-at-work and thus tend to ignore time outside the organisation. To consider holistically remote workers’ temporal experiences, the project adopts the lens of chronopathic experience with the view to explore “How does technology influence the affective temporal experiences of remote workers, and how do these experiences impact on and shape their work?” The inquiry focuses specifically on knowledge workers who work remotely, and specifically on women scholars of varying career and life stages and diverse personal commitments in order to identify intersectional impacts.
TikTok as a blended learning tool
Aimee Jacobs (Craig School of Business, California State University, Fresno, USA)
The pandemic has shifted the delivery method of learning material as well as how and when students consume the material. Social media applications have emerged as one of the taken-for-granted ways for people to interact. TikTok, a popular social media application, has been incorporated in higher education, as well as outreach and widening participation in chemical education . Such effort has resulted in increased participation of learners. However, there is little focus on the effectiveness of TikTok as a learning tool on learner performance. This project aims to investigate how social media can assist blended learning by assessing the effectiveness of TikTok as a medium for learning. Statistics is the foundation for analytics and sense making of data and is deeply applicable to many disciplines, including information systems (IS). Many IS curriculum will include machine learning and other analytics courses, which normally require the fundamental understanding of statistics. For the purpose of this project, the statistical analysis taught via TikTok will be focused on the essential statistics via built in functions and the Data Analysis Toolpak in Excel.
The main impact will be an alternative method of delivering learning material that is proven to be better for consumption by students. The broader impact of the project should be reflected as blended learning is widely adopted everywhere, and not limited to any specific country nor discipline. Although this initial investigation focuses on statistical education, the results of this project can be applied to other IS related disciplines.
Assessing the value of DT enabled business model pivoting within SMEs in post COVID-19 era
Thanos Papadopoulos, Maria Balta, and George Saridakis (Kent Business School, University of Kent, UK)
This project assesses the value of Digital Technologies (DT)- enabled business pivoting within SMEs in post COVID-19 era. Pivoting may come as a solution to the SMEs’ need to develop their ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments and disruptions such as COVID-19, by focusing on current resources and capabilities and identifying ways to apply these to new opportunities. However, research has not acknowledged the importance of DT-enabled business model pivoting and how its value can be assessed. To address this research gap, this project draws on dynamic capabilities’ theory to address (i) how SME owners respond to the crisis created by COVID-19 pandemic; (ii) which business model pivot they adopt to survive and seize opportunities; and (iii) how the value of the business model pivots they adopt can be assessed. The study adopts a two-phase methodological approach: firstly, drawing on analysed data from semi-structured interviews with managers involved in the use of DT to deal with the challenges related to COVID-19; and secondly, via a survey with 300-500 SME owners. The study aims to shed more light on (i) how to select and assess the value of DT-enabled pivots; and (ii) how to encourage growth endeavours while considering firm specific characteristics, leading to higher employment and increased development of the UK economy in the post COVID-19 era.