ABSTRACT. Companies don’t transform, people transform companies. However, there is still a pressing need to understand ‘what’ action a Digital Transformation (DT) leader needs to take and ‘how’ they should enable that action, in order to achieve the best possible outcome in a DT initiative. Therefore, this paper explores the underlying practices associated with DT leadership in the context of pre-digital organisations. We set about understanding these underlying practices uniquely, using a grounded approach, analysing sixteen key informant’s accounts of the ‘what’ and ‘how’ of DT leadership. In total we identify six underlying practices (collaborative change, digital influence, collaborative tooling, employee spirit, prioritised platformitisation, democratising data) that impact on the outcome of a DT initiative within a pre-digital organisation. We believe that our approach strengthens the relevance of our research outputs for practitioners, where the practitioner voices and their lexicon are central to the theorising and the outputs produced.

ABSTRACT. Digital transformation endeavours can become a facade due to inertia, and thus, they are increasingly perceived as failed, giving rise to concerns for practitioners as well as ongoing debates in the extant literature, which highlights the need to better understand the phenomenon. To address that lacuna, we explore the technology adoption process for enabling fundamental change in existing organizational systems in terms of internalization and inertia. In doing so, we conduct an empirical study at a stated-owned engineering organization to derive a process model. Our work contributes to the extant Information Systems literature by elucidating the internalisation process of digital technologies, further providing a systematic framework incorporating perspectives of inertia and internalisation. We discuss the anticipated findings as well as the implications of our work for theory and practice, and we delineate an agenda for future research on the topic.

ABSTRACT. High quality public spaces are promoted in the UK on the ground that they facilitate social mix and contribute to cohesive communities. Although widely endorsed in both academic literature and policymaking, there is little evidence to critically evaluate how the relationship between public space and social cohesion is captured within UK policy contexts. In this work-in-progress paper, we address this gap by conducting a short review of UK policies and propose a methodology to understand the social outcomes of planning policies using crowdsourcing information combining citizen science activities (participatory photo elicitation and collaborative field survey) and Volunteered Geographic Information (OpenStreetMap). The outcome of this ongoing study will fill the information gap in linking public space and social cohesion policies in the UK context and contribute to the data-driven solutions in understanding the social outcomes of planning policy.

ABSTRACT. Small and Medium-sized Enterprises (SMEs) globally confront significant challenges amid rapid technological advancements. Particularly in developing nations, these businesses encounter unique hurdles in embracing digital transformation due to limited financial resources, a lack of awareness about its implications, and a deficit in technological expertise. This research, using Oman as a case study, introduces an empirically grounded digital transformation framework tailored to the specific needs of SMEs in these regions. Innovative concepts such as the "digital transformation canvas" and "digital interaction" serve as foundational elements in this framework. Developed through design science research, the digital transformation canvas offers a practical model with nine key components: ecosystem, strategy, people, technology, innovation, revenue, customer (external interactions), internal operations (internal interactions), and continuous development. This framework aims to provide a valuable roadmap for SMEs in developing countries, guiding them to thrive in the digital age despite their limitations.

ABSTRACT. This paper advocates for an existentialist viewpoint that recognizes time as both objective and subjective, allowing for an exploration of the emotional dimension of time. Utilizing a study involving remote workers, the research investigates affective temporal experiences, the role of technology in mediating these encounters and the emerging observed behaviours. Inspired by Existentialism and the Negative Theology of Time, the central research question addressed is: "How does technology influence chronopathic experience?" This approach extends beyond conventional productivity concerns to understand how technology commodifies personal time and shapes distinct temporal experiences.

ABSTRACT. Instant messaging (IM) has been found to support both synchronous and asynchronous learning in Higher Education Institutions (HEIs), but the efficacy of this approach is heavily reliant on staff adoption. Related work has focussed on the effect of IM on learners; frequency of usage, perception of usefulness, and its relationship with academic performance. However, this research will explore the extent to which IM is adopted in HEIs and the perceptions of academic staff towards the use of IM to support learners. Furthermore, it examines the impact of IM on stress and academic workload. Therefore, this work aims to identify and classify the barriers that hinder academic staff from incorporating IM into their practice. This Research in Progress paper sets out the background, rationale, and theoretical frameworks for this study. This work intends to contribute insight for Higher Education institutions aiming for optimal adoption of IM for inter-staff and student-staff communication

ABSTRACT. The UK has suffered declining growth in productivity over many decades and there have been several attempts to understand the reason, why? Various potential reasons including the transition to lower productivity sectors and the lack of sufficient high-skilled workers have been suggested to explain the productivity puzzle. One factor affecting productivity is firm investment in technology, an area where the evidence remains decidedly mixed. This paper presents the background to an ongoing UKRI (UK Research and Innovation) funded project, investigating the link between technology adoption, decision making and in-firm productivity. The project proposes to pair organisations with high productivity with organisations with low productivity and seeks to find out whether mentoring between senior management teams from the high productivity category can yield a positive outcome for organisations with lower productivity. The researchers are currently recruiting firms to form the mentor-mentee pairs and the results will be presented at the conference.

ABSTRACT. Automatic first impression estimation has garnered increased attention in recent years due to its potential applications in various fields. However, the momentum of this research is hampered by the significant lack of specialized datasets. Existing datasets largely focus on facial features, leaving out other critical elements that play a pivotal role in forming first impressions. Addressing this gap, we introduce the First Impression Static Appearance Dataset (FISAD). This comprehensive dataset comprises 6000 full-body images, each meticulously annotated with the Big Five first impression traits. Notably, FISAD opens up a new dimension for investigation, spotlighting the often-overlooked influence of clothing in first impression formation. Researchers can now delve deeper into understanding how attire interacts with and influences people's initial perceptions, paving the way for richer, more holistic studies in the realm of first impression estimation.

ABSTRACT. The paper reports on a three-stage research design pursued to uncover the shared understanding of practices linked to the execution of a Data &Analytics (D&A) strategy, within the *MULTINATIONAL-ANONYMOUS-FOR-REVIEW* AME (Africa and Middle East) region. This research uses the Data Value Map (DVM) to present a visualised representation of the “lived experiences” of ten key informants. These key informants represent a snapshot of the important roles constituting the D&A team within the *MULTINATIONAL-ANONYMOUS-FOR-REVIEW* AME region. The DVM analysis reveals eight ‘black boxes’ that represent the most frequently occurring topics of conversation across the ten key informant interviews. A reflection (by the Head of Data & Analytics for the AME region) on the impact of these ‘black boxes’ on the execution of the D&A strategy is also presented. The paper concludes with a sense of the practical implications linked to this applied research approach.

ABSTRACT. Traditional return on security investment (ROSI) models often emphasize investment costs and anticipated returns but overlook risk-related factors and qualitative cybersecurity metrics. To address this oversight, this paper employs an aggregation strategy that integrates five selected qualitative and quantitative metrics with the Factor Analysis of Information Risk (FAIR) model for risk analysis and quantification. The study pioneers the fusion of FAIR-ROSI models, combining practical qualitative and quantitative indicators to enhance the granularity of the traditional ROSI model. A case study is utilized to evaluate the proposed metrics. Empirical data from pre- and post-control measures reveal a narrow margin between actual and projected loss values and a significantly higher ROI compared to total security expenditure. The integration of FAIR model and ROSI model addressed the limitations found in traditional ROSI models concerning risk assessment. Such integration fosters a holistic approach to ROI and risk management, thereby facilitating informed decision-making.

ABSTRACT. Recommender systems suggest items pertinent to users based on signals extracted from ratings, clickstreams, descriptions, or other relevant data. This paper aims to develop a novel matrix factorisation-based approach to design recommender systems. The proposed model combines the recommendation lists generated based on explicit ratings, positive implicit feedback, and negative implicit feedback, respectively. Further, the context-aware version of the model filters out irrelevant items from the recommendations. When applied to the SUSHI preference dataset, the proposed model performs better than the baseline matrix-based models and the state-of-the-art neural embedding models for metrics NDCG (Normalised Discounted Cumulative Gain) and NDCG@10. The context-aware version of the proposed model performs better than the context-unaware version. Thus, this model can be implemented instead of the other models in cases where NDCG is vital. We plan to implement this model on other datasets to improve the generalizability of the results.

ABSTRACT. The increased adoption of algorithmic solutions into existing pathways provides opportunities for freeing up experts’ capacities and improving outcomes by delegating decision-making to such solutions. The literature, however, paradoxically suggests that experts are reluctant to delegate low-uncertainty decisions to algorithmic solutions, while their willingness to delegate increases for high-uncertainty ones. We refer to this phenomenon as the ‘delegation paradox’ and we attempt to further unpack it by drawing upon the theories of algorithm aversion and algorithm appreciation in the frame of a two-phase study, incorporating interviews and experiments. The anticipated findings of our study will contribute to the literature on algorithm aversion and algorithm appreciation and bear sorely needed insights for practice on human-algorithm interactions, as well as on decision delegation in the face of uncertainty.

ABSTRACT. Artificial intelligence (AI) has seen rapid development in recent years and it has increasingly applied to various fields. Research is no exception. However, there is much to be explored in this domain. This study aims to explore the suitability of current generative AI applications for research purposes. The focus is on the generative AI’s capability to synthesise information as a potential alternative or supplement to human-based information synthesisation. In order to evaluate the effectiveness of the thematic analysis produced by generative AI, this study compares the generative AI-produced results by ChatGPT with human-generated results, based on the same set of papers. The results show generative AI produced very similar results to humans, in terms of the topics themselves and the number of topics identified. However, there are also some minor mismatches between generative AI and human results.

ABSTRACT. An increasing body of research on cross-boundary collaboration is investigating how digital artefacts (e.g., 3D representations, data visualisation), when viewed as boundary objects, influence group dynamics and collaborative performance. Central to this conversation is the inter-team and interpersonal communications mediated by such digital artefacts. We investigate large-scale construction projects based on Building Information Modelling (BIM), where multiple stakeholders collaborate across a variety of organisational and disciplinary boundaries. BIM is a process-based virtual representation shared by project team members in their collaboration. The promise of its efficacy as a boundary object lies within its capability of affording ‘model-oriented’ communications. To understand this process, we draw on the literature of semiotics to analyse how virtual representations are used to signify objects, meanings and processes during communication practices.

ABSTRACT. The philosophy of Agile development has been hugely influential in the software development and other fields, at the same time, Design Thinking has been widely embraced by many leading companies, promising better user-centred innovation, and design. There are still pragmatic difficulties in making both operational. In this paper, we suggest the use of modern generative AI systems, underpinned by Foundation Models, to help designers operationalise the Agile philosophy, and its manifestation in the Agile process models, and put Design Thinking into practice more cost-effectively and thoroughly by leveraging foundation models, tuned with the target substantive domain, to help in ideating and selecting the most optimum experiments, and in prioritising the selection and roll-out of features, embodied in user stories in the various hierarchical levels.

ABSTRACT. This paper aims to investigate digital inclusion network building as a mechanism for reducing digital poverty. Analysing a rural digital inclusion network in the UK, and drawing on Network Weaving Theory (Holley, 2013), this case study analyses how people’s roles and places play a big part in both the construction and growth of the network, as well as in the advancements of its initiatives. The contribution of this study is significant.Theoretically, this research builds on the literature on contextual conditions to digital access and adoption, and proposes a novel theoretical framework to unpack the complexity of digital inclusion network building - based on Holley’s theory. Results will inform UK regional organisations’ practices for establishing effective digital inclusion networks in post-pandemic, ‘digital by default’, and cost of living crisis times in the country. It will also provide recommendations for national policies to strengthen the resilience and sustainability of digital inclusion provision.

ABSTRACT. During the pandemic, the Higher Education had to rapidly adapt to new ways of working with both staff and students having to swiftly work in a remote environment for a prolonged period. This research is focusing on how women in academia within the Higher Education environment in the UK have adapted to virtual working and online teaching and learning and in what way they were affected by the pandemic in their professional and home life. For the purposes of this study, my research approach is to investigate women in academia perspectives during the transitional period from face-to-face onto e-learning and the mechanisms that they have used, in order to endure the challenges of work and everyday life.

ABSTRACT. The objective of this paper is to present a Simple Hermeneutics-inspired Learning Analytics Model for Modules (SHLAM²). Through a series of weekly learner self-assessments, as part of a 5-credit research methods module (for doctoral students) delivered over 12-weeks in an Irish Higher Education Institution (HEI), three patterns of learning are examined, namely: Seeking Clarity, Building Confidence, and Finding Voice. Our SHLAM² insights reveal that ‘Seeking Clarity’ (through reading and re-reading papers) is the strongest pattern of learning, while ‘Building Confidence’ (through evaluating an evolving design artefact) and ‘Finding Voice’ (through peer-led discussion and in-class presentations) are consistently lower throughout the delivery of a 12-week module. Furthermore, we provide an ‘engagement assumption vignette’ which highlights the value of “show & tell” sessions in a module design as opportunities to ‘see’ and ‘celebrate’ a learner’s progress and as challenges to module lecturer assumptions around learner engagement.

ABSTRACT. The rise of generative AI (GAI) is affecting various sectors, including higher education (HE). In HE, educators are grappling with students' use of GAI, which might infringe upon academic integrity. Given the pervasiveness of this technology, particularly through free AI tools, it should be utilised for its benefits rather than merely blocked. Thus, responsible use of AI in higher education is essential. However, encouraging students to openly declare their use of AI in summative assessments, for transparency purposes, has led to fears of negative perception and potential marking down by teachers. There is currently limited research in this area. Hence, this study aims to explore the boundary of students using GAI in assessments by gathering views from teachers through an exploratory survey. It contributes theoretically to responsible AI literature, extending it to HE, and practically by developing guidelines for AI use in student assessments, potentially informing university policy.

ABSTRACT. This paper explores factors influencing the adoption of generative AI (GenAI) among employees in China endeavouring to alleviate the excessive overtime work culture. Built on UTAUT and the institutional theory, a research model examines adoption determinants at the individual (performance expectancy, effort expectancy, personal innovativeness and trust), the organisational (social influence, facilitating conditions, organisational innovation climate), and the national (AI policy landscape) levels. A survey methodology will collect data from Chinese employees across industries. The paper argues GenAI can augment human capabilities and automate repetitive tasks, enabling employees to focus on creative, strategic activities and restore work-life balance. By revealing multi-level drivers of GenAI adoption, theoretical contributions include extending technology acceptance research to emerging GenAI while providing practical implications for organizations undergoing AI transformation. As one of the first examinations of employee GenAI adoption in the Chinese context, this study provides timely insights into harnessing AI’s benefits for workers' well-being.

ABSTRACT. This paper explores the adaptation of social workers to digitally mediated communication with their clients, amidst the constraints imposed by the COVID-19 pandemic. Focusing on the centrality of interpersonal relationships to social work, we examine how social workers in the UK and Hong Kong adapted to the transition from face-to-face meetings with clients to remote interactions via various computer-mediated communication channels. Through interviewing 37 social workers, we analyse the tension between maintaining close interpersonal relationships, and satisfying the need for task efficiency and regulatory compliance. Our findings reveal that social workers employed a strategic mix of digital media to fulfil both interpersonal and impersonal communication motives. We propose an integrative theoretical framework which links the dimensions of interpersonality—impersonality and agency—communion to understand how social workers’ communication media uses co-evolve with multiple communicational motives. This research contributes to understanding the transformative implications of digital media on professional practices in relationship-centric work.

ABSTRACT. Social media has democratised strategic communication. Strategists are adopting social media in their (digital) work as they evolve from the being discreet decision-makers operating behind the scenes to becoming prominent communicators at the forefront of strategic discourse. With this practice change, strategists must possess language skills to help others make sense of strategic issues, subsequently influencing stakeholder sensemaking in a desired direction. This paper asks how strategists are adopting social media for sensemaking on strategic issues. Our netnography research is conducted using the social media posts of strategists in FTSE 100 companies. The preliminary finding shows linguistic features such as expressed emotion and rhetoric are prominent in our data. We conclude with some emerging contributions where this work-in-progress intends to extend prior research by advancing understanding of specific discursive forms of strategic sensemaking afforded by social media.

ABSTRACT. Recent rapid developments in Artificial Intelligence (AI) have led many observers to believe we are on the cusp of a revolution, with AI poised to have an enormous impact upon societies and economies. However, many challenges must be met before AI can safely and fairly fulfil its potential. Blockchain is a set of inter-related, interconnected technologies that allow for the development of a range of socio-technical constructs such as data markets and prediction markets which have unique attributes and capabilities such as data immutability and designable anonymity and privacy. This research explores how these attributes and capabilities of these systems could be leveraged to address some of the challenges in AI development.

ABSTRACT. The proliferation of Artificial Intelligence (AI) systems with adaptive features has provided businesses and Society numerous benefits. Nevertheless, a growing body of literature has discussed the ethical issues these systems pose and the responses of human agents. Through a systematic literature review, we analyse and synthesise the existing literature on AI ethics and suggest new directions for further research in this area. There is a need to investigate the AI developers' stance on ethics, as the lack of transparency and accountability in the AI domain has sparked new debates and tension between AI performance, explainability and accountability. The deployment of AI systems affects Human role identities and reputations. Consequently, there is an increasing demand for explainable AI, interdisciplinary co-design processes, and ethical codes of conduct, and there is an urgent need to identify methods of accelerating AI developments without compromising human rights of autonomy and agency.

ABSTRACT. Advances in generative Artificial Intelligence (AI), hardware, notably the Internet of Things (IoT), smart phones, and software, especially Machine Learning (ML) and social media, are creating new ethical challenges globally. Digital ethics challenges impact Information Technology (IT) professionals. IT professionals and managers are jointly responsible for ensuring that digital data are captured, stored, processed, and used in an ethical manner. Digital ethics questions are often “wicked” problems for multiple stakeholders. This article defines what is meant by digital ethics and digital trust and explores five primary “wicked” problems and dilemmas associated with digital ethics. By evaluating the dilemmas associated with making ethical decisions related to data, principles and strategies are proposed to help managers and IT professionals mitigate digital ethics challenges and support ethical decision making within their organisations. Future discussions of standards and professional codes of practice should emphasise win-win solutions.

ABSTRACT. As artificial intelligence (AI) increasingly shapes our world, the AI divide, comprising access, skills, and outcomes, becomes a critical issue. The AI divide encompasses disparities in access, skills, and ethical outcomes related to AI technology. This paper employs a socio-technical framework to comprehensively understand and address the multifaceted challenge of the AI divide. A systematic literature review was conducted, analysing 46 studies that examined various aspects of the AI divide. Three levels of the AI divide emerged: access, skills, and outcomes. Geographical disparities, algorithmic literacy, digital skills, and algorithmic bias were identified as key factors influencing the AI divide. Accessible AI technology, digital and algorithmic literacy, unbiased AI outcomes, and effective regulation are essential for a more equitable AI landscape. We conclude that a socio-technical approach is crucial for bridging the AI divide, ensuring that the benefits of AI are accessible to all in our rapidly evolving technological landscape.

ABSTRACT. This paper presents an approach which aims to build on earlier approaches to the ethical study of emerging technologies. The ethics of emerging technologies is a growing field, as the range and potential impact of technologies is ever expanding in our increasingly technological world. The ethics of emerging technologies and their study is first reviewed by examining a number of key ethical frameworks. However, these approaches all lack some elements, which the paper looks to strengthen by integrating policy and empirical elements. The resulting approach is the TechEthos Anticipatory ethics Matrix (TEAeM) framework. This framework provides a methodological foundation for the study of ethical issues. Further, the framework has been designed in such a way that it may also be used in the context of other emerging technology ethics. In this way the TEAeM framework contributes to the field of ethical analysis of emerging technologies.

ABSTRACT. Live streaming commerce has emerged as a distinctive form of e-commerce, wherein products or services are promoted and transacted through real-time video broadcasts. This evolving paradigm leverages the immediacy and interactivity fostered between streamers and their audience during live video content. While there is a widespread recognition that the effectiveness of live streaming relies upon the presentation skills of streamers in articulating product value and stimulating audience purchase, a critical examination of the influence of streamers’ linguistic signals on audience purchasing behaviour remains insufficiently explored. This study, grounded in Signalling Theory, endeavours to investigate whether specific attributes of streamers’ speech, including speaking speed, pitch, and vocabulary richness, exert an impact on the live sales. Furthermore, the research delves into the potential extension of charismatic speaking to post-purchase phenomena, encompassing transactions subsequent to the conclusion of live video broadcasts.

ABSTRACT. A growing number of retail companies are implementing highly advanced in-store technologies to better serve their consumers by improving the shopping experience and assisting them as they proceed along the customer journey. This study looks into the connections between techno-stress, disengagement, privacy fatigue, and technology-enabled personalization. The research hypothesis is put forth based on previous literature, and it is projected that 502 in-store shoppers actually make use of the personalization technology. Second, the data for this study was gathered by a questionnaire survey using online survey through a panel data, and LISREL would then be used to verify the model's causality. Lastly, based on the research findings, this research provides insights into strategic implications and potential research areas for management and businesses in this domain, offering valuable guidance for improving the customer experience in retail settings.

ABSTRACT. This research aims to establish a comprehensive and validated model of donor motivations in crowdfunding, serving as a foundational framework for future studies in this domain. Leveraging the Self-Determination Theory to categorize crowd funding donor motivations into intrinsic and extrinsic categories, our study seeks to unveil disparities in the impact of intrinsic and extrinsic motivation on crowdfunding. Furthermore, it endeavors to identify the primary motivating factor that drives individuals to contribute to crowdfunding projects. Based on the data collected from Vietnam, this research has the potential to offer valuable guidance to both scholars and crowdfunding practitioners, particularly for the emerging markets.

ABSTRACT. The impact of WhatsApp groups on teaching and learning in higher education institutions is growing, as both instructors and students see its potential to improve the learning experience. The study adopted a systematic literature review following the PRISMA guidelines and 26 articles were analyzed. The results showed a rise in the usage of WhatsApp during COVID-19 and an expansion of the usage in higher education in teaching and learning. Furthermore, WhatsApp groups have benefited students and lecturers in teaching and learning in different academic fields and a positive impact was seen. However, some challenges were realized due to the introduction of WhatsApp groups in teaching and learning. This study has brought a new voice to the body of literature on digital technologies.