ABSTRACT. As universities invest heavily in Artificial Intelligence, a disconnect has emerged: the tools students and staff actually rely on often sit outside institutional provision. This "Shadow AI" migration suggests that the current adoption challenge is not technological, but relational. In this keynote, Professor Isabel Fischer explores the emerging "Trust Gap" in higher education. Drawing on her latest research into educator identity, student sensemaking, and institutional governance, she examines the tension between Integrity (the university’s focus on risk and security) and Ability (the user’s need for high-performance capability). She suggests moving beyond a "culture of concealment" by building robust trust architectures that encompass AI, students, educators, and the institution.

ABSTRACT. Contracts form the backbone of modern economic and legal transactions, yet their drafting is a resource-intensive process susceptible to inconsistencies. The present paper conceptualises consistency as a multidimensional construct grounded in contractual law, linguistics, and logic. Based on recurring elements across these domains, four analytical dimensions are derived, namely formal, interpretative, contextual, and overarching consistency. These dimensions inform a systematic literature review that identifies existing methods, concepts, and operationalisations of consistency in information systems. Drawing on the findings, an integrative framework for the systematic validation of contractual consistency is introduced. The present paper discusses a multidimensional framework for assessing contractual consistency across formal, interpretative, and contextual levels. The framework integrates findings from law, linguistics, and information systems, offering a basis for systematic and automated consistency validation in contract analysis.

ABSTRACT. In this developmental paper, we present a study that aims to examine the future of the legal profession. It is based on an understanding that AI-based technologies have already begun to impact legal services and that technological advancements will continue to transform both the sector and the professionals within it. Adopting a methodology that entails the use of futuristic and fictional scenarios and co-creative job adverts, the study will examine the impact of AI-based technologies on the professional identity of legal professionals in 2075. It is expected that the study will lead to theoretical insights on the transformation of professional identities in an AI accelerated future, contribute to educational insights, as well as offer practical implications by providing creative training materials for regulators, professional bodies and training providers.

ABSTRACT. This paper critically examines the global acceleration of Digital ID systems, contrasting official techno-optimistic narratives with implementation realities in two distinct contexts: the United Kingdom and the Caribbean. While governments frame these initiatives as vehicles for efficiency, security, and sustainable development, we argue they frequently ignore the digital divide and lived complexities. By comparing the proposed UK "Brit ID" and Caribbean digital transformation agendas, we expose a significant disconnect: these programmes often exacerbate structural exclusion and enforce coercive adoption on marginalized groups. Drawing on theoretical frameworks of surveillance capitalism and technocolonialism, we posit that official discourses serve to mask "untold narratives" of state control, performative security, and extractive data power. We conclude that rather than empowering citizens, current Digital ID models risk entrenching inequality and serving geopolitical and corporate interests under the guise of innovation.

ABSTRACT. Generative artificial intelligence (AI) offers new opportunities for small and medium enterprises (SMEs), yet adoption in developing economies remains uneven due to limited awareness, skills, and ethical guidance. This study examines how participatory awareness initiatives shape readiness for responsible generative AI adoption among SMEs in a developing countries. Drawing on a participatory case study of an AI awareness workshop involving 170 SMEs in Gombe State, Nigeria, the study combines pre- and post-workshop surveys with qualitative analysis of discussions, observations, and reflections. The findings show that hands-on engagement with accessible generative AI tools produced substantial shifts in perception, confidence, and ethical awareness, enabling early technology appropriation despite persistent infrastructural and financial constraints. The study contributes to ICT for Development and responsible AI literature by demonstrating that participatory awareness initiatives can foster both technical readiness and ethical judgement, offering an inclusive pathway for bridging the AI divide among SMEs in developing economies

ABSTRACT. The wide adoption of healthcare chatbots for counselling, diagnosis, and health promotion is transforming how healthcare services are delivered and how patients engage with service providers. Despite growing academic and industrial efforts in designing technically competent healthcare chatbots, our understanding of their social interaction with users remains fragmented and underdeveloped. This systematic literature review (SLR) was conducted to integrate existing evidence on the social characteristics of text-based healthcare chatbots, with the aim of developing a comprehensive design codebook for chatbots used in providing healthcare support. In addition, this systematic review will shed light on how healthcare chatbots’ social design, along with user traits and use context, affects user perceptions and use outcomes.

ABSTRACT. After many years of investment in the digital transformation of healthcare, alongside calls to make systems safer, more affordable, accessible and patient-centered, it is timely to reassess progress. Understanding theoretical developments and the influence of the Information Systems (IS) community on practice and policy is essential. This review examines the current landscape of Health Information Technology (HIT) research, exploring contemporary challenges and dilemmas facing healthcare organisations. It revisits the three areas identified by Agarwal et al. (2010): HIT design, implementation and meaningful use; the measurement of HIT payoff and impact; and the extension of HIT beyond traditional boundaries. The study also highlights emerging opportunities for transformation, proposing new research questions and methodological approaches. As global investment in digital health continues to grow, addressing HIT’s ongoing challenges and unresolved dilemmas remains a critical priority for the IS research community.

ABSTRACT. This paper presents the ongoing research findings funded by the UKAIS Teaching Innovation Award 2024 to indicate a conceptual framework developed through the project, namely the Agile-Community of Inquiry (Agile-CoI). The approach integrates Agile Learning principles with the Community of Inquiry (CoI) framework to support the development of responsive, inclusive, and sustainability-focused postgraduate education. The paper presents a case study of the MSc Managing AI in Business programme at Salford Business School (SBS), which applied Agile-CoI to create a student-centred, industry-aligned, and ethically grounded curriculum. The study situates Agile-CoI within contemporary challenges in UK Higher Education (HE), including international student diversity, digital transformation, and sustainability integration in business education. Through three development workshops and iterative feedback cycles, the programme embedded social, cognitive, and teaching presences while incorporating Sustainable Development Goals (SDGs), active learning approach and innovative assessments. Preliminary findings suggest enhanced engagement, reduced stress, and improved employability alignment.

ABSTRACT. As AI agents’ literacy is increasingly regarded as essential in future workplaces (Hughes et al., 2025), there is a growing need for higher education to prepare students to engage with AI tools. Yet, within UK higher education, widening participation students often lack digital networks and communities where they can learn, and develop digitals skills. This project responds to this challenge by proposing an innovative assessment and engagement tool i.e student-generated podcasts to foster the development of digital skills by widening participation students. The emerging practice in this project is the use of student-generated podcasts as an assessment tool, at the same time promoting engagement in a digital community. This project is essential because it fosters digital inclusion of widening participation students, bridging a digital gap between them and non-widening participation students.

ABSTRACT. Pedagogy can be defined as the method of teaching spanning theory and practice. As intelligent technologies cast doubt on existing teaching approaches and disrupt higher education models, purposeful pedagogical transformation in HE has become a prominent issue. This is particularly the case for disciplines that operate at the intersection of the social and technical (i.e., socio-technical) spheres, such as the Information Systems discipline. These disciplines may have elevated responsibilities to provide informed contributions to pedagogical transformation initiatives. However, there are many challenges that inhibit successful pedagogical transformation. This article presents a project concept that aims to address the challenges to successful pedagogical transformation from an IS perspective. The paper reports on the preliminary exploratory research phase, briefly defining pedagogical concepts (the “what”), exploring the challenges to pedagogical transformation (the “why”), and proposing a community-driven approach to address the challenges (the “how”), while identifying the anticipated implications (the “so what”).

ABSTRACT. Active Debris Removal (ADR) is a critical domain of the space economy where sensitive, reusable, and strategically valuable data must be shared across competing actors. Governance failures in this ecosystem pose systemic operational, legal, and security risks. Existing data governance models offer partial solutions but lack enforceable sovereignty, revocability, and usage control once data crosses boundaries. This paper addresses that gap by investigating Data Spaces as socio‑technical governance institutions tailored to ADR. Through conceptual analysis, we synthesize IS governance literature with ADR’s imperatives, comparing Data Spaces to Fabric, Mesh, and Lakehouse. Findings show Data Spaces best operationalize federated sovereignty, purpose binding policies, and auditability, though challenges remain in data governance drift, artefact accountability, cross‑border enforcement, and assurance scalability. Effective ADR data governance requires embedding rules within architecture, supported by trust services and legal enforcement. Implications extend beyond ADR, offering a pathway for collaboration in high‑stakes ecosystems where conventional models fail.

ABSTRACT. Technological advances and reduced costs have enabled rapid growth in the space sector. Hence, there is increased participation by smaller actors in the Space 4.0 era, in contrast to earlier periods dominated by government-funded space agencies, prompting questions about space sustainability, which is also a nascent area of Information Systems (IS) research from the sector-specific knowledge perspective. Therefore, this study aims to explore factors impacting space sustainability through a systematic literature review. The review identifies key factors that contribute to space sustainability, which is closely related to the space value chain. The findings also highlight opportunities for practical implementation of these factors, including the potential integration of Circular Economy principles into the space value chain. While the study does not advance a specific IS theory, the identified factors provide a structured empirical foundation for future research to apply and extend established IS theories within the space sector.

ABSTRACT. This research-in-progress paper examines how smartwatches can support emotion regulation in digital workplaces. Drawing on a six-week action research study with 11 employees in a Norwegian organisation, the project explores how smartwatch feedback influences planning and organisation of work, perceived wellbeing, and performance. Data were collected through workshops, longitudinal qualitative diaries, and semi-structured interviews. Preliminary findings reveal three emerging themes: (1) biometric feedback from smartwatches triggers reflection on stressors, recovery patterns, and behaviours affecting sleep; (2) employees adapt their workday mainly through breaks and physical movement rather than task restructuring; and (3) participants adopt proactive emotion regulation strategies. These insights highlight the potential of wearable technologies to foster self-awareness and wellbeing in organisational contexts, while emphasizing the need for personalization to mitigate challenges such as notification fatigue.

ABSTRACT. This study examines how personality congruence between humans and large language models (LLMs) influences creative problem-solving. Building on the Human–AI Collaboration framework and Social Presence Theory, the research investigates how alignment between user personality (introversion or extraversion) and LLM interaction style affects creativity, engagement, and task efficiency. Using the HEXACO-PI-R model to classify participants, matched (introvert–introvert, extrovert–extrovert) and mismatched (introvert–extrovert, extrovert–introvert) human–LLM pairs were tested in controlled experiments with GPT-based agents trained for specific personality expressions. Findings are expected to reveal how personality fit enhances perceived social presence, reduces cognitive effort, and improves creative outcomes measured by innovativeness, usefulness, and impact. The study advances theory by integrating personality psychology with AI interaction design, offering empirical evidence on the behavioural mechanisms underlying human–LLM collaboration. Practically, it provides insights for designing adaptive, personality-aware LLM systems that foster effective and meaningful creative partnerships.

ABSTRACT. This paper introduces a practical and replicable socio-technical method for refining qualitative interview guides through structured human–AI collaboration. ChatGPT was used to role-play participants, allowing researchers to test and improve theory-informed questions through a two-layer workflow: (1) designing structured prompts that elicit realistic role-based responses, and (2) systematically evaluating those responses using criteria adapted from the Interview Protocol Refinement (IPR) framework. Applied in a healthcare study, this method improved question clarity, relevance, and alignment with theoretical constructs, and the resulting guide later produced rich and reflective responses in real interviews. The main contribution is a replicable early-stage prototyping method that shows how structured prompt engineering can be used to refine qualitative instruments with transparency and efficiency when traditional piloting is difficult. Although demonstrated in healthcare, the approach is transferable to other Information Systems contexts where expert access is limited.

ABSTRACT. Research on electric vehicle (EV) adoption has grown rapidly, yet the everyday charging experience remains underexplored, particularly from the consumer perspective. This study addresses this gap by examining how users describe EV charging services in the United Kingdom using large-scale consumer review data. The research aims to develop an analytical framework that applies topic modelling to identify the key service-related factors shaping user experience. A dataset of 24,908 verified reviews from 15 charging service providers has been collected, and this paper outlines the ongoing data preparation process, including anonymisation, and text preprocessing. The planned topic-modelling approach will uncover recurring themes within unsolicited user feedback, offering insights beyond those captured through traditional surveys. As a work in progress, the paper discusses expected outcomes and their implications for understanding EV post-adoption. The study is anticipated to highlight the aspects of charging that matter most to consumers and inform future research and practice.

ABSTRACT. Virtual teams have become a dominant form of digital collaboration, where trace data enable rich assessments of work performance. Yet, prior research has primarily emphasized task performance, overlooking contextual performance such as helping behaviours. This study introduces a social emotions perspective, focusing on how performance shapes members’ well-being through two types of social emotions that accumulate over time. Using a two-wave longitudinal design, we find that contextual performance fosters accumulated gratitude, which subsequently enhances well-being, whereas task performance shows no comparable effect. These findings establish contextual performance as a meaningful dimension of performance measurement and highlight the cumulative role of social emotions in shaping well-being in digital collaboration. The study extends IS research by enriching user well-being theory with a novel emotional antecedent and pointing to new opportunities for examining cumulative emotional dynamics.

ABSTRACT. Text-to-image generation (TTIG) has transformed digital creativity, yet collaboration within these communities remains under-explored. While traditional theories of online collaboration, such as those for Open Source Software, typically focus on convergence towards a single functional solution, TTIG collaboration prioritizes aesthetic divergence and rapid iteration. Drawing on semi-structured interviews with active TTIG community members and thematic analysis, we identify four collaboration modes: Direct, Indirect, Inspirational, and Functional collaboration. A primary contribution is the definition of "Prompt Jams" as collaborative episodes of prompt-based co-creation with a shared creative trajectory, iterative reciprocal responsiveness within a near-synchronous or session-based time window, and action-oriented feedback enacted through successive prompt revisions and generations. We show that collaboration in TTIG communities involves complex social performances and ethical tensions regarding ownership and remixing. We extend knowledge collaboration theory by conceptualizing prompts as a fluid, conversational artifact rather than a static object, offering critical insights for future platform design.

ABSTRACT. This paper examines the use of generative artificial intelligence, specifically ChatGPT, to support the evaluation of student assignments and feedback in a project-based learning (PBL) Business Continuity Management (BCM) module across the 2023 and 2024 academic years. The study compares AI-generated analyses with traditional human assessment to evaluate consistency, depth, and reliability. Multiple evaluation rounds using different prompts and users show that ChatGPT can efficiently identify themes, extract patterns, and apply rubric-based criteria, offering meaningful support for processing large volumes of qualitative work. However, limitations arise around contextual nuance, over-generalisation, and prompt sensitivity, highlighting the continued need for human oversight. The study also demonstrates how AI can contribute to rubric refinement by surfacing overlooked elements and misalignments between learning outcomes and assessment criteria. Practical principles for responsible and transparent integration of AI into assessment are proposed, with implications for teaching practice, feedback quality, and digital responsibility in higher education.

ABSTRACT. This paper explores the ethical implications of Generative Artificial Intelligence (GenAI) in postgraduate education at UK universities. Through a literature review and online survey with postgraduate educators, the research develops a set of guidelines grounded in virtue ethics to guide GenAI's responsible and ethical use. These guidelines address academic integrity and transparency challenges, promoting moral character development and open communication between educators and students. By incorporating reflective practices and fostering trust, the guidelines offer practical measures for institutions, departments, and educators to implement that align with the evolving role of GenAI in higher education. This study highlights the limitations of current approaches and provides adaptable, actionable strategies for maintaining academic integrity while integrating GenAI into postgraduate education. The guidelines are a valuable resource for navigating the ethical challenges AI technologies pose in this dynamic educational landscape.

ABSTRACT. This study examines how technology providers respond to institutional complexity during client-led enterprise AI implementation in China. Using institutional logics, it identifies how state, market, professional and other logics shape expectations and practices, and conceptualises conditions when multiple logics coexist and are hard to reconcile. A qualitative case study builds contextual understanding of how these logics and the resulting complexity relate to organisational strategies and structures. Data will be gathered through semi-structured interviews and document analysis and analysed with the Gioia methodology to develop data-grounded concepts. The study is in the design and data-collection phase. Expected contributions include extending institutional logics and complexity research to technology providers, clarifying links between complexity and enterprise AI implementation, and offering practical guidance for implementation in diverse institutional environments.

ABSTRACT. Local governments face several service delivery challenges, including delayed responses to citizen requests, limited customer service orientation among employees, restricted operating hours, and the need for residents to travel long distances. While many studies focus on success and failure factors during ERP deployment, few explore the contextual elements that prevent local governments from realising ERP benefits post-implementation. This study therefore asks: Why do local government organizations fail to achieve ERP benefits realisation after implementation? A qualitative research design was employed, collecting empirical data through interviews and analysing them inductively to identify emerging themes. Guided by an interpretive paradigm, the study examined the barriers to ERP benefit realisation within a local government context. The findings reveal that contractual limitations and frequent management rotation are principal factors inhibiting ERP benefits realisation.

ABSTRACT. Generative Artificial Intelligence (GenAI) is increasingly used for creative activities. Despite evidence of ‘creative outputs’ in existing writings, we lack detailed understanding of the ‘creative process’ whereby creativity emerges through GenAI-human interactions. In this research-in-progress paper, we take the case of scriptwriting as an ideal case for studying the creative process in the GenAI context and present an ongoing study involving 21 interviews with scriptwriters which we analysed using two rounds of qualitative coding. Our findings suggest that GenAI plays four different roles during the scriptwriting process: creative guide, proofreader and rewriter, content producer and creative collaborator. We contribute to the emerging literature on GenAI and human collaboration by explaining how the creative process is transformed in the GenAI era. Finally, we outline implications for scriptwriters and creative industries.

ABSTRACT. Toxic behaviours in online gaming environments pose serious threats to players’ well-being and the long-term sustainability of gaming communities. To alleviate the stress that gamers experience as a result of game toxicity, this study draws on the stress-buffering model to explore how gratitude interventions can mitigate perceived toxicity by enhancing perceived social support. Building on this conceptual foundation, the study proposes five theoretical propositions, emphasizing four key dimensions of gratitude expression, intensity, span, density, and frequency, as underlying mechanisms that shape intervention effectiveness. This study contributes by extending the application of the stress-buffering model to online gaming contexts, underscoring the critical role of social support in online environments, and informing practical insights for gaming platforms aiming to design interventions that cultivate healthier and more supportive gaming communities.

ABSTRACT. Chatbots are increasingly used to fulfil various purposes, including providing social companionship. Research has reported how people engage with these social chatbots (SCs) in different and unexpected ways, producing different relationships and consequences. Although existing studies have investigated the adoption, use, and impact of SCs, the current understanding of human-SC interactions in the context of social companionship is fragmented, with research often adopting a static theoretical lens, thus limiting a holistic understanding of the relationship-building landscape. A systematic review of the literature will be conducted to develop a novel process model for human-SC relationship development and outline key SC design features and user characteristics that shape relationship evolution. Through this dynamic perspective, this study will develop a comprehensive framework to theorise both the agents’ and users’ roles in the relationship development process, whilst considering ethical design, responsible use of AI in social contexts, and future research directions.

ABSTRACT. The growth of digital content and systems featuring nostalgic appeal is contributing to the increasing interest in digital nostalgia. However, the implications of digital nostalgia remain inconsistent and underexplored. To address this gap, this study examines the emotional and psychological implications of digital nostalgia and explores the features and conditions of digital media consumption that shape such experiences. We use an affordances-based theoretical lens and a mixed-method approach to address the study objectives. The results of the qualitative stage show that digital nostalgia evokes a range of negative and positive emotions that can either motivate or inhibit engagement with nostalgia-inducing content. These psychological and behavioural responses depend on how recent the nostalgic event was, the type of platform, and the counterfactual explanation associated with the attribution of negative experiences triggered by nostalgic content. These findings contribute to the literature on digital nostalgia and information systems management.

ABSTRACT. As organisations become increasingly dependent on digital workflows, the risk of knowledge loss grows amid rapid staff turnover and shifting work practices. While AI is positioned as a solution to these challenges, sustaining the adoption of AI-driven documentation systems remains problematic, often undermined by low engagement, inadequate training, and fragmented practices. This paper examines how organisations can embed AI-enabled knowledge documentation into everyday work to preserve institutional memory and strengthen resilience. Drawing on a mixed-methods study within a global technology company, including surveys (n=75) and four multi-level focus groups (n=23), the research develops a cyclical adoption framework that integrates software selection, system integration, motivation, and training. Findings highlight the socio-technical dynamics of adoption, where sustained use depends as much on organisational culture and workforce engagement as on system capability. The paper advances understanding of how intelligent digital technologies reshape work practices and enable more resilient forms of organisational learning.

ABSTRACT. In an increasingly transparent and accountability-driven business environment, organizations must align strategic communication with tangible action to maintain stakeholder trust. While firms frequently articulate commitments to sustainability, ethics, and digital innovation, discrepancies between stated intentions and observable actions generate scepticism, reputational damage, and financial loss. Drawing on signalling theory, this study examines how stakeholders interpret strategy-based versus action-based signals, and how misalignment between the two shapes perceptions of trust and performance. Using two quasi-natural experiments—the COVID-19 crisis and the post-2022 AI boom—we empirically assess how firms’ sustainability and AI-related strategies translated into concrete actions, and how stakeholders responded to these signals. The contrasting contexts enable a systematic comparison of the effectiveness of communicative versus behavioural signals.

ABSTRACT. Information sharing is increasingly central to data driven public administration, yet its adoption remains limited due to legal, technical, and organisational barriers. This research explores both the benefits and challenges of inter organisational information sharing within the UK public sector. Using a qualitative case study of the Greater Manchester Combined Authority (GMCA), it draws on 28 semi-structured interviews with professionals across local government, health, social care, and data governance. An interpretivist approach reveals that information sharing offers significant advantages, including better coordinated services, earlier intervention, enhanced safety for vulnerable groups, and more efficient processes. Despite these benefits, longstanding obstacles persist, such as outdated IT systems, departmental fragmentation, limited resources, and a cautious culture shaped by GDPR uncertainty. Trust, leadership, and organisational culture strongly influence effective data sharing. The study concludes that successful information sharing depends on aligning technical interoperability with ethical governance and sustained organisational change that delivers public value.

ABSTRACT. Data governance (DG) has emerged as a cornerstone of organisational success in the digital economy, enabling reliable decision-making, regulatory compliance, and innovation across sectors. However, despite a growing body of research, DG remains conceptually fragmented and inconsistently operationalised across different organisational contexts. This paper presents a literature review that synthesises insights from 85 studies, including 18 literature reviews, 51 foundational DG papers, and 16 recent studies (2023–2025). Using a five-stage framework (Define–Search–Select–Analyse–Present), this review identifies how DG principles, structures, and challenges differ between intra-organisational and inter-organisational settings. Findings reveal that DG has evolved through two dominant approaches: control-oriented governance (intra-organisational) and coordination-based governance (inter-organisational). This study provides (1) a comparative framework, distinguishing governance approaches across contexts; (2) an empirical synthesis of challenges and enablers; and (3) a research agenda highlighting the growing importance of new technologies, automation, and ethics in future DG design.

ABSTRACT. Digital transformation (DT) is a topic that has attracted significant attention from both academia and practice. However, existing research often relies on organisational change models and focuses on outcomes and success or failure factors, overlooking DT’s processual, human-centred, and context-specific nature. Addressing these gaps, this study is based on sensemaking theory to study how organisational agents collectively conceptualise DT. Drawing on a case study of a large Chinese state-owned enterprise (SOE), we identify five sensemaking episodes and three reinforcing mechanisms: technology perception divergence, information distortion, and experience asymmetry. These mechanisms amplify role-based tensions, leading to forced meaning reconstruction and dual-track compliance systems. The study contributes a process understanding of DT sensemaking, revealing boundary conditions for sensemaking theory and offering practical guidance for SOE leaders and regulators to align strategic intent with operational realities.

ABSTRACT. Fake news is a global social media concern, but most research has focused on Western text-based platforms. Douyin, a Chinese leading short-video app with 750 million users, offers a highly visual, algorithm-driven environment. This study explores how Douyin users perceive fake news videos, make credibility judgments, and respond behaviourally. An online survey was administered to 125 Douyin users, with data analysed using descriptive statistics and group comparisons. Participants predominantly used superficial visual and emotional cues to judge video credibility rather than source credibility. Although a majority acknowledged the presence of fake news on Douyin and had encountered suspicious clips, their typical reaction was passive. Douyin users exhibit a “high awareness–low action” pattern regarding fake news. The findings underscore the need for improved platform design (clear credibility indicators and user-friendly reporting features) and enhanced digital literacy education to encourage critical evaluation and proactive engagement with misinformation on visual platforms.