ABSTRACT. In this keynote talk, I will reflect on my 27 years as an Information Systems scholar and my experiences of change and churn within my own career and in the wider IS field which has been beset over the years by identity crises and blurred boundaries with more ‘established’ and dominant disciplinary areas. I will review some of the key influences on the field, including leading scholars’ reflections about its direction, and the potential shifts that may occur in the field through recent trends in emerging technology and artificial intelligence. I end on a note of resilience and hope for those who are just embarking on their own IS research careers.

ABSTRACT. Large language model (LLM) chatbots have become a key medium for disclosing psychological distress, offering anonymity and immediacy beyond clinical or social media settings. Using one year of longitudinal data from a major Chinese chatbot (3,000+ SI cases), we predict future suicidal ideation (SI) using only pre-SI queries. A finetuned RoBERTa model achieves AUC ≈ 0.88, surpassing traditional mass screening methods.

We advance theory by empirically testing the Motivational–Volitional (MV) model at scale, mapping constructs such as defeat, entrapment, burdensomeness, and thwarted belongingness to linguistic signals. Topic modeling identifies both MV-consistent markers (e.g., sleep disturbance, hopelessness) and novel themes—parasocial intimacy, sexualized roleplay, and fantasy escape—suggesting digital-age extensions to suicide theory.

Trajectory clustering further shows heterogeneous emotional and risk pathways toward SI. This work demonstrates that chatbot language is both predictive and theoretically informative, opening new horizons for suicidal ideation prediction.

ABSTRACT. Digital transformation (DT) is a key driver of innovation and competitiveness, yet UK SMEs face persistent barriers such as limited resources, lack of technical expertise, and fragmented adoption. This research investigates how DT influences SME productivity through the development of data-driven decision-making (DDDM) capability—a critical but underexplored mechanism in SME contexts. Drawing on the Technology–Organisation–Environment (TOE) framework and Dynamic Capabilities theory, the study examines whether DDDM mediates the relationship between DT and performance, and how organisational factors like leadership support and digital skills shape capability development. Using a quantitative design, data will be collected via a survey of 300 UK SME decision-makers, with Structural Equation Modelling employed to test direct and mediating effects. Findings will advance IS theory by clarifying value realisation from DT and inform SME leaders and policymakers on strategies to enhance digital and data capabilities for productivity gains.

ABSTRACT. Small and medium-sized enterprises (SMEs) play a critical role in the economic advancement of a nation and contribute significantly to job creation. SMEs comprise approximately ninety percent of all businesses, account for over fifty percent of global employment, and contribute fifty-five percent of the worldwide GDP. However, SMEs encounter difficulties that arise from the constrained availability of resources, limited human, financial and technological capacities, establishing external partnerships, expanding their operations and getting financial support from credit lenders. Despite the abovementioned challenges, information systems (IS) research has paid limited attention to studying SMEs. A careful review of prominent IS journals indicates that only a few articles address issues specific to small enterprises. In this regard, the present research tries to fill this gap by studying three different digital technologies, namely data-enabled mobile phones, digital platforms, and digital public infrastructure (DPI) in relation to SMEs.

ABSTRACT. Application for Doctoral Consortium

This presentation will focus on the literature review chapter of my thesis. The aim of the literature review is to identify the key barriers of effective EPR use with the focus on system fatigue and staff burnout, and to assess the effectiveness of various change management strategies in enhancing staff engagement with the EPR system following its implementation. While the widespread adoption of EPR system across National Health Service (NHS) Trusts in England is nearing completion with 91%, a small number of organisations are still struggling to reach this milestone, and many more are not yet using these systems to their full potential (Kurdi, 2025; Lawrence et al., 2025). Despite the significant investments in EPR, a few challenges have been encountered in the adoption of this system. This research addresses the gap in knowledge regarding the post-implementation phase of EPR system in Gloucestershire Royal Hospital.

ABSTRACT. Retrieval-Augmented Generation (RAG) is increasingly critical in legal practice, yet current systems often retrieve noisy text chunks that increase hallucination risks. This research optimizes span-level retrieval using the LegalBench-RAG benchmark to locate the precise character indices of answering clauses. We evaluated dense-only, hybrid, and lexical architectures using various embedding models and chunking strategies. Results demonstrate that dense-only architectures utilizing legal-specialized embeddings (Voyage AI) and structure-aware chunking yield the highest top-rank precision (11.1%), significantly outperforming the original benchmark’s generic OpenAI baseline (6.41%) and hybrid approaches. While generic models offer broader recall, domain-specific tuning provides the high precision required for auditable, trustworthy legal AI. Future work will investigate retrieval variance across document types and link technical metrics to user trust.

ABSTRACT. This PhD research examines the dynamic interplay between digitalization and organizational legitimacy within sustainability-oriented enterprises. Legitimacy pressures influence how digital innovations emerge, develop, and gain acceptance. Conversely, organizations can deploy digital technologies strategically to address their own legitimacy. Using qualitative (case study) and configurational (QCA) approaches, the research uncovers how legitimacy shapes the digital innovation process, and how digitalization supports legitimacy-building efforts. The study advances theoretical understanding of legitimacy in digital contexts and provides practical insights for innovative organizations trying to develop and make an impact in a sustainability context.

ABSTRACT. Eating disorders (EDs) are visually mediated psychiatric conditions exacerbated by the pervasive "thin-ideal" imagery on social media. While existing Digital Mental Health Interventions (DMHIs) focus on functional tracking, they often neglect the psychological impact of interface design. This research adopts a socio-technical perspective through Affordance Theory to investigate how social media platforms function as "action possibilities" that trigger pathological attentional biases. This research proposes a Visual Communication Design (VCD) framework that integrates Cognitive Bias Modification (CBM) and adjusted affordances to recalibrate user perception while using social media. By developing and evaluating a therapeutic digital artifact, this research demonstrates how strategic visual interventions can transform digital environments from pathogenic spaces into cognitive recovery. This work contributes a novel paradigm for IS-based mental health research, addressing the sensory-perceptual distortions at the heart of EDs.

ABSTRACT. Rapid NHS AI adoption is driving organisational reconfiguration of clinical work, decision authority, and accountability allocation, yet governance clarification remains incomplete. This study advances a configuration-specific explanation of human-AI interaction by analysing how alternative AI configurations redistribute judgement, responsibility, and escalation control, and how such redistribution shapes trust formation, role restructuring, and equity exposure. A comparative multiple-case mixed-design investigation across four NHS trusts examines collaborative, decision-support, autonomous, and adaptive/escalation-aware configurations, focusing on override enactment, handover specification, auditability, and accountability assignment in practice. The analytical integration of socio-technical theory, human-AI collaboration theory, and technology trust theory supports mechanism identification linking configuration design to organisational adaptation. The principal output is an empirically refined Minimum Viable Accountability Control (MVAC) matrix, specifying the minimum documentation and oversight control-set required for safe, trusted, and equitable AI implementation at scale.