In the UK, the introduction of austerity measures for public services has intensified the thinking around inter-organizational collaboration between emergency services and other public and/or private sector organizations. Theoretically, while collaborative benefits are held up as beacons that drive organizations to participate in inter-organizational arrangements, a high number of such arrangements fail. In this paper, we explored the factors that influenced the collaboration process in the context of developing ‘collaborative information infrastructures’, from an organizational and collaboration level perspective, via a multiple case study approach. Our findings offer insights into how policymakers and public managers could improve their practices by considering their approach towards, and impact of, these factors when implementing collaborative projects in information technology and information systems.
Like most companies, small and medium-sized enterprises (SMEs) have become reliant on digital technology for their day-to-day business operations. While valuable, this comes with challenges; one of which is the rise in cybercrime. In terms of their cybersecurity resilience and risk, SMEs are among the most vulnerable and least mature. This article addresses a gap in the literature that has neglected cybersecurity readiness in SMEs. The study proposes a CyberSecurity Readiness Model for SMEs (CSRM-SME) based on a Socio-Technical view of organizations. The model was applied to three SMEs to assess their cybersecurity readiness and further understand the environment and strategies adopted to prevent and manage cyber-attacks.
BACKGROUND Whilst digital health innovations are increasingly being adopted by healthcare organisations, implementation is often carried out without considering the impacts on front line staff who will be using the technology and those who might be affected by its introduction. The enthusiasm surrounding the use of artificial intelligence (AI) enabled digital solutions in healthcare is tempered by uncertainty around how it will change the working lives and practices of clinicians and healthcare professionals. Digital enablement can be viewed as facilitating enhanced effectiveness and efficiency by improving services and automating cognitive labour, yet the implementation of AI comes with challenges related to changes in work practices brought by automation. This research explores staff experiences before and after care pathway automation with an autonomous clinical conversational assistant (Dora) that is able to automate routine clinical conversations. OBJECTIVE The primary objective is to examine the impact of digital automation on the wellbeing of doctors, nurses and allied health professionals (AHPs) who provide or facilitate healthcare to patients in high-volume low-complexity care pathways. In the process of transforming care pathways through automation of routine tasks, staff will increasingly work at the top of their licence. The impact of this fundamental change to the professional identity and work practices of the individual is poorly understood. We aim to focus on understanding how automation of routine tasks impacts staff wellbeing, specifically assessing whether it contributes to, or mitigates burnout. Investigating this will illuminate how the implementation of conversational agents such as Dora impacts work practices. METHODS A multiple case study approach will be adopted, combining qualitative and quantitative data collection methods, over two distinct phases: (a) pre-implementation/ adoption, and (b) post-implementation. RESULTS The analysis is expected to reveal the interrelationship between Dora and those directly or indirectly affected by its introduction. This will reveal how tasks and responsibilities have changed or shifted, current tensions and contradictions, ways of working, and challenges, benefits, and opportunities as perceived by those on the front line of the healthcare system. CONCLUSIONS The implementation of AI in the healthcare sector, as well as the body of research on this topic, remain in their infancy. The project’s key contributions will be to understand the impact of AI enabled automation on clinician wellbeing and work practices.
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