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The aim of this paper is to establish how resource dependency theory (RDT) and transaction cost theory (TCT) can inform decisions to outsource ICT services by public university libraries in Kenya.

The study adopted a multiple case study strategy in four selected public universities libraries in Kenya. Purposive sampling was used to identify respondents and data collection was done using a semi-structured interview schedule.

The study highlights how RDT and TCT theoretical perspectives illuminate some of the reasons, and problems associated with Information and Communications Technology outsourcing in Libraries. The paper concludes with recommendations and the way forward.

The study was limited to the outsourcing of information technology services in four public university libraries in Kenya, namely, Kenyatta University (KU) in Kahawa, Nairobi; Moi University (MU) in Eldoret; University of Nairobi (UON) in Nairobi; and Jomo Kenyatta University of Agriculture and Technology (JKUAT) in Juja, Thika. This being a qualitative study (and taking into consideration the subjective views where bias could occur), the researchers ensured that the research was reliable by recording and taking notes during the interviews and by using peer-debriefing and professionals in the field to ascertain their views.

The paper provides practical insights into outsourcing of Information Technology (IT) services in Public University libraries and information centres in Kenya. This study is useful for university libraries, information professionals, information communication technology professionals and university management.

The implications of the study are that outsourcing needs to be guided by clear policies that are documented and communicated to all the stakeholders.

This research assesses IT outsourcing services in selected public academic libraries in Kenya.

Artificial intelligence (AI) is poised to reshape mental health practices, policies and research in the coming decade. Simultaneously, mental health inequalities persist globally, imposing considerable costs on individuals, communities and economies. This study aims to investigate the impact of AI technologies on future citizenship for individuals with mental health challenges (MHCs).

This research used a community-based participatory approach, engaging peer researchers to explore the perspectives of adults with MHCs from a peer-led mental health organisation. This study evaluated potential threats and opportunities presented by AI technologies for future citizenship through a co-created film, depicting a news broadcast set in 2042. Data were gathered via semi-structured interviews and focus groups and were analysed using a reflexive thematic approach.

The analysis identified four key themes: Who holds the power? The divide, What it means to be human, and Having a voice. The findings indicate that adults with living experiences of MHCs are eager to influence the development of AI technologies that affect their lives. Participants emphasised the importance of activism and co-production while expressing concerns about further marginalisation.

This study provides new insights into the intersection of AI, technology and citizenship, highlighting the critical need for inclusive practices in technological advancement. By incorporating the perspectives of individuals with living experiences, this study advocates for participatory approaches in shaping AI technologies in mental health. This includes the co-creation of machine learning algorithms and fostering citizen engagement to ensure that advancements are equitable and empowering for people with MHCs.

The adoption of smart classroom is increasing in higher education around the world. Yet, factors affecting smart classroom adoption have not been sufficiently explored. Based on the innovation diffusion theory and external pressures, the present study developed a model to investigate the main drivers of smart classroom adoption.

SEM-AMOS was used to analyse the data collected from a sample of 1,208 educators.

The findings revealed that innovation diffusion theory and external pressures provide an appropriate model for understanding smart classroom adoption.

The findings offer important implications for higher education institutions, IT managers, and are likely to stimulate further research in the area of smart classrooms.

To the best of the authors' knowledge, this is the first study that used innovation diffusion theory external pressures to understanding smart classroom adoption.