PHD-Department of Management Science

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Browsing PHD-Department of Management Science by Author "Too, William Kiplimo"

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    Digital Dynamics, Government Policy, Artificial Intelligence and Productivity of Selected Public Sector Institutions in Kenya
    (Kenyatta University, 2025-11) Too, William Kiplimo
    Public sector productivity in Kenya remains a concern, hindering socio-economic transformation, global competitiveness, and job creation. A study by KIPPRA revealed a long-term decline in overall productivity from 0.45 in 2009 to 0.40 in 2022 with both labor productivity and total factor productivity falling over several decades. Similarly, productivity of government MDAs ranges from 45% - 65% which implies existence of wastages in majority of the MDAs assessed. It’s against this backdrop that this study assesses digital dynamics and productivity of selected public sector institutions in Kenya. It focused on five objectives; the effect of data modernization, network transformation, digital workplace and Information Technology managed services on productivity of public sector institutions. The study further assessed the mediating effect of AI and the moderating effect of government policy on the relationship between digital dynamics on Productivity of Selected Public Sector Institutions in Kenya. This study was underpinned on E-Government Theory, Resource Dependence Theory, Institutional Theory and Diffusion of Innovations Theory. This study adopted explanatory research design. The study population included 433 state department and agencies that have mainstreamed national productivity as provided by National Productivity and Competitiveness Centre (NPCC). The unit of analysis of the study was 433 MDAs that had mainstreamed national productivity while the unit of the observations was Heads of departments of performance monitoring units in the MDAs. The study adopted a scientific formula to give a good representative of the population. The formula adopted yielded a sample of 204 respondents from the target population. To select the respondents, stratified random techniques was used. To estimate the relationship between the study variables the study adopted Pearson correlation analysis which measured the magnitude of the relationship while multiple regression analysis was used to predict the existing relationship between independent and dependent variables. The study established a significant positive relationship between data modernization, network transformation, digital workplace and productivity of public sector institutions. The study found that IT managed services had a minimal and statistically insignificant effect on productivity. AI was found to partial mediate the relationship between digital dynamics and productivity significantly. AI integration enhanced the predictive power of digital dynamics on productivity. Finally, this study found that government policy moderated the relationship between digital dynamic and productivity. The study concluded that to achieve sustained productivity improvements, public institutions must adopt a holistic digital transformation approach that integrates advanced technologies, leverages AI, and operates within a supportive policy framework. The study recommends efforts to be directed at aligning practice with policy frameworks to create a supportive ecosystem for digitalization of government processes. To fully realize the benefits of digital workplaces, public sector entities need to upgrade their IT infrastructure. This includes investing in high-speed internet connectivity, cloud computing platforms, and secure remote working tools. Providing employees with access to these resources ensures continuity in service delivery and improves productivity.