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The purpose of this chapter is to highlight the important role of human capital management in the Smart Manufacturing and Industry 4.0 revolution. Two hundred years ago, industrial revolution in the west has transformed or evolved from mechanical production driven or powered by water, and to date, we are in an era characterised by cyber physical systems. This transformation or industrial revolution has been driven by humans using creative minds to solve problems that were confronted. The Industrial 1.0 Revolution around 1700 AD, mass production was carried out by mechanical production powered by water (steam engines), which was labour intensive. The more manpower an industrial organisation has, the more goods and services would be produced, though this could take long to reach the market but that was the industrial system at that time. From mechanical production powered by steam engines between 1700s and 1800s to the second Industrial Revolution mass production powered by electricity between 1800s and 1900s to the third Industrial Revolution powered by electronic and IT automation and finally to Industry 4.0 Revolution cyber systems in 2000 and beyond, human capital has generated innovative solutions to human problems more than ever before. Today, human capital is not only creative, but rather a super human capital.

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Purpose Innovations provide a vital stimulus for economic growth. Through innovations, public sector organisations (PSOs) need to grow the economy to provide for the needs of their citizens. The purpose of this study is to identify innovation drivers and barriers in PSOs in Kenya. The paper aims to contribute to the understanding of the antecedents of innovations and to offer insight to PSOs to foster such innovations. Design/methodology/approach This research was conducted in two PSOs in Kenya. The participants of the present study consisted of a sample of 186 managerial and non-managerial employees. Empirical data were analysed using descriptive statistics, factor analysis and multiple regression analysis. Findings First, the results indicate that drivers of innovation in PSOs are: leadership practices, social factors, technological factors and management practices. Second, the results reveal that poor management practices and over-reliance on existing resources, among others, are barriers to public sector innovation. Third, the study indicates that management practices and leadership practices are factors to consider in overcoming barriers. Research limitations/implications As the present study was conducted with a convenience sample of 186 respondents from 2 purposively selected PSOs in Kenya, the extent to which the results could be generalized may be in doubt. However, as the aim of the study was theory testing, the study makes a contribution in this regard rather than doing a representative survey. Practical implications The study offers a first-hand insight into public sector innovation from the perspective of a developing country, Kenya, an area that has been neglected by researchers. The present study has implications for theory, practice, research and policy development, mainly in Kenya, but also for comparable situations worldwide. Originality/value The present study represents a first attempt to investigate the drivers, barriers, overcoming barriers and outcomes to innovations in a single study of PSOs from a developing nation. The present study provokes both academics and policy makers to rethink approaches to nurture innovations in the public sector.

Purpose The purpose of this paper is to examine the antecedents of entrepreneurial intentions amongst open and distance learning students during employment crisis. To achieve the purpose of this study, Ajzen’s theory of planned behaviour (TPB) was applied and empirically tested on the sample population. Design/methodology/approach Data were taken from a sample of university students pursuing business-related courses in Open and Distance Learning mode. Self-reported questionnaires were handed to a total of 500 students to complete and return. Returned and usable questionnaires numbered 245 in total, giving a return rate of 49 per cent. Descriptive statistics and regression analyses were utilised to analyse data. Structural equation modelling incorporated into SPSS was used to assess the structural model. Findings The key finding reveal that Ajzen’s TPB can partially be applied in determining entrepreneurial intentions in the developing economy. The study results also revealed that perceived behavioural control, personal attitude and subjective norm (SN) explained 62.5 per cent of variations in entrepreneurial intention, which surpasses many other studies conducted previously. Research limitations/implications Present study relied on cross-sectional data using quantitative design, therefore limiting the full understanding of the causal relationship between variables. Originality/value The study developed a conceptual framework based on literature that was empirically tested, which adds to existing ones, thereby extending the literature in the field. Moreover, the study managed to incorporate SN as an intervening variable, which has rarely been done.