We begin our analysis in this paper by recalling the persistent paradox that while the digital age is now pervasive around the world, it remains grossly underrepresented in relation to its official contribution to GDP growth. Conversely, the increasing dominance of software and internet companies among the world’s most research and development (R&D) intensive firms,and the fierce digital innovation race among the leading technological nations, gives some credence to the slogan that “data is the new oil”. Given that the asymmetric global value distribution from the “big data revolution” mirrors the natural resource curse that continues to plague African countries, we therefore problematize the intersection between Africa’s data governance trajectory and technological innovation. However, rather than attempting to account for the elusive contribution of the data revolution to GDP or tracking the R&D investment of African digital firms, we instead underscore the significance of endogenous technological innovation in achieving inclusive developmental outcomes (public value). In this vein, our main objective is to conceptualize a framework for the governance of inclusive, data-driven innovation in Africa. This conceptual framework is then operationalized to demonstrate its potential for being applied in three main ways: 1.) By developing a measurement indicator framework that uses stylized facts from reliable sources; 2.) Through an analysis of key policy documents on data governance and digital innovation in selected countries; 3. By grounding the conceptual framework in an experiential reality, based on the insights of specialist professionals in the relevant domains. On the basis of our analyses (including benchmarking against data from an OECD country, namely, South Korea), we conclude with recommendations for the efficiency of innovation-driven data governance in Africa, with implications for the achievement of policy relevant outcomes relating to digital access, health, agriculture and energy.

Data plays a crucial role in enabling individuals, organizations, and governments to make informed decisions. In the realm of education, big data analytics (BDA) is becoming increasingly prominent, allowing educational institutions to process and analyze large volumes of data to enhance their operations and outcomes. The aim of this study is to investigate the awareness and preparedness for predictive analytics in Nigerian universities. The study adopted a non-experimental design leveraging on the descriptive survey research design. The population for the study were university employees while the target population were academic and top-level non-academic staff. The purposive sampling technique was employed to reach the target population. The instrument for the study was a self-developed questionnaire titled Big Data and Assessment for Learning in Nigerian Higher Institutions Questionnaire (BiDAL) with an overall reliability coefficient of 0.96. The instrument was deployed using google forms for data collection. The research questions were answered using percentages and frequency while the generated hypotheses were tested using chi-square statistics. The findings of this study revealed that there is an average awareness of predictive analytics within the higher education institutions in Nigeria while the preparedness predictive analytics for improving educational assessment was established among others based on which the conclusion was drawn.

This paper presents insights on how developing country firms learn, with a particular exploration of the learning associated with the introduction of the new fourth industrial revolution (4IR) technology. At the core of production are questions about how firms select, adopt and adapt new technology and how they acquire the associated skills and knowledge. Industrial development rests on the notion of improving productivity to generate increasing returns to scale. How the value-added and efficiency gains are set in motion, shaped and achieved has interested scholars across a variety of disciplines and produced a diverse literature drawing out insights on what drives firms to invest in technology, what types of technology, the impact on revenue or costs, and obstacles as well as the broader sector, national and global economic setting. Recent research has identified the need to unpack the diversity of learning processes and the heterogeneity of technology adoption patterns. The contribution targets three gaps identified in the literature. First, there is a need to look within the firm to explore technology adoption from the perspective of the workers involved. Second, the paper adds to literature exploring the complexities and unique forms of technology-learning processes that take place in developing country firms and sectors. Third, is to contribute to a better understanding of the patterns and processes of learning associated with technology across manufacturing and services.