Electronic Theses and Dissertations (Masters/MBA)
Permanent URI for this collectionhttps://hdl.handle.net/10539/37942
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Item Innovation capability building by the TVET sector for the Fourth Industrial Revolution in South Africa(University of the Witwatersrand, Johannesburg, 2023) Mngomezulu, Thulani ProffessorThis is a qualitative research report on Technical and Vocational Education and Training (TVET) system capability building for the fourth industrial revolution in South Africa. The study evaluated the level of complementarity amongst the main components and key role players within the Centres of Specialisation (CoS) program in relation to capability building. The foundational theories that guided this study include the Sectoral Systems of Innovation and Technological Relatedness. An embedded case study involving welding and boilermaking CoS cases was used. Data were collected through scholarly and grey literature review, semi- structured and unstructured interviews of participants representing colleges, employer-partners and students that were on the verge of completing their program. A thematic analysis approach was used for analyzing the collected data, with guiding themes emerging from both the literature survey and primary data. Despite employer-partners being one of the key role players for the learner development process, the study finds that past interventions and research efforts have largely been directed to colleges with little attention paid to industry firms. Even though some colleges have taken initial steps, none of the cases studied has fully integrated industry 4.0 (i4.0) technologies with their training programs. Employer-partners either are in the same position or have achieved partial integration. The study highlights complementarities that exists within the sector. Potential improvements are also outlined with regard to interaction and interdependency structures within the TVET sector. These offer possibilities for maximizing synergies among various 4IR capability building projects and capabilities that may exist within the whole TVET sectorItem A study of Industry 4.0 technologies and customer perception in the insurance industry(2021) Busschau, Mary C.BThe changes in society and business towards a more digitised and connected world evoke feelings of both excitement and anxiety. Businesses are increasingly using these technologies to ensure optimal customer service and delivery of services and products, but the literature shows that many customers may not be ready for this change. Industry 4.0 technologies such as big data, artificial intelligence, and the internet of things are bringing increased awareness around customer concerns on privacy, fear of autonomous robots and artificial intelligence, and a general distrust of new technology. This research study looks at the potential issues that customers have with digital technology and their perceptions of South African insurance providers using this technology. The research also looks at whether customer education and communication have an impact on these areas of privacy concerns, fear of autonomous robots and artificial intelligence and distrust of new technology and customer perception. A quantitative research method was applied through an online survey, of which 395 participants formed the segment. Using correlation statistics and structural equation modelling the results showed that a unit increase in privacy concerns was more likely to improve their perceptions towards insurance by as much as 17.9%. The results also suggest that there is a 26% chance that improvements in trust in technologies could positively impact respondents' perceptions of insurance. The study also revealed that fear of autonomous robots and artificial intelligence have nothing to do with customer perceptions; results were not significant at the 5% level. Further results indicated that customer education and transparent communication significantly impact customer perception related to privacy concerns by 61.15% and distrust of new technologies by 143.15%. These results support most of the theories from the literatureItem The digital maturity levels of African airports: a departure point for the digital transformation journey(2020) Mosehlane, TshegofatsoBackground: The study aims to investigate Digital Maturity levels within the African airport industry. The correlation between Digital Maturity and the following airport performance indicators; total revenue growth, total departing passenger growth and Airport Service Quality (ASQ), was investigated to establish whether any such relationships exist. Objectives: To determine the as-is Digital Maturity levels as input into Digital Transformation Strategy development and to understand whether there exists a relationship between high Digital Maturity levels and an increase in company performance. Method: A literature study of fourteen Digital Maturity models was performed to determine the qualitative dimensions of the Digital Maturity Model used in this study. An online survey set up in a Likert scale format (1 = strongly disagree to 5 = strongly agree), was subsequently developed. Frameworks by De Bruin, Rosemann, Freeze, and Kulkarni (2005) and Maier, Moultrie, and Clarkson (2012), were used for the development of the Digital Maturity Model. The reliability of the Digital Maturity model was tested using Cronbach’s alpha (α) test (Gilem & Gilem, 2003). The survey was sent to African airport employees via email. Responses were quantitatively measured by allocating weightings (1 to 5) to Digital Maturity sub-dimensions, enabling the calculation of maturity levels per Digital Maturity dimension for each airport. Descriptive studies were further conducted to understand the distribution of the collected data. The second part of the study investigated the correlation between Digital Maturity levels and company performance indicators (Remane, Hanelt, Wiesboeck, & Kolbe, 2017). Results: The study found that African airports display low maturity levels, ranging between 1.39 and 2.96. With South African and Ghanaian airports being on the higher end and Nigerian airports being on the lower end of the Digital Maturity scale. Most of the airports fall on the higher end of the scale, above Digital Maturity level 2.7. Furthermore, all the airports experienced a decline in total revenue and an increase in total departing passenger numbers over 3 years. The airports with the higher Digital iii Maturity levels experienced lower total revenue declines and higher total departing passenger growth, compared to the airport with the lowest Digital Maturity level. Additionally, the airport with the highest Digital Maturity level, experienced the most considerable decline in ASQ. Whereas the airport with the lowest Digital Maturity level, experienced an improvement in ASQ over the 3 years. Conclusion: Digital Maturity levels at African airports are low and to remain competitive, airports need to define strategies to assist them in progressing to higher levels of Digital Maturity. The features and outputs of the Digital Maturity Model survey should be used to inform the Digital Transformation Strategies. The study found a positive relationship between Digital Maturity and growth in total revenue and total departing passengers, and a negative relationship between Digital Maturity and ASQ. Organisations should decide on the Digital Maturity dimensions that will be a priority for them to remain competitive. These priority dimensions should be used to offer a differentiated experience to passengers and customers per the organisations’ refreshed Digital Transformation Strategy.