Faculty of Commerce, Law and Management (ETDs)
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Item Ethical challenges of artificial intelligence product innovation in South African financial services(University of the Witwatersrand, Johannesburg, 2025) Kiiru, Leonard; Matshabaphala, ManamelaThis research investigates the ethical complexities surrounding artificial intelligence (AI) driven product innovation within South African financial services, focusing on issues of fairness and transparency. As AI continues to transform the financial sector, ensuring responsible and equitable implementation has become a non-negotiable. Current AI practices across selected South African banks are examined by analysing challenges such as algorithmic bias, the need for financial inclusion, and the intricacies of data privacy. Drawing on qualitative data and thematic analysis from twelve semi-structured interviews, the research evaluates how these institutions address ethical dilemmas associated with the use of AI and their observance of regulatory frameworks that prioritise fairness, transparency, and accountability. To navigate these ethical challenges, this paper proposes a practical ethical framework and adoption strategy that is tailored to the unique South African context. This framework emphasizes safeguards against bias, transparency through explainable AI, continuous audits, and multi-stakeholder collaboration to ensure ethical compliance throughout AI product development. Ultimately, this research serves as a guide for South African banks, regulators, and policymakers in advancing fair, transparent, and responsible AI systems.Item Impact of enterprise development training on the performance of small retail businesses in Gauteng(University of the Witwatersrand, Johannesburg, 2024) Kazhila, Cleopatra Mwansa; Urban, BorisContext - Small, Medium, Micro Enterprises (SMMEs), which include small retail businesses, are considered as how South Africa's national development plan (NDP) will achieve its socio-economic goals. The NDP aims to ensure growth and sustainability in the country by having 90% of jobs created by SMMEs by 2030. Motivation of the study – Many other research studies have investigated how enterprise development training affects small and medium-sized enterprises in South Africa, but few, if any, have zoomed into how it affects small retail enterprises' performance, particularly in the region of Gauteng. It has, however, been argued that SMME owners who possess the right skill set will be able to obtain a significant advantage over their rivals who have not received skill training. Research purpose – This research study, therefore, sought to investigate the impact of enterprise development training on the performance of small retail businesses in the Gauteng province. Methodology – The study was quantitative and comprised 34 closed-ended questions which were designed to draw primary data from the sample population using an electronic interview survey questionnaire. Data from 132 respondents was received, cleaned out and then analysed using various mathematical modelling tools such as the Little MCAR test, regression analysis and multiple linear regression. Main findings – This research study finds that enterprise development training has an impact on the performance of small retail businesses in the Gauteng province. Contributions / Value Add – This study contributes to the existing body of knowledge by showing that enterprise training development has an impact on small retail businesses in Gauteng. It also inspires SMME owners of small retail businesses to embrace enterprise training as it has huge potential to unleash them in the South ii African economy. Policy makers have also been challenged to consider making internet connectivity affordable among small retail businesses.Item The adoption of Intelligent Applications by South African Organisations(University of the Witwatersrand, Johannesburg, 2025) Kawal, Chiresh; Sethibe, TebogoDigital disruption has impacted many industries globally. Not all industries have been equally impacted; some have experienced more disruption than others. The ICT industry, among others, is closest to the centre of the vortex indicating the extent to which it has been disrupted compared to others. Digital technologies are merging to leverage their combined capabilities in forming more powerful tools to aid industries to cope with organisational transformation. This quantitative study uses the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the relationship between the UTAUT constructs and the behavioural intention of employees to adopt intelligent applications in a South African ICT organisation. The model was extended to include General Awareness, Attitude and Trust, job classification, employment contract type, and education level as moderating variables to examine the influence on behavioural intention. The cross-sectional study included the collection of empirical data through an anonymous online survey. Respondents were also given the opportunity to respond to open-ended questions (divergent question technique) on barriers and enablers to new technology adoption. The analysis results revealed that performance expectancy and effort expectancy are not significant predictors of adoption. Social influence is a weak predictor of adoption. General Awareness, Attitude and Trust, and facilitating conditions were strong predictors of the behavioural intention to adopt intelligent applications. Key outcome topics are insufficient training, management support and strategy, financial constraints, and data management. The results of this study contribute to the body of knowledge on extended factors of UTAUT on influencing the adoption of intelligent applications in the ICT Sector. The study also provides insights to ICT leaders, talent managers, and technology service providers on factors that support the adoption of intelligent applications.Item Benefits and barriers to digitalisation of loan bursary repayment in the National Manpower Development Secretariat (NMDS) of Lesotho(University of the Witwatersrand, Johannesburg, 2025) Hlaele, Makhauhelo; Magida, AyandaThe National Manpower Development Secretariat (NMDS) in Lesotho continues to face critical challenges in recovering disbursed student loan bursaries, largely due to its reliance on outdated, manual repayment methods such as cash payments, unenforced stop orders, and bank deposits. These inefficiencies contribute to persistently low recovery rates, affecting the sustainability of the NMDS fund and the country’s broader goals for higher education access. This study explored how digital payment systems can be adopted to improve the operational efficiency of loan bursary repayments and enhance recovery outcomes. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Diffusion of Innovations (DOI) theory, the research employed an interpretivist paradigm and a qualitative case study design. Data was collected through semi-structured interviews with seven purposively selected participants, including NMDS administrators and IT personnel. Thematic analysis revealed that while digitalisation offers transformative benefits—such as enhanced repayment tracking, reduced fraud, and streamlined administrative processes— it is hindered by low digital literacy, infrastructural gaps, funding constraints, and lack of regulatory enforcement. The study incorporated a comparative analysis of student loan repayment models in South Africa (NSFAS), Kenya (HELB), and Uganda (HESFB), revealing valuable lessons for phased implementation, automation of deductions, and strategic partnerships. The research concludes with a detailed implementation roadmap for NMDS, structured around short-, medium-, and long-term strategies. These include conducting a digital readiness assessment, piloting integrated systems, updating legal frameworks, and building digital capabilities. The findings offer practical guidance for policy reform and digital transformation in higher education financing and contribute to the growing body of knowledge on public- sector innovation in developing countries.Item Gender inclusivity towards a just energy transition in South Africa(University of the Witwatersrand, Johannesburg, 2025) Geen, Valerie; Gobind, JenikaTo avoid the escalating impacts of climate change, governments have increasingly committed to a net zero decarbonisation trajectory by 2050. As a country which is the largest carbon emitter in Africa due to its high fossil fuel dependence, South Africa committed to a just energy transition at the Conference of the Parties (COP 26) in 2021. This commitment was conditional on pledges being honoured by international partners to support South Africa in capacity building, technology and finance. Premised on the intention for the energy transition to be just and inclusive, this study investigated how gender inclusivity could be advanced. Based on the theoretical framework of energy justice theory, this study used the lens of the adapted engendered energy justice conceptual framework to inform its qualitative study of South Africa’s just energy transition to clean energy. The qualitative study interviewed a selected sample of 11 key informant interviewees (KII) and examined the barriers to gender inclusion. The findings confirm that the Just energy transition is underway and has accelerated recently. While it potentially may offer more opportunities for women, there is a need to introduce gender mainstreaming and the integration of broader energy justice principles into the transition. The development of a long-term energy vision and strategy is recommended. Finally, the study proposes that the energy strategy and gender mainstreaming should be part of a national dialogueItem The adoption of big data analytics in South African financial institutions(University of the Witwatersrand, Johannesburg, 2024) Dlamini, Mzwandile; Kalema, Billy M.Financial institutions by nature of their operations handle a lot of information, to examine and extract value from the data they receive. However, with the increasing automation, the data they receive have change in volume and the speed at which it is generated necessitating them to learn new techniques to analyse this voluminous data also known as Big Data (BD). Much as this is so, there are still fewer frameworks and models that have been developed to guide the adoption of this big data analytics (BDA). More still, the available frameworks are not contextualised to perspectives of South African financial institutions. The main goal of the study was to develop a framework for the adoption of BDA in South African financial institutions. The technology-organisation-environment (TOE) framework was used as the underpinning theory for this study based on which a conceptual framework was designed. A close-ended questionnaire was used to collect data from a South African financial institution in the Gauteng Province. Random sampling to select the 130 respondents that participated in the study. Results revealed that technological factors, technological characteristics, users’ perception towards technology, organisational factors due to top management support, individual characteristics and BD characteristics are essential in BDA adoption. However, the results also indicated that organisational factors, organisational factors due to size and structure of the organisation and environmental factors were not significant in the adoption of BDA. This study contributes to the studies of BDA adoption in organisations in developing nations. The degree of influence that different factors have on adoption of technologies differs depending on the context, future studies can leverage these findings to extend research in BDA adoption. This study recommends that future research expand data collection to include more organisations that are categorised as financial institutions to properly generalise the study’s findings.Item Adoption of Generative AI in Loyalty Programmes to Enhance Customer Engagement in South Africa(University of the Witwatersrand, Johannesburg, 2025) Digama, Ramaesela Hazel; Moodley, KebashneeThis research investigated the adoption of generative artificial intelligence (GenAI) in loyalty programmes and its potential to enhance customer engagement in South Africa. The study explores how businesses can leverage GenAI technologies to foster stronger relationships with their customers, increase participation in loyalty programmes, and drive growth and loyalty within the South African market. The research method involved conducting interviews with ten senior management professionals from both the business and technology sectors of an organisation planning to adopt GenAI in its loyalty programme. Using the Technology-Organisation-Environment (TOE) framework, the study assessed the factors influencing GenAI adoption. This approach provided a comprehensive evaluation of the technological, organisational, and environmental aspects impacting the successful implementation of AI-driven personalisation. Findings suggest that GenAI can drive hyper-personalisation, improving customer loyalty and engagement through tailored rewards and real-time experiences. However, challenges like departmental misalignment, knowledge gaps, and change management need to be addressed for successful adoption. Ethical concerns regarding privacy, algorithmic bias, and inclusivity also need to be considered. Recommendations include improving data quality, aligning strategies, addressing change management, and ensuring ethical AI practices to unlock GenAI's full potential. The contribution of this research will benefit key stakeholders, including organisations looking to enhance customer engagement with GenAI, policy bodies creating frameworks to support innovation and ethical practices, tech developers tailoring solutions for successful implementation, and the academic community advancing discussions on GenAI’s impact on consumer-focused innovation.Item Consumer-based factors in applying dynamic pricing in a digital context in South Africa(University of the Witwatersrand, Johannesburg, 2024) Demrugaram, Kaajal; Godspower-Akpomiemie, E.This study examined dynamic pricing, an academic field that analyses and determines the most advantageous selling prices for items or services. The study found consumers are opposed to paying transactions, scarcity, urgency, and specific categories of goods and services fees. They are willing to pay more for personalised offers, fair pricing, transparent pricing strategies, and customer treatment. The study confirms the results of the Ariely experiment, suggesting that customer-based factors influence willingness to pay for a product or service. The study suggests that dynamic pricing can effectively increase revenues and company valuations for online retailers, when implemented fairly and justifiably. Consumers are tolerant of price variations where fluctuating demand is expected, given the price differential is not excessive. Firms in industries with limited resources and fluctuating demand are more able to implement dynamic pricing. Online retailers must allocate resources and determine suitable artificial intelligence (AI) solutions to address negative customer reactions. AI and machine learning (ML) are pivotal in forecasting and facilitating tailored experiences in big data analytics. Adopting AI and ML is key for dynamic pricing, especially regarding price sensitivity and irrationality. Recommendations for sellers include developing consistent, transparent, and simple policies that align with consumer expectations. Companies should carefully consider price discrimination and increase transparency to offset negative effects. Future research should consider Consumer factors, pricing optimisation for lower-income consumers, and longitudinal studies. The study's limitations include insufficient data for younger generations, potential biases due to generational opinions, and a bias favouring individuals with higher socio- economic levels.Item The adoption of AI for project portfolio management in South African financial services(University of the Witwatersrand, Johannesburg, 2025) Chisuro, Kundishora; Hughes, MitchellThe growing potential of artificial intelligence (AI) to improve project portfolio management (PPM) through better decision making, resource optimisation and strategic alignment is creating new opportunities for the South African financial services sector. This study examines the key technological, organisational and environmental factors influencing the adoption of AI for PPM, filling an important gap in research on emerging markets. Using the Technology-Organisation- Environment (TOE) framework, the study adopts a quantitative, cross-sectional design. Based on a literature review, nine key factors were identified and included in a questionnaire to assess their importance. The data was collected from IT and project management employees in South African financial services organisations. Covariance-based structural equation modelling (CB-SEM) was used to analyse the relationships between these factors and the adoption of AI. The results show that high data quality and a favourable investment environment are the most important factors. Organisational readiness, technological infrastructure, top management support, supportive culture and government regulation also have a positive influence. In contrast, the availability of AI technologies and skilled technical personnel has a negative effect when considered alone, suggesting that these factors may hinder adoption without additional support. Although the study focuses on the South African financial services sector, which may limit the generalisability of the findings, it provides useful insights into the factors driving AI adoption. The findings provide recommendations for financial organisations, IT leaders, project management stakeholders and policy makers to support AI integration, guide strategic decisions and develop frameworks that promote responsible AI adoption while driving innovation. This research contributes to the theoretical understanding of AI adoption for PPM in emerging markets, particularly in South Africa. By applying the TOE framework and CB-SEM, it highlights the importance of an integrated approach considering the interplay of technological, organisational and environmental factors.Item Investigating Factors Influencing Pro-Environmental Behaviour Among Students at the University of the Witwatersrand(University of the Witwatersrand, Johannesburg, 2024) Chipoka, Nyashadzashe; Mazonde, NomusaThis quantitative study investigated the factors influencing pro-environmental behaviour (PEB) among students at the University of the Witwatersrand (Wits), guided by the theory of planned behaviour (TPB). This research explored the roles of environmental knowledge, social influence, sense of control, and demographic characteristics in shaping PEB among a diverse student population in South Africa. The study revealed that social influence, particularly within the university context, emerged as a powerful predictor of PEB, with the university environment exerting a stronger influence than family. Results indicated a significant positive correlation between environmental knowledge and PEB yet highlighted a gap between awareness and proactive information-seeking. Perceived behavioural control (PBC) also significantly and positively correlated with PEB, although variability across different actions suggested barriers unique to each situation. Notably, while gender and education level did not significantly predict PEB, age and field of study did, emphasising the need to consider the specific institutional and cultural context when examining the impact of any demographics on PEB. The findings from the study suggest that while the TPB provides a useful framework for understanding PEB, incorporating insights from other behavioural theories and considering demographic moderators may enhance its explanatory power. Recommendations for Wits include integrating pro-environmental practices into educational programmes, campus culture, infrastructure, academic disciplines, and providing financial incentives and promoting a sense of collective responsibility.