Faculty of Commerce, Law and Management (ETDs)

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    The Factors Influencing the Adoption of Big Data in the Financial Services Sector in South Africa
    (University of the Witwatersrand, Johannesburg, 2023) Toma, Upenyu; Ndlovu, Chiedza
    This investigation examines factors influencing the adoption of big data in the South African banking sector. The dearth of studies on big data in the sector inspired the research. The investigation interrogates factors that influence the adoption of big data using the TOE model. The study used a total of 173 respondents across 53 South African banks. The primary data analysis model used was linear regression. The study’s findings are as follows: [1] Government regulations, competitor’s actions, and customer demands significantly influence adoption of big data. [2] Technology has a significant influence on the adoption of big data. [3] Organizational factors have a significant influence on the adoption of big data. Regression analysis showed that the dependent variable, big data adoption, is either positively or negatively affected by the study's variables. The study conducted a hypothesis test, which showed enough evidence to accept all alternative hypotheses suggesting a relationship between the variables and big data adoption. The study concludes that factors in the TOE model influence the rate of big data adoption in the banking sector. The study recommends that the government reduce regulations hindering big data adoption. The industry is encouraged to invest in big data for sustainable competitive advantage.
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    Factors Influencing Artificial Intelligence Adoption in South African Organisations: A Technology, Organisation, Environment (TOE) Framework
    (University of the Witwatersrand, Johannesburg, 2023) Hoosen, Kaneez Fathima; Cohen, Jason
    Artificial intelligence (AI) refers to the formation of machines that mimic human intelligence and encompasses various technologies. AI technology is changing the landscape for South African organisations and how they operate. Using current literature and other online reports by auditing firms, the study aimed to identify a suite of AI technologies used by South African organisations. Technologies such as robotic process automation, image and speech recognition, machine learning and chatbots were defined. In addition, this research paper investigated the factors influencing AI technology adoption by South African organisations. The technology, organisation and environment factors of the TOE framework were examined to understand adoption decisions. It was important to close this gap as lack of understanding of how factors influence AI decisions, and an undefined suite of AI technologies could impact adoption decisions. A cross sectional relational research design was chosen for the study. A survey instrument was used and administered through a web-survey to 252 IT decision makers or IT leaders from South African organisations who served as key informants for their organisations. Responses were received from 55 organisations. Reliability and validity tests were used to evaluate the consistency and reliability of the data and to evaluate whether measures correctly represent the variables that they intend to measure. Correlation analysis, stepwise and multiple regression were used to test the hypotheses of the conceptual model. It was found that of the suite of AI technologies, robotics process automation followed by machine learning and image recognition had the highest levels of adoption. Results showed that data availability and top management support were supported as the most significant technology, organization, environment (TOE) factors influencing AI technology adoption in South African organisations. It was found that perceived technology benefits, IT infrastructure, resource capability and normative pressure were also strongly correlated to AI technology adoption. Financial resources and competitive pressure were not supported as determinants. Artificial intelligence is receiving much attention in both practice and research. This study addresses the gap in the current body of knowledge on AI adoption in South Africa by making use of the TOE framework to study adoption of artificial intelligence technologies in organisations. Useful insights are provided to South African organisations so that they can benchmark their adoption against other industry players and manage their response to those factors most significant for AI adoption
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    A comparative study of green taxation in South Africa, Australia, Singapore, and India
    (University of the Witwatersrand, Johannesburg, 2023) Mokwena, Dankie; Kolitz, Maveve
    Global warming and climate change have been on the agenda for years, with discussions on dealing with and mitigating their effects on humanity and the environment (Brink, 2019, Para. 1) Industrialization, as the driver of economic development, has resulted in massive pollution emissions (Ahhmad and Zhao, 2018:3). In an effort to protect the environment and encourage sustainability, tax policies and mechanisms have been used and trusted as effective methods for government to influence society`s behavior (Brink, 2019, Para. 2). Government across different countries have introduced green taxation, including tax incentives, cash grants, and soft loans aimed at encouraging investment in environmental, social, and governance-related projects (PwC, 2023a:3)