4. Electronic Theses and Dissertations (ETDs) - Faculties submissions

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    Attitude and acceptance of Artificial Intelligence technologies in the South African financial services. industry
    (University of the Witwatersrand, Johannesburg, 2024) Wotela, Ruth Rumbidzai; Maier, Christoph
    Despite Artificial Intelligence (AI) being topical, the successful adoption of AI technologies within organisations has been slower than expected. Literature and past research highlights the mixed and contradictory views and findings regarding employees’ attitude and acceptance of AI technologies, which challenge the successful implementation and use of AI technologies. Further, research on employees’ attitude and acceptance of AI technologies in emerging market economies, such as South Africa, and specifically within mandatory settings is limited. The purpose of this research was to investigate and determine factors influencing employees’ attitude and acceptance of AI technologies amongst employees within the financial services industry, where the use of AI technologies is mandatory. The Technology Acceptance Model (TAM) and the Technology-Organisation-Environment (TOE) framework were integrated and extended. This quantitative research study used a cross-sectional design. An online survey was distributed to employees within financial services organisations. A total of 410 valid responses were analysed using descriptive statistics, correlation analysis and regression analysis. Textual responses from the open-ended questions were categorised and presented visually in the form of word clouds. The research results indicate that each of the technological, individual, organisational, and environmental factors have a significant positive effect on attitude towards use of AI technologies. Multiple regression and stepwise regression analysis were used to identify the most influential determinants of attitude towards use of AI technologies from all the technological, individual, organisational and environmental factors. The results indicate that employee wellbeing, competitive pressure, perceived usefulness, management support, perceived ease of use, organisational justice and customer pressure are key determinants of attitude towards the use of AI technologies. The attitude-acceptance relationship is confirmed, as attitude towards use of AI technologies positively influences the acceptance of AI technologies. Although employees’ job roles do not moderate the relationship between attitude and acceptance of AI technologies, their experience with using AI technologies does. Based on these findings the ITOE model for implementing AI technologies is developed, and can be used to facilitate the successful implementation and use of AI technologies. The implications of this research, as well as recommendations for organisations and future research are also discussed.
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    An exploratory analysis of the environmental and social incentives of key management personnel for JSE-listed companies
    (University of the Witwatersrand, Johannesburg, 2024) Haripersadh, Shriya; Burnham, Kayleigh; Van Zijl, Wayne
    Societal pressure on companies to be environmentally and socially responsible as well as stock exchange requirements have led to the wide adoption of integrated reporting by public companies in South Africa (Baboukardos & Rimmel, 2016; De Villiers et al., 2014; IoDSA, 2016; Lokuwaduge & Heenetigala, 2017; Moloi & Iredele, 2020). The prior literature discusses the importance of remuneration linked to Key Performance Indicators (KPIs). Consequently, analysing whether Key Management Personnel (KMP) have non-financial KPI-linked remuneration provides strong evidence of a company’s commitment to being socially and environmentally responsible. Currently, no research investigates this globally and in the South African context. This study presents a comprehensive comparative analysis of the integration of environmental and social (ES) KPIs in KMP remuneration for South African Johannesburg Stock Exchange listed companies. Data was collected from twenty companies from the JSE’s top, middle and small capitalization companies at different points in time (2011, 2018 and 2022) using content analysis to provide a total sample of 60 companies with 180 firm-years. Data was analyzed using descriptive and inferential statistics. The prevalence, distribution and settlement methods of E, S, and combined ES KPIs in KMP remuneration structures were examined. Utilising both agency theory and stakeholder theory, the research explores how linking the remuneration of KMP to ES KPIs may serve the interests of both shareholders and stakeholders. The findings reveal a progressive adoption of ES KPIs in KMP remuneration structures over the investigated years, with notable variations observed across industries and company size. Larger companies and companies with higher social and environmental impacts utilize more ES KPIs in their remuneration policies. Industry-specific trends influencing the integration of ES KPIs were identified, shedding light on the evolving landscape of corporate governance and sustainability practices. By elucidating the dynamics between KMP remuneration and environmental and social performance metrics, this study contributes to a deeper understanding of how companies incentivise responsible leadership and foster sustainable business practices.
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    Hydrogeological assessments and investigation of inflow sources at Lumwana Copper Mine, Zambia
    (University of the Witwatersrand, Johannesburg, 2023) Mbilima, Mike; Abiye, Tamiru
    This Research Report presents results of integrated field and desktop-based hydrogeological investigations at the Lumwana Mine, Zambia. Groundwater occurrence in the mine poses challenges with effective mining operations and slope stability. The primary aim of this study was to establish the sources of groundwater inflows and to establish the nature of surface water and groundwater interaction within the Lumwana Mine hydro-geotechnical units. The Lumwana hydrogeological investigation has been achieved through the integration of multi-disciplinary data types, which include geology, structures, hydrochemistry, meteorological data (rainfall, temperature, humidity and evapotranspiration), environmental isotopes, dewatering pumping records, groundwater level monitoring, water temperature, general hydrogeological data and surface hydrology. The investigation has confirmed the presence of hydraulic connections between different surface water bodies such as dams, diversion channels, streams and open pit excavation, and has proven to be a useful approach in tracing the source of mine inflows. Rainfall, groundwater and surface water samples have similar δ18O and δ2H isotopic signatures thus lamenting the existence of a hydraulic link between groundwater and surface water. Recharge estimation through Water Table Fluctuation method (WTF) determined 8% of mean annual precipitation (MAP). The dominant hydrochemical facies are Ca-Mg-HCO3 and Ca-Mg-SO4. The local geology and geochemistry of the tailings are the main controllers of groundwater chemistry through rock-water interaction. The geology of the study area consists of older metamorphosed gneisses, schists, migmatites, amphibolites and granitoids. Integrated assessment of the Lumwana hydrogeological environment has enabled the development of the Lumwana Mine hydrogeological conceptual model. In the shallow, highly to moderately weathered zones, groundwater flows from south towards low topographic regions in the northwest mimicking the general topography. The hydraulic test conducted at Lumwana Mine has revealed the saprock units have higher hydraulic conductivity by several orders compared to the saprolites and the fresh bedrock, where groundwater flow is mainly controlled by the occurrence and distribution of the fracture network.
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    The relationship between sustainability reporting and banks financial performance
    (University of the Witwatersrand, Johannesburg, 2023) Msimanga, Thokozani; Godspower-Akpomiemie, Euphemia
    Sustainability reporting, which involves environment, social, governance (ESG) is about reporting non-financial information regarding a company. It explains how the three sustainability components affect a company. ESG has gained significant popularity in the last ten years as new risk factors for investors are introduced by global sustainability concerns such as climate change, growing regulatory constraints, and social transformations. There is limited ESG-related research in South Africa, hence the aim of this study is to empirically evaluate whether sustainability reporting, improves financial performance and value for investors and other stakeholders. This has created a knowledge gap that may be investigated and used to start a discussion about the relationship sustainability has with financial performance from a South African banking perspective. This study’s data covered a 16-year period being, 2006 – 2021, across the six largest locally controlled banks listed on the JSE; Absa, Capitec, FirstRand, Investec, Nedbank, and Standard Bank. To examine for a statistical association, panel data regression analysis is used in this study.Multiple methods of estimation were considered, ultimately various diagnostic tests conducted concluded the fixed effects model as the most robust. A negative relationship with financial performance was found. Two models, Return on Equity and Tobin’s Q model showed a negative and significant relationship with the performance of banks. The Return on Assets model also indicated a negative relationship, but it was not statisticallysignificant. This indicates that an increase in sustainability reporting, leads to a decline in financialperformance from both an accounting and market perspective
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    Is the Environmental, Social and Corporate Governance (ESG) score the missing factor in the Fama and French five-factor asset pricing model?
    (2022) Nsibande, Luyanda Malusi Qiniso
    Background: Companies are increasingly encouraged to focus on the creation of sustainable value. In South Africa, financial research institutions evaluate and track companies’ performance based on environmental, social and governance-related criteria. These scores are intended to inform decisions by potential equity investors, amongst others. However, commonly-used asset pricing models do not include ESG scores. Purpose: The purpose of this research is to discover whether the inclusion of Environmental, Social and Governance (ESG) scores in the Fama and French fivefactor model (FF5) will improve the model’s predicting power of expected returns on the Johannesburg stock exchange JSE Methodology: For the largest 40 JSE-listed companies, statistical ordinary least squares (OLS) regression was employed with R statistics to analyse fundamental, share price and ESG score data over the five-year time period from 2015 to 2019. The researcher compared the predictive power of the FF5 model to that of the same model including ESG scores. Findings: The results showed that the predictive power of the FF5 model is only marginally improved when the ESG scores are incorporated. These findings may indicate that equity prices are not significantly influenced by ESG scores. Implications: The findings of this research provide the basis for further endeavours on the share-price implications of ESG performance. It makes a theoretical contribution by suggesting possible enhancements to traditional asset pricing techniques.
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    Is the Environmental, Social and Corporate Governance (ESG) score the missing factor in the Fama-French five factor asset pricing model?
    (2022) Nsibande, Luyanda Malusi Qiniso
    Background: Companies are increasingly encouraged to focus on the creation of sustainable value. In South Africa, financial research institutions evaluate and track companies’ performance based on environmental, social and governance-related criteria. These scores are intended to inform decisions by potential equity investors, amongst others. However, commonly-used asset pricing models do not include ESG scores. Purpose: The purpose of this research is to discover whether the inclusion of Environmental, Social and Governance (ESG) scores in the Fama and French fivefactor model (FF5) will improve the model’s predicting power of expected returns on the Johannesburg stock exchange JSE Methodology: For the largest 40 JSE-listed companies, statistical ordinary least squares (OLS) regression was employed with R statistics to analyse fundamental, share price and ESG score data over the five-year time period from 2015 to 2019. The researcher compared the predictive power of the FF5 model to that of the same model including ESG scores. Findings: The results showed that the predictive power of the FF5 model is only marginally improved when the ESG scores are incorporated. These findings may indicate that equity prices are not significantly influenced by ESG scores. Implications: The findings of this research provide the basis for further endeavours on the share-price implications of ESG performance. It makes a theoretical contribution by suggesting possible enhancements to traditional asset pricing techniques.