4. Electronic Theses and Dissertations (ETDs) - Faculties submissions
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Item Influence of AI Personalisation on E-commerce customer experience and purchase decisions in South Africa(University of the Witwatersrand, Johannesburg, 2024) Sookhdeo, Lavina; Moodley, KebashneeCovid-19 has underscored the importance of organisations to invest in E- commerce for sustainability and has accelerated E-commerce adoption globally and in South Africa. E-tailers need to look beyond product catalogues and competitive pricing and promotions for differentiation and look towards providing superior customer experience for competitive advantage. Artificial Intelligence is a transformational technology that can be harnessed for enhanced personalised interactions and customer experience in E-commerce. The study investigates Artificial Intelligence (AI) capabilities that enable personalisation features in E-commerce, and examines how the Perceived Usefulness, Perceived Ease of Use, Relative Advantage and Voluntariness of Use of AI personalisation features in this medium influence Customer Experience, Purchase Intention, Repeat Purchases Intention and Loyalty. An online survey was conducted with local online shoppers to gather their feedback on the use of AI-enabled personalisation features on E-Commerce. Factor analysis including Exploratory factor analysis (EFA), Confirmatory Factor analysis (CFA) and Structural Equation Modelling (SEM) was used to analyse the results. The results indicate that both Relative Advantage and Voluntariness of Use of AI personalisation in E-commerce, positively and significantly influence Customer Experience as well as customer Purchase Decisions. Perceived Ease of Use positively influences customer experience and negatively influences purchase decisions, although both effects are insignificant. Finally, Perceived Usefulness is found to have a negative, albeit insignificant influence on both Customer Experience and Purchase Decisions. These findings contribute a South African perspective on understanding customer perceptions of AI personalisation applications in E-Commerce.Item Investigating the Consumer Implications of Artificial Emotional Intelligence (AEI) in the context of Digital Banking in South Africa(University of the Witwatersrand, Johannesburg, 2024) Reddy, Sanussha; Genga, CherylA revolution in human-computer interaction has been brought about by the swift developments of artificial intelligence (AI), especially following the emergence of artificial emotional intelligence (AEI). The integration of AEI in the South African digital banking industry was investigated in this master's thesis, along with the potential and limitations it represented. The study used a quantitative research technique to collect data from Gauteng region residents who use digital banking. Surveys were used to evaluate user experience, ethical issues, and the effect of AEI on consumer trust and privacy. The results showed that although AEI improved user experiences by offering emotionally intelligent and tailored interactions, it also brought up serious issues with data security, privacy, and the possibility of emotional abuse. Additionally, the study revealed a significant deficiency in the existing regulatory structures, which had difficulty keeping up with the rapid advancements in technology. By giving a thorough examination of how AEI affected user habits and banking practices, the study added to the body of knowledge in the academic community. It also made recommendations for digital banking institutions on how to create strong policies and frameworks for the moral use of AI technology. This study contributed to the wider conversations on AI ethics and legal requirements while also deepening our understanding of AEI in the context of digital bankingItem The adoption of AI in the South Africa Supply Chain Industry(University of the Witwatersrand, Johannesburg, 2024) Naidoo, Prenesen; Oba, PiasThe adoption of Artificial intelligence (AI) in supply chain management shows great promise for the future, by identifying and removing waste, which in turn will increase efficiencies and competitiveness within the supply chain industry. The COVID-19 pandemic has fast tracked the use of technology and AI is no different to other technologies. The significance of the research is to unpack the influence of AI adoption within one of the major industries in South Africa, the study focused on South Africa which has a unique socio-economic landscape. The study unpacks how this influences AI adoption, for example, the skills required to deploy and maintain AI, as well as the potential impact on employment (in a country with a high unemployment rate). The study evaluated the readiness for AI adoption in the country. The study analysed a company that has recently been purchased by an international conglomerate, although the company is a major player in the South African supply chain. The researcher used interviews conducted with executives (senior roles), at a company, as well as existing literature to understand the current adoption of AI in South African supply chains. Thematic analysis of the qualitative data was employed to identify trends in the adoption of AI and understand frameworks that may have been used in the adoption. The research found that there was a case in South Africa for the deployment of AI in the supply chain industry, although South Africa does not have the required socio-economic environment for AI to be deployed, due to the high unemployment, and low readiness for AI adoption, as well as low skills for AI adoption. The implication of the study is understanding the current view of iii where AI adoption falls in the supply chain industry from a priority perspective. Is there an appetite for companies within the Supply Chain industry to adopt AI. The research concludes that a more in-depth study is required extending the research beyond one organisation.Item Examining the role of AI ethics in establishing Human-AI Workplace Coexistence in a selected Telecommunications Organisation in South Africa(University of the Witwatersrand, Johannesburg, 2024) Muir, ElmarieArtificial Intelligence technologies reinvent how we live, work, and organise our daily lives and social interactions. It brings about operational efficiencies, customer service enhancements, and organisational innovations for organisations, redefining the future landscape that will open new dimensions beyond distance, distortion, and space. Despite these benefits, using AI raises enormous concerns for telecommunication organisations beyond data protection and security vulnerabilities, including introducing ethical dilemmas due to the technology's accountability, transparency, algorithmic bias, explainability issues, and the potentially dire ramifications for employment. These issues inherent in AI technology and its concerns make it necessary to explore the ethical considerations and the role of AI ethics in establishing a harmonious human-AI workplace coexistence in the telecommunications workplace. A qualitative methodology was undertaken with purposively selected participants based on their telecommunications industry experience and exposure to AI technologies in the organisation, which allowed participants to be interviewed to gain insights into their perspectives. The research findings show that employees have real job insecurities for their future and their technological readiness to work alongside this technology. Key themes highlighted ethical AI practices, with participants advocating for transparency and accountability. Trust in the organisation and trust in AI technology, with proactive engagement with employees and stakeholders, are pivotal to mitigating their concerns and creating a conducive environment for successful integration. Furthermore, upskilling is vital for establishing trust in AI. In conclusion, the consensus is that although ethical guidelines are essential, more than ethics alone may be required to establish human-AI workplace coexistence. Instead, the organisation should cultivate an organisational culture iii that supports ethical AI practices with a robust governance framework to ensure adherence to ethical guidelines is followed and responsible use of AI. Furthermore, leaders must ensure openness and transparency about their intentions to adopt AI, foster trust in the organisation that AI strategies are not designed to replace workers and develop the necessary technological competencies through targeted skill development to build trust in the technology. This will allow the organisation to be successful in their AI adoption journey and establish collaborative intelligence for harmonious human-AI workplace coexistence.Item Readiness of South African fee-paying public high schools in Gauteng in adopting 4IR technologies in alignment with Education 4.0(University of the Witwatersrand, Johannesburg, 2023) Mokhwesana, Ramantiii ABSTRACT Far-reaching implications are being observed regarding how people engage, live, work, and educate themselves due to the requirements of the Fourth Industrial Revolution. The fusion of physical, human, and digital worlds is becoming increasingly evident. The redefinition of industries and the edification of people has led to the emergence of concepts like Education 4.0. which is characterised by intelligent technologies like three-dimensional printing (3D Printing), the Internet of Things (IoT), big data, data analytics, machine learning (ML), gamification, and augmented reality (AR). Literature in this field highlights the disruptive nature of these 4IR technologies, particularly in the education sector. Purpose: This study investigated the readiness level of South African fee-paying public high schools in Gauteng in their adoption and implementation of 4IR technologies in alignment with the objectives of Education 4.0. The outcomes of the study aimed to provide valuable insights into the factors that may have impacted the adoption or lack thereof of 4IR technologies in the classroom and thus offered remedial solutions where applicable. Research Design and Methodology: A generic qualitative research design was employed to explore stakeholder perspectives on the benefits of 4IR technologies in education. Semi-structured interviews were conducted using snowball sampling to gather data. Thematic analysis, specifically an inductive approach, was chosen to identify and interpret emerging themes from the interview transcripts. This research design and methodology provided an in-depth understanding of stakeholder experiences and insights. The total sample size comprised eleven participants. Key Findings: The study revealed both potential benefits and challenges associated with adopting and integrating 4IR technologies in the educational facilities under study. Educators generally perceived value in 4IR technologies for enhancing education quality. Potential benefits identified included personalised learning, active learning, and preparing students for future work iii contexts. However, challenges such as restricted access to technology, inadequate infrastructure, and insufficient training were also identified as potential barriers to adoption. Recommendations: The study recommends targeted interventions to address challenges and leverage opportunities for integrating 4IR technologies in foundational education contexts. These include exploring alternative financing models, implementing comprehensive and ongoing training programs, revising the curriculum policy statement, and effecting infrastructural improvements.Item The implication of AI-generated music on the industry's business model(University of the Witwatersrand, Johannesburg, 2024) Lothe, NkosinathiThis research report explores how AI-generated music is changing the traditional music industry model. The study uses qualitative research to examine how AI technology affects music creation, distribution, and consumption. It uncovers the challenges and opportunities AI-generated music brings to different music industry players. The research gives insights into how music production is evolving in the digital age by analysing user views, legal frameworks, and economic impacts. Stakeholders can adapt to the changing industry landscape by understanding how AI impacts music. The study shows how AI reshapes music creation and distribution, offering new possibilities for artists and businesses. As technology continues to influence the music industry, grasping the implications of AI- generated music is crucial for staying relevant and innovative in this dynamic environmentItem The Impact of Artificial Intelligence on the future of jobs in the South African automotive sector(University of the Witwatersrand, Johannesburg, 2024) Setati, PortiaThis report attempted to provide insights on the impact of Artificial Intelligence on the future of work in the automotive industry. The aim of this paper was to identify the potential benefits and challenges of AI adoption in the automotive sector and to develop strategies to maximize the benefits while mitigating the risks. South Africa, a significant player in the global automotive market, faces unique challenges and opportunities as AI integration progresses.The study employed a qualitative method approach and conducted semi-structured interviews to gather data. By examining current trends and future projections, the research interprets how AI technologies are reshaping traditional automotive manufacturing processes and workforce dynamics.Findings suggest that while AI adoption promises enhanced productivity, efficiency, and product quality, it also poses challenges in terms of workforce displacement, skill gaps,and job redefinition. The South African automotive industry, characterized by a diverse workforce and socio-economic disparities, must navigate these changes with a strategic approach to ensure inclusive growth and equitable distribution of opportunities.This research contributes to a deeper understanding of the transformative impact of AI on the future of work in the South African automotive industry, offering insights into the opportunities and challenges that lie ahead and proposing strategies for harnessing AI's potential for inclusive and sustainable growthItem Sustainability and performance of the South African mining industry in supply chain management post Covid-19(University of the Witwatersrand, Johannesburg, 2024) Malebana, Marakeng; Totowa, JacquesThe COVID-19 pandemic has significantly impacted global supply chains, disrupted operations, and caused delays across various industries. The mining industry in South Africa was not immune to some of these problems. Gradually, restrictions eased, businesses reopened, and supply chain performance slowly improved. However, the pandemic has highlighted the importance of building resilience in supply chains to prepare for future disruptions. Mining firms in South Africa should re-evaluate their supply chain strategies, looking to diversify suppliers, shorten lead times, and increase transparency to mitigate risks. Moreover, adopting advanced technologies like artificial intelligence, Blockchain, and the Internet of Things should assist firms in managing their supply chains better, improving visibility, and enhancing overall performance. This study examined the post-COVID-19 supply chain management performance in the mining industry. This was quantitative research, and the population of the study was 319 and 175 respondents across five mining companies in South Africa. The study developed and empirically tested hypotheses to determine the influence of supply chain network design, information systems, organizational structure, and supply chain strategy on supply chain finance and performance. The research suggests that mining firms in South Africa must radically improve their supply chain design, organization structure, and strategy and deploy information systems such as blockchain, machine learning, AI, and ERP to enhance industry performance. The current supply chain challenges in the industry require building capabilities and sharing resources among firms to alleviate the cost and other problems in logistics. The study contributes to the body of knowledge in supply chain management and offers a proposition to management on how to resolve the bottleneck in industry support to improve industry performanceItem The role of personalisation in digital advertising on consumer decision making in the South African context.(University of the Witwatersrand, Johannesburg, 2024) Jansen, Bareile; Ndlela, ThubelihleThe surge in digital advertising has redefined the consumer landscape, profoundly impacting decision-making processes related to brand and product choices, which has ultimately led to digital brand saturation (Agrawani, 2022). Digital brand saturation could potentially lead to consumer decision making frustration, unnecessary marketing to the wrong audience, costly expenses related to that, and an increase in the need for personalisation (Agrawani, 2022). Despite extensive research on digital advertising's impact on consumer decisions, there is a lack of studies focusing on the effects of personalisation on consumer behaviour in South Africa. This study employs a qualitative approach, using semi-structured interviews analysed via thematic analysis, with convenience sampling to select the 20 participants for this study (Creswell & Creswell, 2018). This method was practical for gathering data efficiently within the study’s constraints. The findings of the study highlight the critical role of relevant advertising in engaging consumers and underscore the importance of ethical data practices to build consumer trust Drawing upon foundational literature in consumer behaviour, marketing ethics, and cross-cultural studies, this study seeked to inform decision-making and promote ethical practices in personalised advertising. The conclusions emphasise the critical importance of relevance, transparency, and consumer autonomy in developing effective advertising strategies and building trust in brand-consumer relationships. By integrating these elements, the study underscores the need for aligning advertising practices with ethical standards to foster meaningful and trustworthy interactions between brands and consumers.Item The application of machine learning methods to satellite data for the management of invasive water hyacinth(University of the Witwatersrand, Johannesburg, 2023-06) Singh, Geethe; Reynolds, Chevonne; Byrne, Marcus; Rosman, BenjaminBiological invasions are responsible for some of the most devastating impacts on the world’s ecosystems, with freshwater ecosystems among the worst affected. Invasions threaten not only freshwater biodiversity, but also the provision of ecosystem services. Tackling the impact of invasive aquatic alien plant (IAAP) species in freshwater systems is an ongoing challenge. In the case of water hyacinth (Pontederia crassipes, previously Eichhorniae crassipes), the worst IAAP presents a long-standing management challenge that requires detailed and frequently updated information on its distribution, the context that influences its occurrence, and a systematic way to identify effective biocontrol release events. This is particularly urgent in South Africa, where freshwater resources are scarce and under increasing pressure. This research employs recent advances in machine learning (ML), remote sensing, and cloud computing to improve the chances of successful water hyacinth management. This is achieved by (i) mapping the occurrence of water hyacinth across a large extent, (ii) identifying the factors that are likely driving the occurrence of the weed at multiple scales, from a waterbody level to a national extent, and (iii) finally identifying periods for effective biocontrol release. Consequently, the capacity of these tools demonstrates their potential to facilitate wide-scale, consistent, automated, pre-emptive, data-driven, and evidence-based decision making for managing water hyacinth. The first chapter is a general introduction to the research problem and research questions. In the second chapter, the research combines a novel image thresholding method for water detection with an unsupervised method for aquatic vegetation detection and a supervised random forest model in a hierarchical way to localise and discriminate water hyacinth from other IAAP’s at a national extent. The value of this work is marked by the comparison of the user (87%) and producer accuracy (93%) of the introduced method with previous small-scale studies. As part of this chapter, the results also show the sensor-agnostic and temporally consistent capability of the introduced hierarchical approach to monitor water and aquatic vegetation using Sentinel-2 and Landsat-8 for long periods (from 2013 - present). Lastly, this work demonstrates encouraging results when using a Deep Neural Network (DNN) to directly detect aquatic vegetation and circumvents the need for accurate water extent data. The two chapters that follow (Chapter 3 and 4 described below) introduce an application each that build off the South African water hyacinth distribution and aquatic vegetation time series (derived in Chapter 2). The third chapter uses a species distribution model (SDM) that links climatic, socio-economic, ecological, and hydrological conditions to the presence/absence of water hyacinth throughout South Africa at a waterbody level. Thereafter, explainable AI (xAI) methods (specifically SHapley Additive exPlanations or SHAP) are applied to better understand the factors that are likely driving the occurrence of water hyacinth. The analyses of 82 variables (of 140 considered) show that the most common group of drivers primarily associated with the occurrence of water hyacinth in South Africa are climatically related (41.4%). This is followed by natural land cover categories (32.9%) and socio-economic variables (10.7%), which include artificial land-cover. The two least influential groups are hydrological variables (10.4%) including water seasonality, runoff, and flood risk, and ecological variables (4.7%) including riparian soil conditions and interspecies competition. These results suggest the importance of considering landscape context when prioritising the type (mechanical, biological, chemical, or integrated) of weed management to use. To enable the prioritisation of suitable biocontrol release dates, the fourth chapter forecasts 70-day open water proportion post-release as a reward for effective biocontrol. This enabled the simulation of the effect of synthetic biocontrol release events under a multiarmed bandit framework for the identification of two effective biocontrol release periods (late spring/early summer (mid-November) and late summer (late February to mid-March)). The latter release period was estimated to result in an 8-27% higher average open-water cover post-release compared to actual biocontrol release events during the study period (May 2018 - July 2020). Hartbeespoort Dam, South Africa, is considered as a case study for improving the pre-existing management strategy used during the biocontrol of water hyacinth. The novel frameworks introduced in this work go a long way in advancing IAAP species management in the age of both ongoing drives towards the adoption of artificial intelligence and sustainability for a better future. It goes beyond (i) traditional small-scale and infrequent mapping, (ii) standard SDMs, to now include the benefits of spatially explicit model explainability, and (iii) introduces a semi-automated and widely applicable method to explore potential biocontrol release events. The direct benefit of this work, or indirect benefits from derivative work outweighs both the low production costs or equivalent field and lab work. To improve the adoption of modern ML and Earth Observation (EO) tools for invasive species management, some of the developed tools are publicly accessible. In addition, a human-AI symbiosis that combines strengths and compensates for weaknesses is strongly recommended. For each application, directions are provided for future research based on the drawbacks and limitations of the introduced systems. These future efforts will likely increase the adoption of EO-derived products by water managers and improve the reliability of these products.