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This article systematically reviews literature on the challenges affecting the delivery of low-income housing in Cape Town, South Africa. A systematic method, informed by PRISMA, was employed to identify, evaluate, and select relevant scholarly works, official documents, policy papers, and governmental publications. The identified sources were subjected to a thematic analysis with the objective to pinpoint recurrent issues that impact the provision of low-income housing. The review found that low-income housing delivery in Cape Town is affected by interconnected challenges, including land availability, spatial inequality, funding constraints, infrastructure limitations, administrative delays, weak institutional coordination, limited stakeholder participation and transparency concerns. The results demonstrate that low-income housing delivery should be viewed as a major governance, planning, and service-delivery issue in addition to the building of housing units. This paper suggests that integrated human settlements, better financial planning, more transparent approval processes, more intergovernmental cooperation, significant stakeholder participation, and open communication should be given top priority when it comes to Cape Town's low-income housing delivery. Through summarizing previous research and emphasizing the necessity of an integrated strategy to address Cape Town's low-income housing issues, the article adds to the conversation regarding housing delivery.

This paper examines how drawing skills can be taught to unemployed youth in under-resourced contexts to support the expression of their lived experiences during the COVID-19 pandemic. Framed within a vocational education and training (VET) skills ecosystem orientation, the study positions creative skills development as part of broader human development and livelihood sustainability initiatives in informal settings. The paper aims to explore the potential of arts-based research (ABR) as a pedagogical and methodological approach for developing 21st-century skills, with a specific focus on drawing as a tool for communication and reflection during a crisis. We employed a qualitative arts-based research design that combined creative workshops, visual artefacts, and participant reflections. Due to pandemic-related restrictions, the research design was adapted to a digital environment, with WhatsApp used as the primary platform for skills instruction, interaction, and data collection. The dataset comprised visual drawings produced by unemployed youth participants, reflective narratives, and facilitator observations generated during a series of online creative workshops. The qualitative and visual data were analysed thematically, resulting in six key themes that captured participants’ experiences of unemployment, uncertainty, resilience, identity, and the challenges of learning creative skills in a digitally mediated, resource-constrained context. The main findings demonstrate that (i) drawing skills can be effectively taught using low-cost digital platforms, even in under-resourced settings; (ii) creative processes enable unemployed youth to articulate and reflect on their lived experiences during a pandemic; and (iii) a VET-oriented skills ecosystem provides a useful framework for situating arts-based skills development within broader livelihood and social support structures. Despite a small sample size, the study contributes practical insights into conducting arts-based research during crises and offers guidance for integrating creative skills development into informal youth skills ecosystems.

This article examines the influence of mentorship on women entrepreneurs in Cape Town, South Africa. The study assesses the extent to which mentorship contributes to personal empowerment, entrepreneurial performance, and innovation, while accounting for the effects of systemic barriers and the policy environment. A qualitative research design was employed, incorporating a systematic literature review guided by the preferred reporting items for systematic reviews and Meta-Analyses (PRISMA) framework to synthesize existing evidence. The review followed an iterative screening process, identifying three peer-reviewed studies that explicitly address mentorship in relation to women entrepreneurs within the African context. The findings from the literature indicate that women entrepreneurs across Africa face persistent structural constraints, including social-cultural norms, limited access to skills development, weak support systems, financial exclusion, and inadequate policy frameworks.  To complement the literature, primary data were collected from ten young female entrepreneurs in Cape Town who participated in a mentorship programme at RLabs. The empirical finding reinforce the significance of mentorship as a critical enabler of entrepreneurial growth, particularly in enhancing self-efficacy, business capabilities, and innovative practices. The study concludes that mentorship functions as a context-dependent and multifaceted mechanism that bridges personal empowerment and entrepreneurial outcomes. However, its effectiveness is contingent on the alignment of mentorship programmes with the specific social-economic realities of women entrepreneurs. The article recommends the design and implementation of targeted, context-sensitive mentorship interventions supported by enabling policy frameworks. While women's entrepreneurship is increasingly recognised as a catalyst for economic development in Africa, persistent systemic constraints continue to impede their full potential. This study contributes to literature by advancing a nuanced understanding of mentorship as both an individual and structural lever for entrepreneurial success within emerging economies. 

Artificial intelligence (AI) is transforming digital marketing by enabling advanced analytics, automation, and personalised customer engagement. Despite growing adoption, qualitative insights into how small retail enterprises in emerging economies adopt AI remain limited. This study examines AI adoption in digital marketing among small retailers in Cape Town using an interpretivist qualitative case study design. Grounded in an integrated Technology–Organisation–Environment (TOE) and Unified Theory of Acceptance and Use of Technology (UTAUT) framework, data were collected through semi-structured interviews with 18 participants identified via snowball sampling. Thematic analysis shows that AI adoption is driven by competitive pressure, customer expectations, and perceived performance benefits, but is constrained by skills gaps, cost concerns, and data-related challenges. The study extends TOE–UTAUT theory by demonstrating how platform-based AI tools reduce technological barriers while amplifying organisational and capability-related constraints in emerging market contexts. The findings provide actionable insights for policymakers and practitioners aiming to support sustainable digital transformation in small business ecosystems.

Small and Medium-sized Enterprises (SMEs) in South Africa’s tourism sector increasingly rely on business excellence practices to enhance competitiveness and performance. This study examines how employees in Cape Town tourism SMEs perceive business excellence, using a mixed-methods approach, combining quantitative survey data with qualitative thematic insights. The findings identify key critical success factors underpinning business excellence, namely customer and employee satisfaction, operational efficiency, and organisational growth, with satisfaction emerging as the most dominant driver of performance. Additional enabling factors include strong leadership, continuous employee training, effective communication, and the implementation of quality management practices. While most employees indicated the presence of quality plans, gaps in understanding formal business excellence frameworks were evident, suggesting a disconnect between practice and conceptual awareness. These findings reinforce the importance of service quality as central to achieving sustained competitiveness in tourism SMEs. The study contributes to the effective and efficient adaptation of business excellence in both existing and future strategies for tourism SMEs' organizational development. The study contributes empirically to the limited South African literature on business excellence in SMEs and highlights the relevance of employee-centred performance dimensions. Practically, the results suggest that tourism SMEs should prioritise staff development, embed quality management systems, and foster a culture of continuous improvement, while policymakers and industry stakeholders should support SMEs through targeted training and capacity-building initiatives to enhance the effective adoption of business excellence frameworks. The main implication of the study results is that when business excellence principles are implemented, success and better results are easily achieved.

Globally, student assessment surveys are utilised to enhance the quality of teaching and learning. Student evaluation questionnaires require a substantial investment of effort from both students and teachers.  This research aims to elucidate students' attitudes towards evaluation questionnaires, hence enhancing comprehension of the quality of information in completed assessments. The research encompassed undergraduate students enrolled in a Business and Information Management program within the Faculty of Accounting and Informatics at the Durban University of Technology, Midlands Campus, South Africa. The experiences and attitudes of students about teaching evaluation questionnaires were examined through metaphorical drawings and focus group discussions. The results reveal that students possess both favourable and unfavourable opinions toward student ratings. Positive themes encompass assessments as a systematic procedure and a chance for students to propose modifications. Negative attitudes encompass perceptions of evaluations as oppressive and threatening, reflecting a lack of profound contemplation by students when filling out the questionnaire, and raising enquiries about the subsequent activities made after completing the evaluations. Findings elucidate several elements influencing student evaluations of education, including the timing of administration, the individuals responsible for providing them, and the methods employed in their administration. The document advocates for other methods of gathering student feedback and the discontinuation of paper-based surveys. Feedback may be acquired using online questionnaires and qualitative interviews. Furthermore, learning analytics technologies can be integrated into the LMS utilised for administering online surveys, facilitating the provision of tailored feedback to individual students.

This study rigorously analysed policy deficiencies and structural vulnerabilities in climate-resilient water and sanitation governance in the Eastern Cape Province of South Africa. The research employed a qualitative approach, utilising semi-structured interviews with fifteen purposefully selected stakeholders, comprising municipal water technicians, engineers, planners, national and provincial authorities, and civil society representatives. The investigation examined the interaction between climate-induced pressures—such as droughts, floods, and rainfall variability—and governance deficiencies that undermine water and sanitation systems. The data collection concentrated on personal experiences of infrastructure failure, discrepancies between policy and reality, and obstacles in institutional coordination. Findings indicated that despite the province functioning inside advanced national frameworks like the National Water Act and the Disaster Management Act, their execution is cursory and predominantly reactive. Participants emphasised an excessive dependence on obsolete national climate models that neglect spatially distinct vulnerabilities across urban, peri-urban, and rural areas. Chronic underinvestment in infrastructure maintenance has become a persistent issue, as municipal budgets prioritise new capital projects over lifespan asset management. The technical team had institutional memory but lacked decision-making power because of bureaucratic procurement processes and disjointed interagency collaboration. The study additionally revealed significant deficiencies in real-time monitoring and enforcement capabilities, as well as gender discrepancies that marginalised women's involvement in governance frameworks. The study concludes that without immediate reforms to decentralise climate data generation, incorporate localised risk assessments, enhance preventive maintenance systems, and institutionalise participatory, technology-driven governance mechanisms, the water and sanitation systems in Eastern Cape will continue to be structurally fragile and susceptible to climate impacts. These insights provide novel empirical evidence to the discourse on sub-national climate adaptation in Africa, highlighting the necessity for multi-tiered, data-driven, and gender-sensitive reforms rooted in the realities of communities impacted by climate change.

The article seeks to explore the factors which restrict doctoral graduate throughput rates at a selected University of Technology faculty located in the Western Cape, South Africa. In a developing economy like South Africa higher education qualifications are important as it is universally accepted that doctoral studies, in particular advance knowledge and innovation is important in any society. Furthermore, doctoral graduates play a significant role in the knowledge economy, promote innovation organisations, boost credibility of organisations and connect ideas between academia and industry. A positive nexus exists between a country’s Gross Domestic Product (GDP) and the number of doctoral candidates produced. To achieve the aim of this article a qualitative interpretive design was adopted to identify the factors which restrict throughput rates and the extent or significance thereof. The locus for this study was a selected faculty in a University of Technology (UoT) located in the Western Cape, South Africa with the target research population delineated as employees who hold a master’s degree within the same faculty. Using qualitative interpretive design and thematic analysis of survey responses from 40 master’s-qualified employees, the study identifies key barriers and proposes targeted interventions. The forty participants were purposively selected to participate in the questionnaire survey. The paper will propose interventions to facilitate the improvement of the doctoral throughput rate premised on the analysis of the results arising from the questionnaire survey. The paper proposes targeted and contextualized interventions to address the systemic challenges restricting doctoral enrolment and completion by the faculty employees.

This study examines how Artificial Intelligence (AI) adoption in digital marketing enhances the competitiveness of small retail businesses (SRBs) in Cape Town, South Africa. Guided by an integrated Technology–Organisation–Environment (TOE) and Unified Theory of Acceptance and Use of Technology (UTAUT) framework, a systematic review following PRISMA 2020 guidelines was conducted across eight databases, resulting in the inclusion of 37 empirical and conceptual studies published between 2015 and 2025. Findings show that AI adoption remains modest, with only 39% of small businesses planning to develop internal AI capabilities by 2025. The most common entry points are ChatGPT, text-to-image generators, predictive analytics systems, and WhatsApp-based chatbots. Businesses using these tools reported an average 11% increase in sales and a 28% reduction in marketing costs within six months. However, adoption is constrained by infrastructure challenges (patchy broadband, power cuts, high cloud costs), organisational limitations (low digital literacy, managerial scepticism, fear of automation), and socio-cultural barriers (language diversity and customer mistrust of chatbots). This study provides the first Cape Town-focused synthesis linking AI adoption to SME competitiveness through the TOE–UTAUT framework. It recommends policy measures to improve digital infrastructure and data governance, practical initiatives to strengthen AI literacy and ethical awareness, and theoretical extensions to contextualise socio-cultural dimensions of AI use. Collectively, these insights contribute to advancing inclusive, trust-based digital transformation in Cape Town’s small business ecosystem.

Agricultural production in semi-arid regions such as Opsoek, Ladismith Karoo faces numerous challenges, including water scarcity, low soil fertility and unpredictable weather patterns. Digital innovations, particularly precision farming and mobile extension systems have proven to be important tools in overcoming these challenges and promoting sustainable agricultural practices. This case study examines the adoption and impact of precision farming technologies and mobile support services among farmers in Opsoek. The research combines field observations, interviews with local farmers and analysis of data on the use of mobile extension services. The results show that precision agriculture tools, such as soil moisture sensors, GPS-based field mapping and automatic irrigation systems, have significantly improved resource management and crop yields. In addition, mobile extension services improved farmers’ access to timely information on weather forecasts, pest control and best farming practices, thereby strengthening decision-making processes and reducing production risks. Despite the obvious benefits, the study notes that barriers remain, such as limited digital literacy, high costs of technological inputs and inadequate mobile network coverage, which hinder wider adoption among smallholder farmers. The study concludes that targeted digital literacy training, government support for affordable technology access and improved rural network infrastructure are essential to fully realize the potential of digital innovation in semi-arid agriculture. This study contributes to the growing body of literature highlighting the transformative role of digital technologies in improving agricultural productivity and resilience in water-scarce areas and provides practical insights for policy makers, development practitioners and agricultural technology innovators.

Digital transformation is significantly reshaping the global agribusiness sector, with South Africa actively participating in this technological shift. This paper investigates the influence of digital technologies on enhancing productivity, sustainability, and competitiveness within South African agriculture. The adoption of innovations such as precision agriculture, artificial intelligence (AI), Internet of Things (IoT), and blockchain is increasingly viewed as essential for addressing challenges related to climate change, food insecurity, and economic instability. The study highlights the potential of digital transformation to improve supply chain transparency, expand market access, and strengthen risk management. However, it also acknowledges persistent obstacles to adoption. These include poor digital infrastructure in rural regions, high technology implementation costs, limited technical skills, and gaps in digital literacy, particularly among smallholder farmers. By drawing on literature reviews, policy analysis, and empirical case studies, the paper provides a balanced assessment of both opportunities and limitations associated with digital agriculture in the South African context. Findings reveal that while large commercial farms are increasingly utilizing digital tools, small-scale farmers face systemic barriers that limit their participation in the digital economy. As a result, the paper advocates for inclusive digital strategies and capacity-building programs aimed at closing the digital divide. It emphasizes that the success of digital transformation in South African agri-business depends heavily on coordinated efforts among government, industry players, and local farming communities to ensure broad-based access and equitable outcomes.

The implementation of lockdown measures by the government of Zimbabwe in response to the health emergency triggered by COVID-19 resulted in the adoption of emergency fiscal measures comprising supplementary budgets, budget reprioritisations and use of contingency reserves to support the economy and procure personal protective equipment (PPEs). However, the suspension of budget and procurement oversight by the Parliament of Zimbabwe – which was unable to function due to lockdown directives, and the reliance on performance auditing (post-audits) by Supreme Audit Institutions created a fiscal oversight vacuum. The reliance on performance auditing - audit action taken after the expenditure period has been completed, by the Auditor General of Zimbabwe resulted in unaccountable emergency spending and public procurement which led to widespread corruption. Using systematic review results from a Doctoral study, this study seeks to synthesise best practice lessons from countries that managed to use Real Time Audits (RTAs) to enforce real-time fiscal accountability during COVID-19. The analysis then provides a framework upon which the Auditor General’s office and Parliament can integrate their process through RTAs to institutionalise real time oversight on public expenditure during a national emergency. For RTAs to become part of Zimbabwe’s legislative oversight framework during emergencies, the review results underlined the importance of a review of the parliamentary oversight system, review of public finance and audit legislation, codification of emergency oversight instruments and citizen oversight.

This study aims to explore the current state of the adoption of e-health tools for digital mental health services (DMHS) at a selected South African higher education institution. A quantitative case study was conducted at a single university in Cape Town, South Africa, surveying 348 voluntary participants. Data analysis involved descriptive statistics and exploratory factor analysis through Statistical Package for Social Sciences (SPSS) version 28. The results of this study indicate that awareness of freely accessible DMHS, service providers, and Fourth Industrial Revolution (4IR) technologies are significant factors driving the adoption of e-health tools. However, internet accessibility, internet cost concerns, multiple device use, social media use, searching for services, and preferences for digital over in-person services showed no significant correlation with the current state of adoption factor. The study concludes that awareness of DMHS, service providers, and 4IR technologies are key drivers for the sustainable adoption of e-health tools post-COVID-19. The results inform practical strategies for the sustainable adoption of e-health tools in SA HEIs and may be relevant to similar institutions in global contexts. The findings are potentially applicable to similar contexts globally. Thus, helping to achieve the Sustainable Development Goal 3 of the United Nations of ensuring good health and wellbeing.

This paper presents the practical application of a novel approach, the so-called "Lububu method", to develop a causal machine learning model (CML) for the diagnosis of African swine fever (ASF). The Lububu method was developed to build causal machine learning models by focusing on the contextual understanding of a particular phenomenon and using technological tools to improve accuracy. Its main goal is to identify cause-and-effect relationships that can lead to better outcomes in various fields, including manufacturing, energy production, agriculture, transportation, data management, medicine and computer science. In this study, the Lububu method serves as an experimental framework for the construction of a CML model tailored to ASF diagnosis. This involves gathering comprehensive knowledge about ASF, covering aspects such as the causes, symptoms, transmission patterns and diagnostic procedures. This detailed contextual understanding supports the development of a model that can accurately identify ASF-related factors, ultimately increasing diagnostic effectiveness. By combining AI innovation and epidemiological expertise, this approach redefines ASF diagnostics and paves the way for data-driven, ethical and globally applicable solutions for veterinary medicine.

This review emphasizes the urgent need for effective diagnostic strategies for African swine fever (ASF), a serious disease affecting pig populations worldwide. The aim of the review is to analyze the existing research on ASF diagnostics through a comprehensive literature review, focusing on different diagnostic approaches, including clinical assessments, PCR tests, ELISA, rapid tests and epidemiological models. It examines their sensitivity, specificity and overall performance, addressing challenges such as the varying sensitivity of tests and cross-reactivity. The review highlights both the strengths and limitations of current methods and suggests areas for improvement and standardization. Recommendations are made for future research and the development of innovative diagnostic tools to improve ASF surveillance and control. This study makes a practical contribution by providing a detailed assessment of ASF diagnostic methods from which veterinary scientists and practitioners can benefit. Theoretical contributions include the identification of gaps in ASF diagnostics and the refinement of discussions on diagnostic accuracy and reliability. These findings are consistent with the journal’s focus on infectious diseases and veterinary research and support progress in veterinary medicine and animal welfare.

This paper explored factors for infusing change management practices in the public sector and gave recommendations for policy execution of technology. The Western Cape Department of Community Safety (DoCS) launched the Expanded Partnership Programme (EPP) in 2010, as provided for in section 206 of the Constitution to reorient social crime prevention by Community Policing Forums Educate and Share towards Monitoring Guided Actions to increase sustainability, the efficiency of Community Police Forums (CPFs), and the accountability of the police. Even with an investment of R18 million, participation levels were still low and there was no service delivery improvement by the police, thus the need for a change management was borne. The study pointed out the need of strategic methods such as Kotter’s 8-Step Process, Prosci ADKAR, and McKinsey Influence Model to implement institutionalised changes. The research pursued a practical stance and therefore merged objectivist and constructivist positions with an abductive approach. Count data were collected through the use of a Likert scale questionnaire since it was quantitative in nature while qualitative data was obtained from semi-structured focus group discussions. Data analysis was performed using qualitative and quantitative methods such as descriptive statistics, Pearson’s Chi-square, and content analysis, among others. The research findings highlighted key factors such as organizational culture, interests of stakeholders, politics, resources, and the external environment a determinants of change management. The creation of detailed guidelines that are supported by evidence to direct decision making, resource allocation and prioritisation of policies by the government was advocated for in the study. These findings closed the loop between the research academic domain and the practical field, and demonstrated clear steps towards improving accountability, transparency and adequacy of change implementation.

This study focused on improving the diagnosis of African swine fever (ASF) by improving accuracy, reliability and precision using various machine learning algorithms. Data from the European Union Reference Laboratory for ASF and the EU Animal Disease Information System (ADIS) containing clinical information on wild and domestic pigs were processed and converted into numerical and categorical formats for analysis. Various machine learning models were tested as part of the study, including linear regression, Bayesian regression, support vector machines (SVM), decision trees, random forest classifiers, artificial neural networks (ANNs) and logistic regression. The models were evaluated using metrics such as accuracy, precision, recall, F1-score and root mean square error (RMSE). The results showed that the SVM achieved the lowest performance with 44.4% accuracy, followed by the logistic regression model with 61.5%. The neural network model achieved 69% accuracy, closely followed by the decision tree model with 70%. The linear regression model performed slightly better with 74% accuracy. Bayesian regression achieved a higher accuracy of 80%, while the Random Forest model outperformed all others, achieving the highest accuracy of 88.9%. These results make an important contribution to economic efficiency and innovative applications in veterinary medicine and improve disease management through advanced machine learning techniques.

The paper explored the digital capabilities required by the private utility environment to participate and remain competitive in Society 5.0. The development of a digital infrastructure for power utilities within a smart society, utilizing renewable energy and integrating traditional and renewable sources, presents challenges in identifying the specific skills required for effective operation within Society 5.0. While technologies like virtual power plants, smart grids, and microgrids offer potential for enhanced energy management, there is a significant gap in understanding the workforce capabilities needed to support, maintain, and sustain these advanced systems. Therefore, a thorough assessment of the proposed technological structures and requisite skills is essential to ensure successful implementation and operation in this evolving energy landscape. It investigated the type of skills would the workforce require for a private utility to support a super-smart society. A non-probability sampling strategy was utilised to access the entire interest set. Fifteen semi-structured interviews were performed, with the participants featuring a private utility company’s management, administrative, and technical staff. All interviews conducted were recorded after obtaining consent from the participants. Probing questions were asked until the participants supplied the information needed to address the study questions. The findings and the implications are that management and technical staff responsible for managing and coordinating the activities of utilities (water and electricity) and the technical staff responsible for the implementation and maintenance of energy solutions, in a private utility company were interviewed to establish and ascertain their digital capabilities and preparedness for the fourth and fifth industrial revolutions (Society 5.0).

Governance is still a contested concept in both theory and practice.  A proliferation of the concept has sprung up in literature.  One comes across variations where reference is made to co-production, public governance, good governance, hybridity governance, hybrid governance, to name but a few. The aim of this paper is to provide a conceptual overview of the evolution of the concept governance in general and hybrid governance particulary focused on selected African countries.  It is important to clarify what hybrid governance involves, and its implications for state capacity and service delivery.  Furthermore, it is imperative to discern whether hybrid governance could be a useful conceptual tool for facilitating more organised systems of service delivery in parts of Africa and South Africa, or whether it is just “new developmental jargon”. The paper employed a qualitative research approach where secondary sources of information, constituting document analysis, premised around forms of hybrid governance in selected African countries were explored. The paper makes a conceptual contribution to the collaborative international governance discourse.

Despite anecdotal evidence indicating that a lack of management support towards internal audits (IAs) affects their efficacy, only a few studies have been conducted on the topic in a provincial government (PG) context. Besides, studies on the lack of management support towards IA efficacy lack theoretical grounding. This research aims to address this knowledge gap. The paper applied principal–agent theory to identify barriers to efficient management support towards the IA role within PGs, using the case of the Western Cape Government (WCG). Initially, questionnaires were sent to 260 WCG participants. The results revealed that management has a bad perception of IA as adding value to the organisation and does not take timely corrective actions based on audit findings and recommendations. The study adds to the limited knowledge about management and the IA relationship within PGs.