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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.

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.

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.

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.

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.