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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.

In the context of rapid technological advancement and evolving financial ecosystems, this study investigates the interplay between financial literacy, digital finance, and financial behaviour among high school teachers in KwaZulu-Natal (KZN), South Africa. Structural equation modelling (SEM) approach was used to describe intricate relationships between latent constructs, namely, financial literacy, financial Behaviour and, digital finance Knowledge as well as observed variables (B7 to B22, C23 to C44, D45 to D56, demographics). Demographic variables include Gender, Age Category, Qualification Type, Teaching Duration, Financial Literacy Course and Field Employed. The model defined each construct as a linear combination of its observed variables as well as demographic variables under its measurement component, and hypothetical relationships among three latent variables under its structural component. We used Python software and machine learning code to create and estimate the model using observed data. The missing values in each observed variable were imputed with averages of the variables’ data. The tests of normality assumption for SEM were performed using histogram and q-q plots, Shapiro-Wilk test D'Agostino and Pearson's test.  Most data vectors violated the normality assumption. Diagonally Weighted Least Squares (DWLS) was used for parameter estimation as a suitable method that can provide better estimation for more complex models with many parameters. This method has an additional advantage of being less sensitive to outliers. The DWLS parameter estimation results, based on p-values, suggest that financial literacy and financial behaviour have a negative association which means that lacking financial behaviour results in financial literacy. A positive association between has been identified between financial behaviour and digital finance knowledge. Financial literacy and digital finance knowledge have a weak or no relationship. Thus, having or not having digital finance knowledge does not necessarily determine the possibility of experiencing financial literacy. Furthermore, among demographic variables, the financial literacy Course is the only demographic variable that has a significant impact, and only on Financial Behaviour and Financial literacy. The rest of the variables do not significantly influence the latent constructs. This study uniquely applies SEM using the DWLS estimator to explore personal finance dynamics in an emerging economy, offering concise insights into key relationships.

Geophagic practise amongst women of reproductive age remains a major public health concern that is associated with perinatal and postpartum mortalities and morbidities that requires critical interventions to mitigate the practise. Despite the available interventions such as administration of oral iron and folic acid supplementation and intravenous iron therapy, geophagic women of reproductive age do not adhere to the prescribed treatment. Geophagic practise is mostly common and prevalent amongst women of reproductive age worldwide, irrespective of their socio-economic status, ethnicity, age, and social status. An exploratory qualitative research method was used to conduct the study to explore the perceived barriers to accessing treatment for geophagy among women of reproductive age in Tshwane District, Gauteng Province, using the Health Belief Model as a theoretical framework. The study was conducted in the antenatal care and family planning units in the public healthcare facilities of Tshwane District, Gauteng Province. The findings indicate that absence of geophagy health education and screening of iron deficiency in the antenatal care units, as part of the antenatal care. addiction, dependency syndrome, influence from peers, fear of judgement and shame to disclose to healthcare providers about their geophagic practise status, lack of awareness regarding the benefits of taking oral and intravenous iron therapies were stressed as the main barriers influencing the uptake of treatment for geophagy amongst women of reproductive age. The implementation of iron and folic acid supplementation and intravenous iron therapy for geophagic women of reproductive age is not adequately yielding positive results if this initiative is not coupled with geophagy health education particularly in the antenatal care units to enhance treatment uptake and adherence.

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.

The study aimed to investigate factors influencing the intention to adopt e-health tools for accessing digital mental health services among university staff at a selected South African higher education institution. A quantitative case study was conducted at a single university in Cape Town, South Africa. Data was collected from 348 respondents using online questionnaires and analysed using descriptive statistics and multiple regression. The results revealed that stable internet access at home did not significantly influence the intention to adopt e-health tools (p =0.698, ? = -0.020), but concerns about internet costs were a barrier (p = 0.011, ? = 0.131). University staff who used multiple devices (p = 0.014, ? = 0.136) and preferred e-health tools over traditional face-to-face services were more likely to adopt them (p < 0.001, ? = 0.319). Moreover, social media usage (p < 0.766, ? = 0.016), searching for digital mental health services (p <0.107, ? = 0.085), and awareness of free university services (p < 0.307, ? = -0.058), DMHS providers (p < 0.529, ? = 0.038), and fourth industrial revolution technologies (p < 0.106, ? = -0.091) did not significantly influence adoption intentions. The study contributes to sustainable digital mental health support for university staff in South Africa. The results could potentially be applicable to similar contexts globally. Thus, helping to achieve the Sustainable Development Goal 3 of the United Nations of ensuring good health and wellbeing.