Homelessness is a global social issue that has affected various nations around the world, including South Africa. The instances of homelessness began during the apartheid era in South Africa and have since risen to alarming levels in provinces such as Gauteng, Western Cape, and KwaZulu-Natal, as reported in the 2022 census. Despite the lack of comprehensive research on homelessness in South Africa, this study conducted a scoping review to evaluate research completed on homelessness from independence to 2020 in the country. The scoping review followed the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and involved a systematic search of the Development Southern Africa and Urban Forum databases. A total of 72 research articles were identified, with 10 meeting the inclusion and exclusion criteria for the review, which were then analyzed using thematic analysis. The study identified several key themes, including homelessness as a reflection of patriarchal systems, gender-based conflicts leading to homelessness, proactive and reactive interventions by non-state actors for homeless individuals, and the quantitative focus of research on homelessness in South Africa from independence to the present day. The study presents the applicability of these findings to tackle homelessness in Papua New Guinea and recommends the use of mixed methods approaches to research homelessness in South Africa to gain a more comprehensive understanding of the various dimensions of homelessness in the country.

In order to diversify a portfolio, find prices, and manage risk, derivatives products are now necessary. There is a lack of understanding of the true influence of derivatives on the behavior of the underlying assets, their volatility consequences, and their pricing as complex instruments. There is a dearth of empirical research on how these instruments impact company risk exposures and inconsistent findings. This study examines corporate derivatives’ impact on stock price exposure and systematic risk in South African non-financial firms. Using a dataset of listed firms from 2013 to 2023, we employ Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to assess the effect of derivatives on return volatility and beta, a measure of systematic risk. Additionally, we apply the Generalized Method of Moments (GMM) to address potential endogeneity between firm characteristics and derivatives use. Our findings suggest that firms using derivatives experience lower overall volatility and reduced systematic risk compared to non-users. The results are robust to various control factors, including firm size, leverage, and macroeconomic conditions. This study fills a gap in the literature by focusing on an underrepresented emerging market and provides insights relevant to global risk management practices.

The failure to achieve sustainable development in South Africa is due to the inability to deliver quality and adequate health services that would lead to the achievement of sustainable human security. As we live in an era of digital technology, Machine Learning (ML) has not yet permeated the healthcare sector in South Africa. Its effects on promoting quality health services for sustainable human security have not attracted much academic attention in South Africa and across the African continent. Hospitals still face numerous challenges that have hindered achieving adequate health services. For this reason, the healthcare sector in South Africa continues to suffer from numerous challenges, including inadequate finances, poor governance, long waiting times, shortages of medical staff, and poor medical record keeping. These challenges have affected health services provision and thus pose threats to the achievement of sustainable security. The paper found that ML technology enables adequate health services that alleviate disease burden and thus lead to sustainable human security. It speeds up medical treatment, enabling medical workers to deliver health services accurately and reducing the financial cost of medical treatments. ML assists in the prevention of pandemic outbreaks and as well as monitoring their potential epidemic outbreaks. It protects and keeps medical records and makes them readily available when patients visit any hospital. The paper used a qualitative research design that used an exploratory approach to collect and analyse data.

This study investigated the influence of infrastructure spending, government debt, and inflation on GDP in South Africa from 1995 to 2023. Motivated by the need for sustainable growth amid fiscal and inflationary pressures, this research addresses gaps in understanding how these factors shape economic performance. The primary objective was to assess these variables’ individual and combined effects on GDP and offer policy recommendations. Using an ARDL model, the study explored long- and short-term relationships among the variables. Results indicate that infrastructure spending positively impacts GDP, promoting long-term growth, while government debt hinders GDP in both short and long runs. Moderate inflation supports growth, but excessive inflation poses risks. These findings imply the need for targeted infrastructure investments, strict debt management practices, and inflation control measures to sustain economic stability and growth. Policy recommendations include expanding public investment in productive infrastructure, implementing fiscal rules to prevent unsustainable debt levels, and maintaining inflation within a controlled range. Ultimately, these policies could help South Africa build a resilient, balanced economy that addresses both immediate growth needs and long-term stability.