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 aims to analyze how public debt influences economic growth in Kosovo, using quarterly data from Q1 2008 to Q4 2022 and employing the generalized method of moments (GMM). The research reveals that there is a negative relationship between public debt and economic growth when other factors such as trade openness, total investment, current account balance, and primary balance are considered. Furthermore, the findings confirm an inverted “U-shaped” relationship between public debt and economic growth, indicating that the optimal debt level is between 27.75% and 36.2% of GDP.

Purpose: The major objective of this study is to measure the impact of various attributes, such as social attraction, physical attraction, and task attraction on para-social relationships. The study also seeks to measure how the para-social relationship mediates the association between the three attributes (above-mentioned) on perceived credibility and informational influence, and consumers’ intention to purchase banking products. Study design/methodology: PLS-SEM has been used as it is believed to be most suited for the study due to the multivariate non-normality in the data, and the small sample size. Data has been collected using the 5-point Likert scale from approximately 151 respondents, who were selected using the non-random sampling method based on purposive sampling coupled with convenience-based sampling. The data was collected from January 2023 to August 2023. Findings: Largely, the findings reveal that both social and physical attractions do have a positive impact on the para-social relationship, further leading to perceived credibility and informational influence. Notably, this perceived credibility and informational influence lead to consumers’ intentions to purchase banking products, albeit with the use of artificial intelligence-based chatbots and digital assistants. Originality: This is possibly among the first-ever studies extending the para-social theory for purchasing banking products and services using artificial intelligence-based chatbots and virtual assistants.

This study investigates seismic risk and potential impacts of future earthquakes in the Sunda Strait region, known for its susceptibility to significant seismic events due to the subduction of the Indo-Australian Plate beneath the Eurasian Plate. The aim is to assess the likelihood of major earthquakes, estimate their impact, and propose strategies to mitigate associated risks. The research uses historical seismic data and probabilistic models to forecast earthquakes with magnitudes ranging from 6.0 to 8.2 Mw. The Gutenberg-Richter model helps project potential earthquake occurrences and their impacts. The findings suggest that the probability of a major earthquake could occur as early as 2026–2027, with a more significant event estimated to likely occur around 2031. Economic estimates for a 7.8–8.2 Mw earthquake suggest potential damage of up to USD 1.255 billion with significant loss of life. The study identifies key vulnerabilities, such as inadequate building foundations and ineffective disaster management infrastructure, which could worsen the impact of future seismic events. In conclusion, the research highlights the urgent need for comprehensive seismic risk mitigation strategies. Recommendations include reinforcing infrastructure to comply with seismic standards, implementing advanced early warning systems, and enhancing public education on earthquake preparedness. Additionally, government policies must address these issues by increasing funding for disaster management, enforcing building regulations, and incorporating traditional knowledge into construction practices. These measures are essential to reducing future earthquake impacts and improving community resilience.

Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation.  Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

This paper examines the relationship between renewable energy (RE) generation, economic factors, infrastructure, and governance quality in ASEAN countries. Based on the Fixed Effects regression model on panel data spanning the years 2002–2021, results demonstrate that domestic capital investment, foreign direct investment, governance effectiveness, and crude oil price exhibit an inverse yet significant relationship with RE generation. An increase in those factors will lead to a decline in RE generation. Meanwhile, economic growth and infrastructure have a positive relationship, which implies that these factors act as stimulants for RE generation in the region. Hence, it is advisable to prioritise policies that foster economic growth, including offering tax breaks specifically for RE projects. Additionally, it’s crucial to streamline governance processes to facilitate infrastructure conducive to RE generation, along with investing in RE infrastructure. This could be achieved by establishing one-stop centres for consolidating permitting processes, which would streamline the often-bureaucratic process. However, given the extensive time period covered, future research should examine the short-term relationship between the variables to address any potential temporal trends between the factors and RE generation.