With the implementation of the rural revitalization strategy, rural wisdom pension gradually becomes an important direction for the development of rural society. The purpose of this paper is to study the optimization path of rural smart pension in the context of rural revitalization. By analyzing the definition, development status and dilemma of rural wisdom pension, key factors for optimizing rural wisdom pension are proposed, and the paths for enhancing rural wisdom pension are discussed. The research results show that strengthening infrastructure construction, improving service quality, and promoting information technology application are the key paths to realize rural smart aging. This study provides theoretical guidance and policy recommendations for the implementation of rural smart aging.

Under the developing trend of artificial intelligence (AI) technology gradually penetrating all aspects of society, the traditional language education industry is also greatly affected ^[1]. AI technology has had a positive impact on college English teaching, but it also presents challenges and negative impacts. On the positive side, AI technology can provide personalized learning experiences, real-time feedback, and autonomous learning opportunities, and so on. However, it may also lead to a lack of communication between students and humans, resulting in a decline in students’ interpersonal skills, and cause students’ dependence on online learning resources as well as possible risks to student data privacy and security, and other negative impacts. To address these challenges, teachers can adopt the following countermeasures: improving teachers’ skills in the use of AI technology incorporated in the classroom, offering personalized instruction to reduce students’ dependence on AI technologies, emphasizing the cultivation of students’ humanistic literacy and interpersonal communication ability. Additionally, colleges and technology providers should strengthen data security and privacy protection to ensure the safety and confidentiality of student data. By implementing comprehensive measures, we can maximize the advantages of AI technology in college English teaching while overcoming potential issues and challenges.

With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.

This paper explores the interconnected dynamics between governance, public debt, and domestic investment (also known as gross fixed capital formation (GFCF) in South Africa). It also highlights domestic investment as a key driver of economic growth, noting a consistent decline in investment since the country’s democratic transition in 1994. Moreover, this downward trend is exacerbated by excessive public debt, poor governance, and increased economic risks, discouraging domestic and foreign investments. The analysis incorporates two theoretical perspectives: endogenous growth theory, which stresses the significance of local capital investment and innovation, and institutional governance theory, which focuses on the role of governance in promoting economic development. The study reveals that poor governance, rising debt, and high economic risks have impeded GFCF and economic stability. By utilizing quantitative data from 1995 to 2023, the research concludes that reducing public debt, improving governance, and minimizing economic risk are critical to revitalizing domestic investment in South Africa. These findings suggest that policy reforms centered on good governance, effective debt management, and economic stabilization can stimulate investment, promote growth, and address the country’s economic challenges. This study offers insights into how governance and fiscal policies shape investment and capital formation in a developing nation, providing valuable guidance for policymakers and stakeholders working towards sustainable economic growth in South Africa.

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.

With the popularity of smartphones, consumers’ daily lives and consumption patterns have been changed by using multi-functional apps. Convenience store operators have developed membership apps as a platform to promote their brands to consumers to create the benefits of “membership economy”. This study examined consumer behavior towards convenience store membership apps using UTAUT2. Consumers who have installed the convenience store membership apps were recruited as the target population. SPSS 23.0 was used to conduct item analysis and reliability analysis in the pretest questionnaires. The formal questionnaires were distributed online by convenience sampling method, with 375 valid questionnaires collected. Smart PLS 3.0 was conducted by analyzing the confirmatory factor analysis and structural equation model analysis. The results of the study, “performance expectancy”, “social influence”, “price value” and “habit” of convenience store member app users showed positive and significant effects on “behavioral intention”. “Facilitating conditions”, “habit” and “behavioral intention” have positive and significant effects on “actual use behavior”. “Gender” affects “habit” to have a significant moderating effect on “use behavior”. “Use experience” affects “habit” to have a significant moderating effect on “behavioral intention”. Based on the study results, the further suggestions of marketing management implications and feasible recommendations are proposed for convenience store operators to refer to in the implementation of membership app marketing management.