In April 2023, the government of Changshu City, in Jiangsu Province, China, announced that it would officially use digital Chinese Yuan (E-CNY) as a method of wage payment to the government and state-owned enterprises staff starting in May. With the gradual improvement and application of E-CNY technologies, such as no electricity, no internet payment (offline payment), and the programmability of smart contracts, E-CNY will be officially used in China. CNN said China is on the verge of a cashless society. The advantages of E-CNY have a positive role in promoting the Chinese government’s implementation of the development goals of a low-carbon and sustainable economy. However, artificial intelligence (AI) trust concerns are the primary bottleneck in the current development based on intelligent algorithms and digital information technology. AI trust concerns are affecting the scope of use of E-CNY, and it may need to achieve effective scale-use, making it promote low-carbon and sustainable development. From the industry perspective, this article selects the housing rental enterprises, which are challenging to develop and energy-intensive, to analyze the theoretical approach and practical impact of E-CNY in promoting the low-carbon and sustainable development of China’s rental housing economy. Meanwhile, from the perspective of Chinese consumers, the impact of AI trust concerns on E-CNY in promoting low-carbon and sustainable development is analyzed in this article.

The existing studies on the association between the built environment and health mainly concentrates on urban areas, while rural communities in China have a huge demand for a healthy built environment, and research in this area remains insufficient. There is a lack of research on the health impact of the built environment in rural communities in China, where there is a significant demand for advancements in the healthy built environment. Exploring the Influence of built environment satisfaction on self-rated health outcomes in New-type village communities has positive significance for advancing research on healthy village community. This paper selects four new-type village communities as typical cases, which are located in the far suburbs of Shanghai, China. A questionnaire survey was conducted on individual villagers, and 223 valid questionnaire samples were obtained. A PLS-SEM model was developed using survey data to examine how built environment satisfaction influences dwellers’ self-rated health while taking into account the mediating function of the perceived social environment. Moreover, multi-group analysis was performed based on age. The results show that built environment satisfaction indirectly influences residents self-rated health through its impact on perceived social environment. The research also discovered that the relationship between built environment satisfaction, social environment satisfaction and self-rated health is not influenced by age as a moderating factor. The research offers new insights for the planning and design of new-type village community from a health perspective.

Lifelong learning (LLL) is progressively recognized as a crucial component of personal and professional development, particularly for adult students. As a heavily populated developing country, China requires profound national education reform to support its economic development and maintain its competitive advantage on the global economic stage. The governmental policy endorses the execution of diverse forms of lifelong learning programs to bolster the national education reform. However, implementing such programs can be challenging for all the stakeholders of the programs, especially for adult students. The weaker foundational knowledge and insufficient online learning abilities of adult students particularly highlight the academic challenges they face. This study explores the academic challenges faced by adult learners in a Chinese vocational college’s LLL program. Focusing on ex-soldiers, unemployed individuals, migrant workers, and new professional farmers (aged 22–44), data were collected from 16 adult students via purposive sampling. Semi-structured interviews and document analysis revealed recurring thematic academic challenges. Additionally, the study found that adult student attributes (highest education level, age) significantly influenced the unique academic challenges they encountered. This research provides practical solutions to improve LLL programs and promote successful lifelong learning experiences for adult students. 

The increase in energy consumption is closely linked to environmental pollution. Healthcare spending has increased significantly in recent years in all countries, especially after the pandemic. The link between healthcare spending, greenhouse gas emissions and gross domestic product has led many researchers to use modelling techniques to assess this relationship. For this purpose, this paper analyzes the relationship between per capita healthcare expenditure, per capita gross domestic product and per capita greenhouse gas emissions in the 27 EU countries for the period 2000 to 2020 using Error Correction Westerlund, and Westerlund and Edgerton Lagrange Multiplier (LM) bootstrap panel cointegration test. The estimation of model coefficients was carried out using the Augmented Mean Group (AMG) method adopted by Eberhardt and Teal, when there is heterogeneity and cross-sectional dependence in cross-sectional units. In addition, Dumitrescu and Hurlin test has been used to detect causality. The findings of the study showed that in the long run, per capita emissions of greenhouse gases have a negative effect on per capita health expenditure, except from the case of Greece, Lithuania, Luxembourg and Latvia. On the other hand, long-term individual co-integration factors of GDP per capita have a positively strong impact on health expenditure per capita in all EU countries. Finally, Dumitrescu and Urlin’s causality results reveal a significant one-way causality relationship from GDP per capita and CO₂ emissions per capita to healthcare expenditure per capita for all EU countries.

In order to explore how hygiene factors and motivational factors indirectly affect job satisfaction through teacher self-efficacy. Based on the two factor theory and Teacher Job Satisfaction Survey (TJS), this study analyzes how hygiene factors and motivational factors indirectly affect job satisfaction through teacher self-efficacy. The study collects valid questionnaires from 120 teachers and conducts mediation analysis using structural equation modeling. From the results, teacher self-efficacy had obvious mediating effects between hygiene factors and job satisfaction (β > 0.6, P < 0.001), as well as between motivational factors and job satisfaction (β > 0.6, P < 0.001). This discovery not only provides new perspectives and strategies for improving teacher job satisfaction, but also emphasizes the importance of enhancing teacher self-efficacy in improving job satisfaction. In addition, the study provides strong empirical evidence for education management departments and school leaders to formulate more effective teacher development policies and management measures, which has positive theoretical and practical significance for improving education quality and promoting education reform.