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Recognising the significant role of artificial intelligence in the labour market is essential for China to develop sustainably. The research utilises the mixed frequency vector auto-regression (MF-VAR) technique, which would innovatively incorporate data at different frequencies into one model to identify the intricate correlation between the monthly artificial intelligence index (AII) and the quarterly unemployment rate (UR) in China. Through comparison, the MF-VAR method has a more substantial explanatory power than the low-frequency VAR (LF-VAR) model, the impulse responses of the former reveal that AII exerts favourable and adverse influences on UR. Among them, the positive effect occurs on the AII in the first and second months. In contrast, the negative one appears on the AII in the third month, highlighting that artificial intelligence has both stimulating and inhibiting effects on the labour market in China. By analysing UR’s predictive error variance decomposition, the total impact of China’s artificial intelligence technology on employment is a substitution; this outcome is accordant with the theoretical dis¬cussion. In the new round of scientific and technological revolution and industrial transformation, meaningful recommendations for China would be put forward to avert the wave of unemployment brought by the development of artificial intelligence technology. First published online 09 September 2024

The internet has influenced human wellbeing through social networking, time-saving, diffusion of knowledge, and access to health information. Health is a key component of human quality of life. This study examines the nexus between education, the internet, and quality of life using data from China spanning the period from 1991 to 2020. The study used ARDL to examine the short and long-term, exploring education and the impact of the internet on quality of life. Education status plays a significant role in promoting quality of life in the short and long term. The empirical findings show the significant positive impact of the internet and ICT on quality of life in the short and long-run. Financial development and FDI improve the quality of life in the long-term in China. Based on these results, policymakers in China should develop the ICT infrastructure and human capital to support increased quality of life.

In this study, our primary focus is to capture the impact of green logistics and social marketing on health outcomes in One Belt Road Initiative (OBRI) countries over the time period 2007–2019. Two estimation techniques, i.e., 2SLS and GMM, are employed to get the estimates of our variables. Findings of the 2SLS model confirmed the negative impact of green logistics on infant mortality in OBRI, European, MENA, and Asian countries. On the other side, the relationship between green logistics and life expectancy is positive in all the regions in 2SLS models. The other estimation technique also supports these findings, GMM, which confirmed the negative impact of green logistics on infant mortality and the positive impact of green logistics on life expectancy OBRI, European, MENA, and Asian economies. From these findings, we can conclude that green logistics helps to improve the health status of OBRI economies. Similarly, social marketing also improves the health status in OBRI and other regions in both models. Therefore, the governments and policymakers in respective economies should focus on the development of green infrastructure and logistics that, on one side, promote economic growth. However, on the other side, it helps improve environmental quality, which ultimately improves the OBRI economies' health status.