The global interest in environmental protection and sustainable development has grown steadily in recent years, sparking widespread concern about green development in the manufacturing industry among governments, enterprises, and scholars around the world. Despite this heightened interest, research on the influence of the digital economy on the manufacturing industry’s green development remains scarce. This article analyzes the impact of the digital economy on the green development of the manufacturing industry and examines the role of human capital and trade competitiveness in this context. Using a two-way fixed-effects model of panel data analysis, we investigated the GTFP (Green Total Factor Productivity) of the Chinese manufacturing industry, as well as that of the overall industry and 20 other Asian countries along the “Belt and Road”. Our findings indicate a positive association between the digital economy and both the overall GTFP and the manufacturing GTFP in China. The countries situated along the Belt and Road experience a U-shaped trend in their GTFP due to the impact of the digital economy. The digital economy displays a delayed impact, and its eco-friendly value is realized, to different extents, after two sequential periods. In addition, human capital and trade competitiveness are threshold variables in the relationship between the digital economy and the green development of the manufacturing industry. When human capital exceeds a certain threshold and trade competitiveness exceeds a certain threshold, the digital economy has a positive effect on GTFP. This study offers unique insights into the impact of the digital economy on the green development of the manufacturing industry. By addressing this research gap, this study gives policymakers the ability to leverage these findings to promote sustainable practices across the industry. Ultimately, the valuable insights provided by this study may contribute to the ongoing efforts to advance the green development of the manufacturing industry.

The concept of spatiotemporal correlation, initially rooted in the domain of physics, has increasingly become of interest to scholars across various fields. This burgeoning interest is especially noted within the realm of human dynamics, where the examination of human behavior’s spatiotemporal aspects is emerging. The exploration into the nuanced ways in which human actions intertwine with geographical contexts is paramount. This paper delves into the Time-Space Characteristic Correlation of Human Behavior (TSCH) model, a pioneering framework that melds the intricacies of human behavior with geographic considerations through a micro-dynamic approach to population strategy, employing the mean-field limit method. This study scrutinizes the spatiotemporal dynamics of individual travel behaviors, focusing on specific traits such as sudden increases in activity (paroxysm B), behavioral memory (M), and the radius of gyration (Rg). The stability of these behavioral waves is evaluated through the application of the “db4” wavelet basis function, revealing stable fluctuations in population travel patterns that resonate deeply with regional characteristics. The model enables the computation of the overall cost burden of area visits for local residents, uncovering a power-law correlation between this cost and the spatial attractiveness of urban centers when analyzed at a collective level. Our findings underscore a profound linkage between the temporal and spatial patterns of human behavior at the urban scale. Furthermore, the TSCH model’s advancement facilitates a nuanced understanding of complex social issues, including urban development, public health management, and transportation systems optimization, offering valuable insights for sociological inquiry and practical application in addressing contemporary societal challenges.

Although the widespread use of the Internet in rural areas provides new opportunities for economic growth, whether and how rural women benefit from it remains a question. Guided by Sustainable Development Goal (SDG) 5 and its targets, this study examines the impact of Internet use on rural women’s income by using survey data from 1384 rural households in underdeveloped areas of China. The results indicate that Internet use can significantly increase rural women’s income in underdeveloped areas. Additionally, the income effects of Internet use are heterogeneous across the different purposes of Internet use, income levels, individual characteristics, and family characteristics. Further analysis reveals that increasing labor input and enhancing capital endowment are two important channels through which Internet use increases rural women’s income. The results offer further empirical support for policymakers to utilize the Internet to increase rural women’s income and contribute to poverty alleviation in underdeveloped areas.