In the context of the digital age, the digital economy, as a new economic model that the Chinese government is currently committed to developing, has played a positive role in driving consumption and creating employment opportunities. However, the differential development characteristics of the digital economy are becoming increasingly evident. The level of digital infrastructure and the application of digital facilities in China’s eastern regions are superior to those in the central and western regions. The increasing level of differential development in the digital economy will further accelerate the cross-regional mobility of labor. For the more developed eastern regions in China, in terms of the digital economy, the ability to empower employment is relatively high, which can create more job opportunities and attract a larger labor force seeking employment opportunities. In contrast, the central and western regions face slower development in the digital economy and relatively insufficient employment-empowering capacity, leading to labor force outflow. Proper cross-regional labor mobility can enhance the efficiency of labor resource allocation. However, excessive labor force mobility can lead to imbalanced labor resource allocation, causing job shortages and reduced employment quality in regions with an excess of labor force, while labor loss regions face labor shortages and talent drain, resulting in a loss of economic vitality in those regions. Therefore, clarifying and addressing the various negative impacts brought about by the differential development of the digital economy are crucial for improving the overall employment quality in the digital economy era. However, there is currently limited research focused on the influence of differential development levels of the digital economy on employment quality. This study delves into the impact of the differential development levels of the digital economy on employment quality and analyzes the underlying mechanisms. Based on panel data from 31 provinces and cities in mainland China from 2011 to 2020, this study uses the entropy method to calculate both the employment quality index and the digital economy index. Building upon the digital economy index, the Gini coefficient of the digital economy development level in various regions in China is calculated using the Gini coefficient formula. Subsequently, a two-way fixed-effects model empirically analyzes the impact of China’s differential development levels in the digital economy on employment quality. The research finds that the improvement in China’s differential development level in the digital economy significantly reduces employment quality. After re-calculating the Gini coefficient and the employment quality index using principal component analysis, it is found that the Gini coefficient of the digital economy still has a significantly negative impact on the employment quality index. After conducting 2SLS regression using instrumental variables, it is confirmed that there is still a significant negative correlation between the Gini coefficient of the digital economy and the employment quality index. According to the regression results, for every 1% increase in the Gini coefficient of the digital economy, the employment quality index will decrease by 0.111% to 0.361%. Through a regression analysis of the mechanism of action, it is found that the industrial structure plays an intermediary role in the impact of the differential development levels of the digital economy on employment quality. The improvement in the differential development levels of the digital economy is unfavorable for the transformation and upgrading of the industrial structure in the central and western regions, as well as the rational development of China’s overall industrial structure, thereby affecting the improvement of employment quality. Based on the above empirical results, the following policy recommendations are proposed: 1. The Chinese government should increase fiscal support for digital infrastructure construction in the central and western regions, continuously narrowing the gap in digital economy development levels between regions. 2. Regional governments in China should actively guide the healthy upgrading of industrial structures based on the actual conditions of each region. 3. In the digital economy era, the government should introduce relevant labor protection and social security policies based on the characteristics of emerging professions to further improve the employment quality of workers in the digital economy era.

The prosperous development of the digital economy can trigger a comprehensive green transformation from factors of production to productivity and production relationships, providing a new path for China to achieve its goals of “peak carbon emissions” and “carbon neutrality.” This paper measures the development level of the digital economy in each region using panel data of 30 Chinese provinces (autonomous regions, municipality directly under the central government) from 2007–2019, and explores the effect of the digital economy on CO₂ emissions, its transmission mechanism, and its impact characteristics through theoretical and empirical analyses. The results indicate that: (1) the development of the digital economy can effectively reduce CO₂ emissions; (2) in addition to direct effects, the digital economy can indirectly suppress CO₂ emissions by lowering energy intensity, promoting economic agglomeration, and increasing the use of robots; (3) the suppression effect of the digital economy on CO₂ emissions has significant regional heterogeneity; the digital construction in east, north, central, northeast, and southwest China has shown a better CO₂ emissions reduction effect, while the development of the digital economy in south and southwest China has not yet exerted the suppression effect on CO₂ emissions. In the next development process, it should improve the efficiency of energy use, give full effect to the positive externalities of economic agglomeration, lower the threshold of robot use and expand the application scenarios, and make full use of the green development advantages of the digital economy.

To clarify the role of agricultural technological progress in the process of rural revitalization, this paper uses the agricultural panel data of 31 provinces in China from 2007 to 2020 to measure the Total Factor Productivity of agriculture, analyzes the impact direction and spatial spillover effect of agricultural technological progress on China’s rural revitalization through the spatial Durbin model, and analyzes the threshold mechanism of agricultural technological progress on China’s rural revitalization by using the panel threshold model. The results are as follows: (1) The spatial and geographical agglomeration of interprovincial rural revitalization in China has gradually weakened, and the regional imbalance has improved; (2) The progress in agricultural technology plays a positive role in promoting China’s interprovincial rural revitalization, and the overall nonlinear characteristics of "first inhibiting and then promoting" are presented, and the conclusion is still robust after fully considering the factors of time, region and economic distance; (3) Further analysis shows that the impact of agricultural technological progress on China’s interprovincial rural revitalization is based on the threshold constraints of land-scale operation and agricultural-industry agglomeration, and shows significant spatial heterogeneity. The inherent reason is that whether the land-scale operation entity adopts long-term investment decisions such as new agricultural technology depends on the expectation of land management risk stability, while agricultural-industry agglomeration hinders the diffusion and spillover of agricultural technology due to the exclusive characteristics of agricultural production geographical locations. Therefore, in the future of China’s rural revitalization, the government should guide the large-scale operation of land and agricultural production according to local conditions to give full play to the positive spillover effect and spatial radiation capacity of agricultural technology.

The educational burden from extracurricular tutoring class has become a pressing social issue in China. This study used data from the China family panel studies (CFPS) in 2014, 2016, and 2018 to empirically analyze the impact of Internet usage on children’s participation in extracurricular tutoring class. There are many factors that influence parents’ decisions to enroll their children in extracurricular tutoring class. These factors include family income status, the level of importance parents place on their children’s education, the marginal returns on educational investment, academic pressure, etc. However, in today’s digitalized society, the widespread use of the internet will also become an important influencing factor in parents’ decisions regarding educational investment. The study finds that, parents by using the Internet significantly increase the probability of enrolling their children in extracurricular tutoring class. Through mechanism regression analysis, it is concluded that internet usage has a positive influence on parents enrolling their children in extracurricular tutoring class by increasing the frequency of social interaction and raising parents’ educational expectations for their children. Based on the empirical results, the following policy suggestions were proposed: 1. Schools should establish a more comprehensive after-school education service system to improve the engagement of students in compulsory education; 2. The government can enhance the accessibility and optimization of educational resources by increasing investment in education, improving the quality of in-school education, and optimizing the management and supervision of extracurricular tutoring class. This ensures that students can access high-quality educational services.