Reducing the use of chemical fertilizers in agricultural production is an inevitable requirement for achieving carbon neutrality and coping with global warming, and it is also an important measure for achieving green and sustainable agricultural development. Furthermore, the development of socialized services of green production provides a new approach to effectively reducing the use of fertilizers. Based on the survey data of 2202 rice growers in Jiangsu Province in 2021, this paper empirically analyzed the effects of socialized services of green production and social network on the reduction in fertilizer application by farmers. The results showed that both the socialized services of green production and social networks could significantly promote the reduction in fertilizer application by farmers. Social networks have a moderating effect between socialized services of green production and reduction in fertilizer application and can enhance the promotion of farmers’ adoption of socialized services of green production to reduce the application of fertilizers. With consideration of the potential endogenous problems of the model and the robustness test by replacing the key explanatory variables and the explained variables, all of the results were stable. Therefore, it is emphasized that the government should cultivate the main body of agricultural socialized services, improve the socialized service system of green production, and promote the green development of agriculture by service scale operation. Equally, it is necessary to strengthen the construction of rural social networks for the exchange of fertilization experience and give full play to the positive role of social networks in the reduction in fertilizer application by farmers.

In China, characterized by its vast population and limited land, expanding the scale of agricultural operations through the transfer of land management rights is a crucial pathway to achieving agricultural modernization. Using data from the China Land Economic Survey (CLES), we empirically explored the influence of digital technology use on land transfer-in by farmers. Employing the Probit model and the KHB method, this study examined the mechanisms underlying this relationship and addressed the issue of endogeneity through the Conditional Mixed Process (CMP) model, grounded in the instrumental variable method. Key findings include: (1) both the accessibility and the depth of digital technology use significantly facilitated land transfer-in by farmers. For every one-unit increase in digital technology accessibility, the likelihood of land transfer-in escalated by 6.2%; similarly, a one-unit rise in the depth of digital technology use increased this probability by 2.6%. (2) An analysis of the mechanisms indicates that social networks and credit availability played partial mediating roles in the impact of digital technology accessibility and depth on land transfer-in, with social networks exhibiting a stronger mediation effect. (3) Heterogeneity analysis suggests that the impact of digital technology use on land transfer-in was more pronounced in peri-urban villages and among farmers with higher literacy levels. In light of these findings, we proposed policy recommendations to accelerate the development of rural digital infrastructure, enhance digital skill training for farm households, and vigorously promote rural digital inclusive finance.

Counties are the basic unit for addressing unbalanced development in a region, revitalizing rural areas, and promoting the integrated development of urban and rural areas. Despite the importance of county-level research, few studies have been conducted research at such a small scale. To address this gap in knowledge, this study constructs an evaluation system to measure the county sustainable development capacity (CSDC) of counties in China, identify constraints to development, and provide policy suggestions to promote the counties’ long-term stable development. Specifically, the CSDC indicator system was based on the regional theory of sustainable development and included economic aggregation capacity, social development capacity, and environmental carrying capacity. This framework was applied to 103 key counties to receive assistance in pursuing rural revitalization in 10 provinces in western China. The AHP–Entropy Weighting Method and TOPSIS model were employed to inform the scores of CSDC and its secondary indicators, and ArcGIS 10.8 was used to portray the spatial distribution of CSDC and to classify these key counties into categories that guided specific policy recommendations. The results demonstrate a high degree of unbalanced and inadequate development in these counties and that rural revitalization efforts can be targeted to increase the speed of development. It is crucial to follow the recommendations that conclude this paper to promote sustainable development in areas that have been lifted out of poverty and to revive rural areas.

Household waste classification and treatment are important for environmental protection and sustainable development. The Logit model is used to analyze differences in farmers’ willingness and behavior regarding waste classification based on data from the China Land Economic Survey. Key findings include the following: (1) There is an evident discrepancy between waste classification willingness and action among rural residents. Despite nearly 90% of the sampled farmers expressing a willingness, nearly 40% do not practice waste classification. (2) Internet usage significantly reduces the discrepancy between farmers’ willingness and actual waste classification practices. This observation is valid even after robustness checks and endogeneity discussions. (3) There is a partial mediating effect between ecological awareness and knowledge perception on farmers’ willingness and behavior differences, which accounts for 12.9% and 52.6%, respectively, of the total impact. Notably, institutional limitations amplify the negative influence of Internet use on this discrepancy. (4) According to heterogeneity analysis, Internet use has a greater negative impact on farmers’ willingness and behavior in waste classification in suburban villages and villages with environmental governance projects. This study proposes policy suggestions such as strengthening the construction of digital infrastructure in rural areas, enhancing the promotion and training of waste classification among farmers, and improving incentives and restraint mechanisms for rural household waste classification.