Agricultural productive services are an important means to achieve effective allocation of regional resources and play an important role in ensuring food security and improving farmers’ welfare. However, the development process of agricultural productive services still faces problems such as large differences in service levels in different segments and low participation rates in the full service. In order to investigate the influential paths of the low participation rate of farmers in the full-service process, this study takes maize farmers in northeast China as the research object. Based on 937 survey data from six cities in three northeastern provinces, we used the Item Response Theory (IRT) model to measure farmers’ information acquisition ability and constructed the Heckman two-stage model and the IV-Heckman model to analyze the logical framework of “information acquisition ability—farmers’ choice of productive agricultural services”. The main findings are as follows: firstly, the more channels there are, the stronger the farmers’ channel internalities; the higher the degree of channel differentiation, the stronger the farmers’ channel internalities. Second, after addressing the sample selection bias and endogeneity, there is a small rise in the facilitation effect of information acquisition ability on farmers’ productive agricultural service behavior. Third, this facilitation effect is achieved through farmers’ perceived usefulness of productive agricultural services, and the mediating effect of perceived ease of use is not significant. Therefore, fostering farmers’ self-perceptions and optimizing information delivery strategies are effective ways to promote farmers’ choice of agricultural productive services and to facilitate the modernization of Chinese agriculture. In general, this study helps to reveal the theoretical mechanism of farmers’ information asymmetry, and provides empirical evidence for how to promote the development of agricultural productive services.

Reducing chemical usage, particularly chemical fertilizers, is a crucial measure for advancing sustainable agricultural development. This study utilized field survey data from 894 maize farmers across three northeastern provinces of China. A double machine learning modeling framework was established to empirically examine the impact and mechanism of agricultural socialized services on chemical fertilizer use of farm households. The model addresses numerous stringent constraints of conventional causal inference models and effectively mitigates the “curse of dimensionality” issue. Current research indicates that agricultural socialized services can substantially decrease chemical fertilizer use among farmers. Further investigation reveals that these services facilitate this reduction by enhancing the mechanization level, promoting the use of organic fertilizers, and providing a labor substitution effect. The region heterogeneity test indicates that the impact of agricultural socialized services is more pronounced in Liaoning and Heilongjiang provinces geographically. Regarding the heterogeneity analysis of food crop income levels, agricultural socialized services can decrease chemical fertilizer use among farmers more effectively with elevated food crop income levels. Consequently, the findings imply that the socialization of agricultural services has substantial potential to be an effective chemical fertilizer reduction strategy to support the agricultural green transition, which can be enhanced through promoting the degree of mechanization, organic fertilizer application, and labor division and specialization.

Along with the increasing prominence of environmental risks such as soil surface source pollution and declining quality grade of arable land, the issues of how to address irrational fertilizer application and enhance the safety of agricultural products have attracted widespread attention. In this context, clarifying the main factors affecting farmers’ use of soil testing and formulated fertilization technology (STFFT) can further improve the technology adoption rate and fertilizer utilization efficiency, promote standardized agricultural production and maintain the health and stability of soil ecology in black soil areas. This is of great significance to the construction of green agriculture, national dietary health and national food security. This study builds an “external environmental stimuli-perceived characteristics-adoption behavior” theoretical framework to investigate the decision-making and the dynamic influence mechanisms of farmers’ adoption behavior of STFFT. Based on farmer survey data, the logistic-ISM model has been applied. The main findings are as follows. First, five types of influencing factors, namely individual characteristics, family characteristics, business characteristics, cognitive characteristics and external environmental characteristics, had significant “push” effects on farmers’ STFFT adoption behavior. Among them, planting scale and technical training are the key factors influencing farmers’ adoption of scientific fertilizer application technology. Second, both farmers’ perceived ease of use and perceived usefulness play a significant role in farmers’ decision-making process, and the easier farmers perceive STFFT to be to master and the greater the benefits it brings, the more pronounced the tendency to adopt the technology, all other influencing conditions being equal. Third, the main influencing factors of farmers’ STFFT adoption behavior are intrinsically related and divided into four categories based on the magnitude of influence: deep-rooted, medium indirect, shallow indirect and superficial direct. In order to reduce further degradation of black soil caused by farmers’ irrational production habits and to improve resource utilization efficiency, this study recommends the government to further regulate the land transfer market, strengthen the propagation of soil-conservation-type technologies in black soil areas, expand the breadth of agricultural technology training and enhance farmers’ understanding and trust in STFFT. Thus, the maintenance of soil ecosystem in black soil areas, effective guarantee of food security and sustainable development of agriculture can be achieved.

Many scholars have conducted in-depth studies on the research area of black soil conservation (BSC) and produced fruitful research results, but there is still a lack of scientific quantitative analysis and objective comprehensive evaluation of the research results. In order to grasp and clarify the current status of BSC research, we explored the trending topics and frontier issues in this research field, as well as the overall evolution trend from 1983 to 2022. Based on the publication information of BSC topics in the core database of Web of Science (WOS), this study utilized the superior tools in two major bibliometric software; they are the VOSviewer and CiteSpace to draw visual maps, such as collaboration networks and keyword co-occurrence maps, to further analyze the research progress and frontiers. The results are as follows: First, research on BSC began in 1983 and can be divided into three phases: the period of nascent research, steady development, and rapid growth. The subject increasingly became an area of research focus in academia, but gradually produced signs of intersection with other disciplines, such as agronomy, biology, and economics. Second, the distribution of research institutions and countries has become more concentrated, forming geographically small research clusters in typical black soil area countries, such as Russia and China, where the centrality of research institutions is higher than 0.20. Research networks have also been initially established between developed and developing countries, such as the United States and China, with a high centrality close to 0.50. Third, the research content is increasingly cross-cutting and systematic, and the research focus can be divided into five major areas, such as black soil distribution and physical and chemical characteristics. Fourth, the research areas cover agronomy, chemistry, geography and other levels, and a more systematic research system has been formed. In the future, it is still necessary to strengthen the establishment of data monitoring systems in black soil areas, the improvement of black soil information database, the assertion of conservation tillage technology and the strengthening of extreme climate early warning network to maintain the soil nutrient content and to guarantee the sustainable development of agriculture.

Purpose: This study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.Design/methodology/approach: This study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.Findings: ADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.Originality/value: Previous studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

The modernization of agriculture in China has begun to take shape, but some groups of farmers still have relatively weak access to welfare and live in poverty, which is closely related to national food security and sustainable agricultural development. Based on survey data from northeastern China, this study analyzes the logical framework of “Agricultural Productive Services (APS) Embedded—Farmers’ Family Economic Welfare Enhancement” by the endogenous switching regression model. The main findings are as follows. First, the purchase of APS brings a significant positive impact on farmers’ family economic welfare improvement, mainly through the income effect and the substitution effect. Second, with the income effect, there are significant differences in the strength of the “pulling power” of different forms of APS for farmers’ family economic welfare. Compared with farmers who purchase APS for the entire production chain, farmers who purchase only some of the services are more likely to increase their welfare in the later stages. Third, with the substitution effect, the re-employment behavior of the rural surplus laborers who are “squeezed out” under the embedding of APS is promoted, which makes farmers’ income channels, income types, and income opportunities diversify, and their welfare will be more obviously strengthened after purchasing services. In order to enhance farmers’ welfare more efficiently and meet their needs for a better life, this study suggests a combination of farmer information archiving and labor market information transparency to reduce service risks, expand employment channels, and enhance the effectiveness of the linkage between farmers and service providers.