The aging of the rural population is one of the important social problems facing China and the world. To provide strategic support for coping with the challenges brought by an aging society, this study examined the impact of aging of the rural population on agricultural green total factor productivity (AGTFP) and the mechanism of transmission between them, based on the panel data of 31 provinces in China from 2000 to 2022. The results showed that, first, the aging of the rural population had a negative inhibitory effect on AGTFP, a conclusion that remained valid after a series of robustness tests. Second, the heterogeneity analysis showed that the aging of the rural population in western China had a significant negative impact on AGTFP, while the effect was less significant in eastern and central regions. The intensity of environmental regulation will increase the negative impact of an aging rural population on AGTFP. Third, the analysis of the mechanism showed that the aging of the rural population had a negative impact on AGTFP by inhibiting labor productivity, scientific research and innovation, and farmland transfer.

Local officials play active and important roles in the high-quality agricultural development process in China. In this study, the DEA-SBM model was used to measure the level of agricultural quality development in China, and Tobit regression was conducted to analyze the impacts of officials on agricultural quality development in China. The results showed that between 1997 and 2016, the agricultural GTFP exhibited a downward trend before following an upward trend in China. The personal characteristics of officials had important effects on the development of agricultural quality. In different development stages, officials had diverse effects on agricultural quality development.

Under the background of uncertainty brought by the rapid development of AI, participation in AI standardisation is becoming the key for strategic emerging enterprises (SEEs) to break through and achieve sustainable development. This paper selects listed SEEs from the China Strategic Emerging Industries Composite Index jointly issued by China Securities Index Co., Ltd. and the Shanghai Stock Exchange in 2017 as the initial sample. We collect 3430 observations from 380 companies spanning 2010 to 2023. This paper employs a two-way fixed effects model incorporating enterprise clustering. It thoroughly investigates and empirically tests how participation in AI standardisation affects the sustainable development of SEEs under uncertainty. It is found that participation in AI standardisation in the context of uncertainty has a significant positive effect on the sustainable development of SEEs, and this conclusion still holds after employing instrumental variables, difference-in-difference, and a series of robustness tests. Mechanism tests indicate that two transmission paths exist between participation in AI standardisation and the sustainable development of SEEs under uncertainty: digital technology innovation and the dynamic capabilities in the dimensions of learning and absorption as well as change and reconfiguration. However, the dynamic capabilities in the coordination and integration dimensions do not play a significant mediating role. Heterogeneity analyses indicate that participation in AI standardisation contributes more significantly to the sustainable development of SEEs that are not state-owned, face lower environmental and information uncertainty, and are under higher economic policy uncertainty. The findings enrich the research related to AI standardisation and firm sustainability and provide policy recommendations for the sustainable development of SEEs in the context of uncertainty.

As an important strategic material in China, cotton policy has positive significance in stabilizing the safety of domestic cotton, ensuring cotton income, and stabilizing cotton output. At the same time, affected by the future market price, the cotton industry supply chain cost management is particularly important. Based on the data of China’s cotton price, consumption, yield, and wheeling-in and wheeling-out from 1978 to 2016, the simultaneous equation model is used to empirically analyze the transmission effect of the rotation mechanism of reserve cotton (RMRC) on cotton supply and demand. Studies have shown that China’s cotton reserve policy and the RMRC play a positive role in balancing the supply and demand of the domestic cotton market and preventing excessive fluctuations in cotton prices. The transmission effect of the RMRC on domestic cotton yield and consumption is significant and there are certain differences. The transmission effect of domestic cotton yield is stronger than the transmission effect on domestic cotton consumption. The difference is owing to the transfer path of the RMRC being different. We should improve the regulation and control effect of the RMRC on cotton demand, realize the normalization of the RMRC, and clarify the policy objectives of the RMRC.

Against the backdrop of pursuing technological self-reliance and strength, examining how participation in technical standard setting influences corporate patient capital investment holds significant importance. This study constructs a complex mediation model based on the Technology-Organization-Environment (TOE) framework. It employs a sample of 211 listed enterprises involved in China’s Information and Communication Technology (ICT) standardization. Utilizing both their cross-sectional data from 2023 and panel data spanning 2003 to 2024, it empirically tests the impact of participation in technical standard setting on corporate patient capital investment and its underlying mechanisms. Findings reveal: First, participation in technical standard setting exerts a significant and robust direct positive effect on corporate patient capital investment. Second, this influence operates primarily through multiple heterogeneous configurational pathways. Configurational analysis identifies four pathways leading to higher patient capital investment, categorized into “innovation-driven” and “sustainable development-driven” types. Further mediation tests reveal that three of these pathways mediate the relationship between participation in technical standard setting and patient capital investment. Third, comparative analysis of linear and complex mediation mechanisms reveals that participation in technical standard setting primarily exerts direct effects through independent pathways influencing innovation levels, innovation information disclosure, and ESG responsibility fulfillment. Variables such as long-term corporate investment and financing constraints—which are insignificant in linear models—emerge as critical components within specific configuration scenarios. These findings enrich the literature on the economic consequences of participating in technical standard setting and the determinants of patient capital investment, providing theoretical foundations and practical references for optimizing corporate strategic allocation and formulating relevant government policies.