Green development is a significant concept that cannot be ignored in contemporary society. However, in the context of China’s transition from high-speed growth to high-quality development, the complex impact of urban development has brought great challenges to the urban green environment. In this paper, the impact of urban development on green development efficiency (GDE) was studied. First and foremost, a Super-SBM model was introduced to measure the GDE of 41 cities in the Yangtze River Delta during 2009–2018. Moreover, a Tobit model was used to analyze the correlation between four urban development factors, including economic development and GDE. According to the results, the mean GDE of the Yangtze River Delta is 0.824, and the GDE in most cities there has shown a fluctuating growth trend in this decade. By comparison, the GDEs of coastal cities and cities in the southeast of the Yangtze River Delta were generally higher than those of cities in the north, indicating that the green development is geographically unbalanced, and there is spatial heterogeneity in the area studied. The study’s results also suggest that the urban economic development, innovation level, and government planning play a significant role in stimulating urban green development, and that the expansion of urban construction area hinders the improvement of GDE.

The eco-efficiency of rice production is an important indicator in the measurement of sustainable rice development. Scientific evaluation of the eco-efficiency of rice production facilitates accurate evaluation of the real level of rice ecosystems to realize efficient utilization of agricultural resources. This paper measured the eco-efficiency of farms growing rice using both the life cycle assessment (LCA) and the data envelopment analysis (DEA) methods based on survey data from 370 farms mainly growing rice conducted in 2020 in the Hubei Province, the middle reaches of the Yangtze River in China. Then, sensitivity analysis and scenario analysis were carried out on the comprehensive index of the rice environmental impact and eco-efficiency of rice production, respectively. The results indicate that the comprehensive index of the rice environmental impact was 2.0971. Water toxicity, soil toxicity and eutrophication were the main influencing factors. The mean value of the eco-efficiency reached 0.51. More specifically, the proportion of farms in the low-, middle- and high-efficiency groups was 87.03%, 1.89% and 11.08%, respectively, with mean values up to 0.42, 0.86 and 1.14, respectively. A sensitivity analysis revealed that the pesticide sensitivity was higher than the fertilizer sensitivity in terms of the environmental impact sensitivity of rice systems. When comprehensively considering environmental and economic benefits, the fertilizer sensitivity was higher than that of pesticides. Moreover, reducing the application of both fertilizers and pesticides by 50% could promote the eco-efficiency of rice production systems by 6%, and the value could reach 0.54. Thus, reducing the application of fertilizers and pesticides and improving the utilization efficiency are effective ways to improve green rice production.

Purpose: As an important engine of economic growth, the digital economy is bringing new opportunities for the promotion of entrepreneurship. However, key questions regarding the extent of the effect of the digital economy on entrepreneurship remain unanswered. This study examines how the digital economy influences entrepreneurship in China using provincial data from 2011–2020, applying convergence tests and spatial econometric models.Design/methodology/approach: Based on theoretical analysis and using macro provincial data covering the period of 2011–2020, we adopt a diversified empirical analytical method and apply a combination of the convergence trend test, spatial auto correlation test, and spatial Durbin model to test the research hypotheses.Findings: First, there is spatial correlation between the digital economy and entrepreneurship. Second, the overall trend of China’s digital economy shows s convergence, with the whole country and the eastern region showing absolute β convergence and the whole country as well as the central and western regions showing β conditional convergence. Third, the digital economy can significantly promote entrepreneurship and has spatial spillover effects. Moreover, higher education has a negative moderating effect on the process of digital economy empowering entrepreneurship.Research limitations/implications: Studying the spatially correlated impacts of the digital economy on entrepreneurship enhances our understanding of its contribution to economic growth. Policy-makers can use these findings to develop targeted digital infrastructure investments in lagging provinces, guide entrepreneurs to better grasp the opportunities of the digital economy, and provide support for innovation and entrepreneurship. The findings also could offer Chinese experience that can be used to guide developing countries in utilizing the digital economy to enable entrepreneurship.Originality/value: This paper expands and enriches the analytical focus on digital economy-empowered entrepreneurship and complements the current theoretical research on the moderating effect of the digital economy in empowering entrepreneurship.

Identifying the key factors influencing agricultural carbon emissions and accurately predicting future trends are essential for achieving carbon peak and carbon neutrality goals. This study aims to assess carbon emissions in agriculture from 1997 to 2022, construct an accurate model to identify the key influencing factors, and predict carbon emissions in agriculture from 2023 to 2030 with an intelligent prediction system to discuss risk management. Additionally, the Dagum method was employed to explore regional differences in agricultural carbon emissions across China. The results reveal that China’s agricultural carbon emissions exhibited a fluctuating trend from 1997 to 2022, peaking in 2015, followed by a period of decline and a moderate rebound in recent years. Elastic Net Regression identified eleven key variables, including Agricultural Machinery Level (MA), Numbers of Agricultural Tools (AT), and Agricultural Industrial Structure Upgrading (AICE), as major determinants of agricultural carbon emissions. Furthermore, the RF-PSO method demonstrated the highest predictive accuracy, forecasting a minor peak in agricultural carbon emissions in 2027, followed by stabilization. Regionally, imbalances in emissions were observed, with the intensity of transvariation accounting for 37.078% of the disparity. Therefore, the Chinese government is advised to implement region-specific strategies for controlling agricultural carbon emissions, cultivate new high-quality agricultural productivity, and promote advanced technologies.

As global urbanization accelerates, the rapidly growing urban population poses significant challenges to the realization of sustainable development. The Urban Vulnerability–Adaptation–Settlements (VAS) nexus has emerged as a critical research domain to address these challenges. This study conducts a bibliometric analysis of 887 highly cited publications from the Web of Science Core Collection to identify key scholars, research institutions, countries, core research domains, and emerging trends in the field. The findings reveal that: (1) Research related to the Urban VAS nexus can be divided into three developmental phases: the initial budding stage (1958–1991), the high-growth stage (1992–2018), and the stable development stage (2019–2024); (2) Current research primarily focuses on population urbanization, land urbanization, and industrial development, while addressing core issues such as environmental sustainability, social equity, smart governance, and community development; (3) Future research should place greater emphasis on the development of smart cities, green infrastructure, and energy transitions, while also exploring policy innovations and technological advancements to foster a more equitable and sustainable urban future. Based on the finding, this study argues that the key to future urban development lies not in the “speed of growth” but in the “quality of resilience.” Researchers are encouraged to promote multi-scale, multi-dimensional studies of VAS coupling mechanisms, while integrating smart governance, green transitions, and inclusive development goals into urban policy and practice.

Agricultural total factor productivity (ATFP) serves as the core driver and a critical benchmark for high-quality agricultural development. Utilizing panel data from 31 Chinese provinces (2012–2023), this study examines the impact, mechanisms, and heterogeneity of agricultural digital infrastructure construction (ADIC) on ATFP. Results show that digital infrastructure significantly promotes ATFP with a distinct non-linear acceleration. Specifically, once development surpasses a critical threshold (1.5416), marginal contributions increase substantially, marking a transition of digital dividends from “accumulation” to “explosive release.” Mediation analysis identifies green technological innovation and farmland scale management as key pathways, accounting for 11.4% and 12.5% of the total effect, respectively. This confirms ADIC enhances ATFP through a technical innovation effect and a scale operation effect. Regional heterogeneity is significant: digital infrastructure yields significant positive impacts on main food consumption and balanced areas, whereas results for main grain-producing areas remain statistically insignificant. Based on these conclusions, it is recommended that policymakers maintain strategic focus by proactively deploying rural digital infrastructure to surpass critical thresholds, implementing differentiated regional strategies, and effectively translating digital dividends into endogenous momentum for high-quality agricultural development through the integrated application of green technologies and the improvement of farmland transfer service systems.