Agricultural new quality productivity empowering rural revitalization: Mechanisms and spatial spillover effects

Rural revitalization is required for modern agriculture in China. Empowering rural revitalization with agricultural new quality productivity has been one of the important national strategies in recent years. This study aims to explore the impact of agricultural new quality productivity on rural revitalization. Provincial panel data were collected from 2012 to 2022. 1) The Spatial Durbin model was used to determine the direct and spatial spillover effect of agricultural new quality productivity on rural revitalization. 2) The mediating effect model was adopted to test the influence mechanism and the regional heterogeneity was explored after evaluation. The results showed that agricultural new quality productivity significantly promoted rural revitalization, particularly with the significant negative effect of spatial spillover; Agricultural new quality productivity empowered urban-rural integration and rural science and technology finance to promote rural revitalization. Urban-rural integration played a more significant role, compared with rural science and technology finance; The most obvious effect of agricultural new quality productivity was observed in the eastern regions. There were significant negative effects of spatial spillover of agricultural new quality productivity in the eastern and central regions, while there was no significant spillover effect in the western region. Some suggestions were proposed from the three perspectives. 1) A differentiated regulatory system should be established with "coordinated development and balanced interests" patterns. 2) Industries, technology, and finance should be integrated for decision decision-making. 3) A regional pattern of agricultural new quality productivity should be featured by eastern leadership, central support and western characteristics. Three prospects were also presented. 1)Municipal or county levels can be refined to explore the artificial intelligence in scenarios, such as agricultural remote sensing, intelligent decision-making, and precise operations, thus resolving the disconnection between quantitative statistics and qualitative penetration of artificial intelligence in the agricultural field. 2) It is also required to explore the interaction between urban-rural integration and rural science and technology finance under the background of artificial intelligence. The regulatory role of the institutional environment can be determined to alleviate the dynamic imbalance between technological empowerment and institutional adaptation in the development of agricultural new quality productivity. 3) A combination of case analysis and spatial econometric models can also be adopted to systematically examine the negative spatial spillover of agricultural new quality productivity. It is very necessary to solve the contradiction between the technological diffusion and the geographical spatial attenuation in the dynamic patterns of agricultural new quality productivity.