Digital financial inclusion (DFI), characterized by digitalization and inclusiveness, has generally been recognized as a significant promoter of efficiency, effectiveness, and sustainability of agricultural production. Simultaneously, cultivated land green utilization efficiency (CLGUE), which is the significant guarantees of food security, social stability and environmental protection, has attracted increasing attention in the recent decades. In practice, DFI seems to be a vital antecedent of the improvement of CLGUE. However, in the academic field, research on whether and how DFI can affect CLGUE is scarce. In this case, based on triple bottom line theory, this paper theoretically and empirically investigates whether and how DFI can reinforce CLGUE through the mediator of cultivated land transfer (CLT). Using Chinese provincial panel data from 2011 to 2020 and structural equation modelling (SEM) analysis in STATA 16.0, this paper identified the following: (1) DFI can directly facilitate CLGUE; (2) DFI can indirectly improve CLGUE through CLT. (3) DFI has regional heterogeneity in the improvement of CLGUE. Compared to the central and western areas, the positive relationship between DFI and CLGUE in the eastern areas is more obvious; (4) compared with main grain producing and main grain producing and marketing balance areas, the positive relationship in the main grain marketing areas is more obvious. Our research is one of the first to explore the mediating mechanism between DFI and CLGUE from the perspective of CLT.
The cultivated land green utilization efficiency (CLGUE) is closely related to high-quality agricultural development (HAD), but the evolutionary characteristics of the relationship between HAD and CLGUE have received little study. In the context of the rural revitalization strategy and high-quality development in China, it is important to ensure food security and cultivated land system security through coordinating HAD and CLGUE. In this study, 31 Chinese provinces were used as the research object, and the entropy weight TOPSIS model and SBM-Undesirable model were used to measure HAD and CLGUE, respectively. In addition, the coupling coordination degree model and the geographical analysis model were used to investigate the development of coordination degree concerning HAD and CLGUE from both geographical and temporal perspectives. The following findings are the result of this study. Firstly, both China’s overall HAD and CLGUE exhibited an upward tendency, with average annual growth rates of 4.35% and 4.08%, respectively. Secondly, there was a volatility upward trend shown by the level of coordination degree regarding HAD and CLGUE in China. Additionally, the coordination degree showed significant spatial-temporal disparities across the 31 provinces due to the variance in the natural endowment of agricultural development resources. Lastly, the coordination degree concerning HAD and CLGUE throughout China showed obvious patterns of spatial agglomeration at the provincial level. However, the geographical aggregation and dispersion of the provinces with high or low coordination levels have diminished somewhat. Furthermore, there was a conversion from hot spot aggregation regions in MGPAs to cold spot aggregation regions in GPMBAs. The conclusions of the present study enrich the theoretical literature on the relationship between HAD and CLGUE, and provide an empirical reference for the policy maker of the developing pathway of “high HAD and high CLGUE”.
In order to balance the relationship between economics, society and environment, the Chinese government has stated that China’s economy should shift from high-speed growth to high-quality development. Since agriculture is the foundation of the national economy, high-quality development of agriculture plays significant roles in the achievement of food security, social stability and environmental sustainability in China. In practice, the expansion of digital financial inclusion (DFI) seems to provide valuable opportunities for the development of high-quality agriculture. Nevertheless, in theory, the extant literature ignores exploration of the close relationships between DFI and high-quality agricultural development (HQAD). Hence, using Chinese provincial panel data from 2011 to 2020 and structural equation model (SEM) in STATA 16.0, this paper attempts to investigate whether and how DFI can enhance HQAD. Analysis reveals that (1) DFI can directly promote HQAD; (2) DFI can indirectly facilitate HQAD through the mediator of farmland transfer (FLT); (3) DFI can indirectly promote HQAD through the mediator of farmland mechanization level (FML); (4) compared with the benefits brought by “high-mechanization”, the benefits brought by “large-scale” farmland transfer policies are much greater. To our knowledge, our research is one of the first to investigate the direct and indirect effecting mechanisms of DFI’s influence on HQAD from the perspectives of farmland scale and farmland technology.
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