Study on distribution dynamics,regional differences and convergence of digital agriculture in China
Based on the big data of China's digital agriculture enterprises from 2000 to 2022,this study uses kernel density estimation and Gini coefficient methods to evaluate the distribution of digital agriculture enterprises in different regions at the provincial level from an"inter-regional"agglomeration perspective.It also examines the convergence trends and influencing factors of digital agriculture enterprises using the σ-convergence model and the β-convergence model.The research finds that the overall agglomeration degree of China's digital agriculture presents an inverted U-shaped curve,with the eastern region leading in development,the central region developing relatively slowly,and the western region growing rapidly.The spatial distribution pattern of China's digital agriculture shows a"southeast-led,multi-core agglomeration"pattern.The overall development trend of digital agriculture in the east-central-west regions shows a"slow rise-violent fluctuation-rapid decline",while the overall development trend of digital agriculture in the south-north regions shows a"first expansion-then contraction".China's digital agriculture exhibits σ-convergence,absolute β-convergence,and conditional β-convergence phenomena,with the convergence speed showing a characteristic of"central-east-west"and"north-south"decreasing after adding control variables.Based on these findings,the study proposes strategies such as building local digital agriculture innovation centers and promoting the balanced regional development of digital agriculture,so as to advance the balanced and sustainable development of digital agriculture.
digital agricultureagglomeration of enterprisesspatial distributionspatial convergenceregional difference
NETL
NSTL
万方数据
