Performance measurement and spatio-temporal evolution of rural living environment governance in China
Improving the rural living environment is the focus and crux of rural revitalization.Research on the evaluation and influ-encing factors of rural living environment governance(RLEG)is conducive to the improvement of living environment in the new stage of development.Based on the super-efficiency SBM model,this paper calculated the performance of RLEG in various provinces of China from 2011 to 2021.It explored the spatial and temporal differences in RLEG performance using kernel density estimation and the Dagum Gini coefficient.In addition,the GML index was employed to analyze the influencing factors of RLEG performance.The results showed that the overall performance of RLEG in China was at low to moderate level,but with a continuous improvement trend over time.There were multi-polarizations in the governance performance of RLEG across the country and the three major regions of the East,Central and West,but the polarization phenomenon was gradually weakening.At the same time,it presented a stepped spatial distribution pattern of"Northeast-East-Central-West"in descending order.The overall difference in RLEG performance in China showed a fluctuating upward trend.The difference was mainly due to differences between groups and hypervariable density differences,while the contribution rate of differences within groups was relatively low.The performance index of RLEG in China was on the rise,with technological progress being the main reason for the improvement in environmental governance performance in various regions.Improving the performance of RLEG required increasing resource input,optimizing the output structure,strengthening regional coordinated development,promoting in-ternal regional balance,and achieving improvement in comprehensive management level and technological progress by improving techni-cal efficiency,scale efficiency and promoting technological innovation.
rural living environmentgovernance performancespatio-temporal differencesdynamic efficiencyinfluencing factor
国家科技期刊平台
NSTL
万方数据
