新疆师范大学学报（自然科学版）2025，Vol.44Issue(3)：86-96,11.
中国城市生态福利绩效的转移路径预测研究
A Study on Transfer Path Prediction of Ecological Welfare Performance in Chinese Cities
摘要
Abstract
This study focuses on the accounting of Ecological Welfare Performance(EWP),aiming to assess the weak links and internal disparities in achieving SDG11 at the aggregate level within regions,thereby promoting ecological urban planning and management,enhancing the potential welfare of urban residents,and simultaneously reducing adverse impacts on the ecological environment.Using China as a case study of a developing country,the SBM-DEA model is employed to measure the EWP of 281 Chinese cities from 2011 to 2021.The Dagum Gini coefficient method is utilized to calculate and analyze the spatiotemporal evolution patterns and regional disparities of urban EWP.Finally,the spatial Markov chain is applied to reveal the dynamic evolution characteristics.The research findings indicate:(1)The overall EWP shows a trend of initial increase followed by a decline;(2)The spatial distribution pattern of high EWP values in Chinese cities has shifted from the western and eastern regions to the central and eastern regions,with the overall regional disparity in EWP showing a narrowing trend,where hypervariable density is the main factor contributing to the overall regional disparity;(3)The EWP of each city exhibits high stability and also demonstrates spatial positive correlation characteristics,with the presence of"club convergence",making leapfrog development difficult to achieve in the short term.The upward or downward transition of urban EWP is influenced by the differential impacts of neighboring cities.The article will offer recommendations based on insights from EWP,aiming to provide certain references for policymakers.关键词
生态福利绩效/SBM-DEA模型/Dagum基尼系数/空间Markov链Key words
Ecological welfare performance/SBM-DEA model/Dagum's Gini coefficient/Spatial Markov chain分类
资源环境引用本文复制引用
陈年安..中国城市生态福利绩效的转移路径预测研究[J].新疆师范大学学报（自然科学版）,2025,44(3):86-96,11.基金项目
教育部人文社科青年项目(22YJC790121) （22YJC790121）
安徽省自然科学基金项目(2308085QG237). （2308085QG237）
