Clarifying the spatial correlation network structure of green development efficiency (GDE) is of great significance for realizing coordinated and sustainable development in China. By constructing the evaluation index system of GDE, this study used the super epsilon-based measure (EBM) model that considers undesirable output to measure the GDE of China from 2000 to 2018, based on which the characteristics of the spatial correlation network characteristics and influencing factors were analyzed using social network analysis (SNA) and a geographical detector. The results indicated that: (1) The GDE of China as a whole remained relatively stable, and there was a significant spatial spillover effect of GDE between provinces; the spatial correlation network demonstrated complex and dense characteristics, and the closeness and stability of the network gradually increased. However, the strict hierarchical structure of the network still existed. (2) The eastern coastal provinces exhibited significant spillover effects and connectivity functions, while the northeastern and central-western provinces are located at the edges of the spatial correlation network. (3) The GDE spatial correlation network is divided into a leader subgroup, bridge subgroup and net benefit subgroup, with no isolated subgroup. (4) The economic development level, urbanization and financial development have a decisive impact on the formation of the GDE spatial correlation network.

Advancing the coordinated and mutually beneficial development of green development and common prosperity is an objective requirement for constructing modernization with Chinese characteristics. Based on clarifying the mechanisms of the coordinated evolution, this study employs the Haken model to quantitatively measure the relationship between green development and common prosperity and characterize the spatial and temporal patterns of the synergistic relationship between the two. Finally, the random forest model is used to analyze the driving factors affecting their coordinated evolution. The results indicate that: (1) From 2011 to 2022, China's green development efficiency and common prosperity index showed a fluctuating growth. The national green development has progressed to form a distinct northwest to southeast gradient differentiation pattern, with the Beijing and the Yangtze River Delta leading in advancing common prosperity. (2) During the study period, the level of synergy between green development and common prosperity rose significantly, presenting a spatial pattern of "stronger in the east and weaker in the west", a continuous narrowing of regional differences, and the type of synergistic evolution in each region showing phased positive development. (3) The economic foundation, industrial structure, environmental regulation, financial development and digital economy can more stably promote the benign synergy and interaction between green development and common prosperity, while the driving role of government regulation first rises and then falls. The results of the study can provide a reference for China's collaborative promotion of comprehensive economic and social green transformation and common prosperity.

【目的】新质生产力作为经济高质量发展的新动能，探究其对生态福利绩效的作用机制，对于推动生态文明建设与民生福祉改善具有重要意义。【方法】在解析新质生产力影响生态福利绩效理论机制的基础上，采用熵值法和Super-EBM模型测度2013—2022年中国285个地级及以上城市的新质生产力和生态福利绩效，刻画二者时空演变规律，进而组合运用固定效应模型、中介效应模型和空间杜宾模型，实证检验新质生产力对生态福利绩效的作用机制及空间溢出效应。【结果】①2013—2022年中国市域新质生产力水平总体保持上升趋势，空间格局上呈现“东高西低”的带状分布特征；生态福利绩效总体呈“先下降后上升”的变化趋势，空间格局上呈现非均衡的团簇状分布特征。②新质生产力对生态福利绩效具有正向促进作用，且在逐步加入控制变量后该结论仍然成立。其中，绿色创新和数字化转型是两条重要的中介渠道。③新质生产力对生态福利绩效具有显著的正向空间溢出效应，即新质生产力不仅能够有效改善本地生态福利绩效，还能够促进相邻城市生态福利绩效的提升。④空间异质性检验显示，新质生产力对生态福利绩效的正向影响在外围城市强于中心城市，且相比于强环境规制城市和高金融发展水平城市，在弱环境规制和低金融发展水平地区的促进作用更为显著。【结论】新质生产力是提升中国生态福利绩效的重要动力源，且具有显著的空间溢出性。因此，应因地制宜发挥新质生产力的赋能效应、推动绿色技术创新升级与数字化转型，以持续增进民生福祉、实现经济发展与环境保护的协同增效。