LAUSR

The contradiction between the endless pursuit of material possessions and finite natural resources hampers ecological well-being performance (EWP) improvement. Green transformation, recognized as an emerging strategy in sustainable development, can help to coordinate ecological, social, and economic growth by optimizing resource usage, with the ultimate objective of enhancing EWP. This research quantifies how green transformation influences EWP by using panel data from 78 prefecture-level cities in western China from 2012 to 2019. Using the super-SBM and entropy weight models, we assess the EWP and green transformation index (GTI) of 78 prefecture-level cities in western China. On this basis, we quantify the spatial characteristics of EWP by an analysis of the Theil index and spatial autocorrelation. Finally, we examine how GTI affects EWP using the Spatial Durbin model. The results demonstrate that the GTI can raise the EWP of local and nearby cities in western China. According to a GTI analysis of internal indicators, the industrial solid waste usage, harm-less treatment rate of domestic waste, savings level, and R&D expenditure significantly affect EWP. In contrast, the soot emission and consumption levels impede EWP advancement. The analysis of effect decomposition indicates that the sewage treatment rate, expenditure on science and technology, and green patents have a significant spatial spillover effect on the improvement of EWP.