<abstract> <p>Technological progress, especially green innovation, is a key factor in achieving sustainable development and promoting economic growth. In this study, based on innovation value chain theory, we employ the location entropy, super-efficiency SBM-DEA model, and the improved entropy TOPSIS method to measure the technological industry agglomeration, two-stage green innovation efficiency, and development quality index in Yangtze River Delta city cluster, respectively. We then build a spatial panel simultaneous cubic equation model, focusing on the interaction effects among the three factors. The findings indicate: (1) There are significant spatial links between the technological industry agglomeration, green innovation efficiency, and development quality in city cluster. (2) The development quality and technological industry agglomeration are mutually beneficial. In the R&amp;D stage, green innovation efficiency, development quality, and technological industry agglomeration compete with each other, while there is a mutual promotion in the transformation stage. (3) The spatial interaction among the three factors reveals the heterogeneity of two innovation stages. The positive geographical spillover effects of technological industry agglomeration, green innovation efficiency, and development quality are all related to each other. This paper can provide a reference for the direction and path of improving the development quality of city clusters worldwide.</p> </abstract>

Objectively recognizing and improving the sustainable development resilience of China's natural gas industry will help achieve the low-carbon transformation goal of China's energy system. Taking 31 Chinese provinces as the research area, this paper measures the sustainable development resilience (SDR) of China's natural gas industry based on the Drive-Pressure-State-Impact-Response (DPSIR) model and entropy method, and integrates the gravity correction model and social network analysis methods to identify the spatial linkages and network patterns among core regions, and further explores the development trend of the SDR of China's natural gas industry using grey model (GM(1,1)) moderated by a variable-weight buffer operator. The results show that: (1) There are significant regional differences in the SDR of the natural gas industry across Chinese provinces. The SDR is a high priority in Shanghai, Shaanxi, Sichuan, Xinjiang, Guangdong and Shandong, while it is low major in Tibet, Yunnan, Guangxi, Guizhou and Ningxia. (2) The spatial connection network density is low in China's natural gas industry, and the network correlation between provinces is poor. In detail, Jiangsu, Guangdong and Shandong are the core of the entire network and the connection lines between provinces are mainly basic in the whole region with poor connection strength, but there is a trend for the better. (3) The changing trend is significantly different in the SDR of Chinese provinces, and the prediction results show a trend of “polarization” in the SDR index of the provinces in the resource endowment area.