<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>

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With the continuous advancement of global scientific and technological capabilities, the issue of global warming caused by greenhouse gas emissions has received widespread attention from countries worldwide. Promoting carbon reduction and curbing the trend of global warming have become urgent and significant challenges for China and the world. Therefore, it is of great practical significance to explore the impact and mechanism of the digital economy on carbon reduction. This paper empirically analyzes the impact and means of the digital economy on carbon emissions using panel regression models and mediation effect models. The research indicates that the digital economy significantly impacts carbon emissions, and the following main conclusions are drawn: (1) The influence of the digital economy on carbon intensity exhibits an inverted U-shaped curve, starting with promotion and then inhibition. (2) The digital economy can affect carbon emissions through industrial structural upgrading and technological innovation. (3) Regions with a relatively high level of digital economy development also tend to have higher energy utilization efficiency, leading to a more pronounced impact of the digital economy on carbon emissions levels.

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