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This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent. [ABSTRACT FROM AUTHOR]

With the continuous development of Internet technology, all areas of social economy have undergone profound changes. The circulation and application of data elements can significantly promote the construction of infrastructure such as big data centers and mobile base stations, and stimulate the market demand for digital consumption such as digital production, e-commerce and digital trade. Data mining technology will provide sustainable impetus for economic development. There is a clearer analysis of the role of data elements in the platform economy, but there is a lack of research in macroeconomics, especially in the coupling of finance and technology. This paper developed a coupling coordination and a coupling efficiency index system, using different methods to measure outcomes and outline the path to achieving high "quantity" and "quality" of finance-technology coupling development. Based on the data mining technology in e-commerce, the fuzzy set qualitative comparative analysis method is used to analyze the complex mechanisms and driving paths of data elements affecting the coordination degree and coupling efficiency of finance-technology coupling performance of China. We empirically document that data mining and data management are necessary to improve coupling coordination; in the absence of other conditions, data mining or data management can produce high coupling coordination, but not sufficient to improve coupling efficiency. [ABSTRACT FROM AUTHOR]

China's economic growth has reached a new plateau. It is no longer appropriate to use the old economic growth model, which relied on labor, land resources, mineral resources, and other economic considerations. Under the background of artificial intelligence, high-quality economic development is an inevitable trend. A new financial paradigm called "digital finance" integrates financial services with information technologies. Digital financial technology is thought to be a crucial foundation for fostering high-quality and sustainable economic and social development since it may offer more economic entities reduced cost of capital and more realistic financial service skills than in traditional financial models. In the era of artificial intelligence, how to reasonably release the momentum of digital finance for China's sustained economic growth has become a hot topic of discussion at this stage. This paper studies the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence. Relevant metrics were also calculated. The findings revealed that: The benchmark regression result of digital finance on the efficiency of the green economy was 0.4685 before adding the main restrictions; the benchmark regression result of digital finance on the efficiency of the green economy was 0.2243 after adding the main constraints. As a result, data finance had a favorable impact on the effectiveness of the green economy. [ABSTRACT FROM AUTHOR]

The study examines the digital finance (DF) and regional sustainable development (RSD) across 90 cities within six major city clusters in China over the period from 2011 to 2020. By constructing an evaluation index system for DF and RSD, we employed the entropy value method to assess their levels, and the coupling coordination degree (CCD) model to evaluate their interplay. Our analysis extended to temporal and spatial disparities, distribution dynamics, and the convergence of CCD through kernel density estimation, Markov chain analysis, σ -convergence, and β -convergence techniques. The results indicate a consistent upward trend in CCD, yet it remains at a low level with pronounced regional disparities and temporal characteristics. The kernel density distribution's central tendency has shifted rightward progressively, albeit with a decelerating pace annually. The Markov transition probability matrix suggests a stable CCD across various levels, hinting at "club convergence". Furthermore, both σ -convergence and β -convergence analyses reveal significant convergence trends in CCD, enhanced by economic growth factors. Using the Quadratic Assignment Procedure (QAP) method, we found that regional economic growth disparities significantly influence the CCD's regional variances. [ABSTRACT FROM AUTHOR]

To investigate the impact of Green Digital Finance (GDF) policies on sustainable regional development goals, this study exploits the implementation of China's green finance reform and innovation pilot zones as a quasi-natural experiment to examine the theory and impact of policy channels on sustainable development. A difference-in-differences model was applied to evaluate the impact of policies in these zones based on data from 285 cities in China from 2014 to 2020. Research has shown that the GDF is conducive to achieving sustainable development goals through the effects of financial inclusion and energy transitions, which promote the transformation and upgrading of industrial structures. The impact of the GDF pilot-zone policies on the sustainable development of cities at different levels, locations, resource endowments, and green total factor productivity is heterogeneous. This study provides accurate empirical evidence of the effects of the extensive implementation of the policies adopted in the pilot zones and the expansion of the scale of these zones, and it provides policy recommendations for the GDF. [ABSTRACT FROM AUTHOR]