Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

The impact of technological innovation on the green digital economy and development strategies

To investigate the interplay among technological innovation, industrial structure, production methodologies, economic growth, and environmental consequences within the paradigm of a green economy and to put forth strategies for sustainable development, this study scrutinizes the limitations inherent in conventional deep learning networks. Firstly, this study analyzes the limitations and optimization strategies of multi-layer perceptron (MLP) networks under the background of the green economy. Secondly, the MLP network model is optimized, and the dynamic analysis of the impact of technological innovation on the digital economy is discussed. Finally, the effectiveness of the optimization model is verified by experiments. Moreover, a sustainable development strategy based on dynamic analysis is also proposed. The experimental results reveal that, in comparison to traditional Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) models, the optimized model in this study demonstrates improved performance across various metrics. With a sample size of 500, the optimized model achieves a prediction accuracy of 97.2% for forecasting future trends, representing an average increase of 14.6%. Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. In the examination of changes in industrial structure using 2020 data to forecast the output value of traditional and green industries in 2030, it is observed that the output value of traditional industries is anticipated to decrease, with an average decline of 11.4 billion yuan. Conversely, propelled by the development of the digital economy, the output value of green industries is expected to increase, with an average growth of 23.4 billion yuan. This shift in industrial structure aligns with the principles and trends of the green economy, further promoting sustainable development. In the study of innovative production methods, the green industry has achieved an increase in output and significantly enhanced production efficiency, showing an average growth of 2.135 million tons compared to the average in 2020. Consequently, this study highlights the dynamic impact of technological innovation on the digital economy and its crucial role within the context of a green economy. It holds certain reference significance for research on the dynamic effects of the digital economy under technological innovation.

Can digital economy development contribute to urban carbon emission reduction? - Empirical evidence from China

In the context of global digitalization, fostering the expansion of the digital economy holds immense importance in promoting energy efficiency and reducing emissions. Utilizing a sample of 281 prefecture-level cities in China from 2003 to 2019, this research analyzes the impact of the digital economy on urban carbon emissions in China. This study employs various methods, including principal component analysis, fixed-impact model, and mediating effect model. Based on the research findings, the development of the digital economy has the potential to significantly reduce carbon emissions in metropolitan areas. Moreover, these effects are especially noticeable in cities located to the east of the Hu Huanyong Line. These cities are characterized by limited reliance on resources and a high level of marketization. Further research reveals that promoting technical innovation and modernizing industrial structures can reduce the intensity of carbon emissions in metropolitan areas. This study provides empirical evidence supporting the effective reduction of carbon emissions in developing countries during the evolution of the digital economy. It acts as a crucial cornerstone for guiding policies and executing strategies aimed at fostering top-tier economic development in the future. The findings of this study confirm the inhibitory effect of the digital economy on urban carbon emission intensity. However, this study has limitations in data samples, research scope, and depth of mechanism analysis, which prevent a full exploration of the spatial spillover effect of the digital economy and other factors. Therefore, the conclusions drawn in this study can only provide empirical evidence for identifying the relationship between the digital economy and carbon emission intensity to a certain extent. Future research should aim to expand on these aspects.

Research on the coupling mechanism and influencing factors of digital economy and green technology innovation in Chinese urban agglomerations

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.

Energy saving effects of digital technologies from a life-cycle-analytical perspective: evidence from China

Digital technology has become a key driver of industrial transformation and resource utilization. However, no consensus has been reached on the exact relationship between digital technology and energy utilization. This study adopted a comprehensive index system to investigate the impact of digital technologies on energy utilization across 30 provinces in China. The results reveal a non-linear relationship between digital technologies and energy efficiency in China (represented by an N-curve), which is validated by robustness tests. This indicates digital technology exerts a fast-slow-rapid impact on improving energy efficiency throughout its initial-rapid-stable developmental stages. Geographically, this effect is more pronounced in eastern and central China, as well as in areas with lower energy efficiency. Furthermore, the impact of digital technology on total energy consumption can be characterized by an inverted N-shaped curve. As regional energy efficiency improves, the energy consumption associated with the development of digital technologies gradually decreases. These findings can contribute valuable insights for enhancing energy efficiency and provide practical guidance for the formulation of energy and digital technology policies.

Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China

This study provides an in-depth analysis of the complex relationship between the digital economy and carbon emissions, fully drawing on essential principles of environmental economics, coupled economics, and sustainable development theory. Focusing on the Qinghai region in the western province of China, the study employs highly sophisticated methods such as multiple regression analysis and system dynamics modeling to reveal the multidimensional coupling effects between digital economy development and carbon emission dynamics. The study's results clearly show that in the Qinghai region of China, the booming growth of the digital economy is related to carbon emissions. Of particular interest, the study finds that this relationship exhibits a high degree of complexity and non-linearity and evolves gradually over time. Initially, the rapid expansion of the digital economy, accompanied by high energy consumption and increased carbon emissions, posed a significant challenge to environmental protection. However, a clear inverted "U"-shaped relationship has emerged as the digital economy evolves. This key inflection point signals a shift in the landscape as the digital economy begins to deliver some ecological benefits, potentially reducing the trend of carbon emissions in the future. The findings of this study go beyond simple causality and reveal a complex and evolving dynamic relationship between the digital economy and carbon emissions. Through such insights, this study provides a solid academic foundation and carefully constructs actionable policy recommendations to drive sustainable development. These insights apply to the Qinghai region of China and provide valuable references and lessons for other areas facing similar challenges.

The impact of digital economy on carbon total factor productivity: A spatial analysis of major urban agglomerations in China

Amid global climate imperatives and intensified economic competition, pivoting from China's conventional growth paradigms to innovative economic catalysts emerges as pivotal for its transformative agenda. Drawing on panel data from 141 principal urban conglomerates spanning 2011-2021, this investigation delves into the intricate nexus between the digital economy and carbon total factor productivity. Our empirical analysis unveils a U-shaped trajectory characterizing the digital economy - carbon total factor productivity interplay, accompanied by a congruent spatial spillover dynamic. While digital economy fortifies environmental governance mechanisms through amplified data and media channels, such regulatory frameworks, albeit efficacious in emission abatement, may inadvertently impede economic vitality, thus attenuating carbon total factor productivity. Progressing from digital economy's foundational phase to its comprehensive deployment, its reverberations on capital productivity manifest in a U-shaped curve, invigorating local carbon total factor productivity while potentially undermining adjacent regions. This digital economy - carbon total factor productivity interrelation is accentuated in advanced, non-resource-reliant metropolises with subdued innovation propensities. This discourse proffers nuanced policy implications for sculpting digital economy trajectories and bolstering carbon total factor productivity in a sustainable context.

Research on the coupling coordination relationship between the digital economy and high-quality energy development: Evidence from China

The deep integration of the digital economy and high-quality energy development is a vital breakthrough in promoting the digital transformation and upgrading of energy, and it is also a critical path to achieving green and low-carbon development. However, the degree of integration of the two has yet to be discovered. This article measures the coupling coordination degree of the digital economy and high-quality energy development using panel data from 30 provinces in China from 2013 to 2020, explores the spatiotemporal evolution characteristics of the coupling coordination degree, and further analyzes the driving factors of the coupling coordination degree. The results show that:(1) The coupling coordination degree shows an upward trend, but there are apparent gradient differences and spatial non-equilibrium features in the coupling coordination degree among provinces. (2) The coupling coordination degree shows a "parabolic" spatial trend of "high east and low west" in the east-west direction and an "inverted U-shaped" spatial trend in the north-south direction. (3) The center of gravity of the coupling coordination degree moves to the southwest, clustering in the northeast-southwest direction and showing a spreading trend in the southeast-northwest direction. (4) The coupling coordination degree has a significant positive spatial correlation, and the cold-hot spot gradually develops into a distribution pattern with the Yangtze River Delta in China as the agglomeration center. (5) Economic development, industrial structure, government behavior, environmental regulation, urbanization, technological innovation, and external openness significantly impact the coupling coordination degree. In addition, economic development and human capital have a positive spatial spillover effect on the coupling coordination degree. Urbanization level and technological innovation have a negative spatial spillover effect on the coupling coordination degree. Accordingly, to promote the coupling and interaction between the digital economy and high-quality energy development, the government should take effective measures in optimizing the industrial structure, scientifically promoting the urbanization process, and enhancing the scientific and technological innovation capacity.

Urban climate adaptability and green total-factor productivity: Evidence from double dual machine learning and differences-in-differences techniques

Climate change has increasingly become a significant challenge to sustainable socio-economic development, and climate adaptation is a key issue that relevant research focuses on regional sustainable development models. By employing panel data between 2007 and 2020 from 284 Chinese prefecture-level cities, this study adopts quasi-experimental methods, including a difference-in-differences design and double dual machine learning model, to study the impact of climate adaptability on green regional sustainable development. Empirical results confirm that the pilot policy of building climate-resilient cities significantly improves urban green total-factor productivity. Difference-in-difference models (derived from entropy-weight and propensity score matching) and double dual learning models also support the improving effect of regional green total-factor productivity after policy intervention. The digital economy has strengthened the green development effect of pilot policies for building climate-adaptive cities. In addition, policy interventions to build climate-adaptive cities promote green urban development by optimizing industrial development structures and enhancing economic growth resilience. In addition, climate adaptability can also attract highly skilled talent and high-quality enterprises, facilitate science and technological progress in urban areas, and thus promoting the green development of cities in China. This study objectively evaluates the effects of climate policies and provides insights for global adaptation to climate change and optimization of public policies.

Impact of the digital economy on total factor energy efficiency: evidence from 268 Chinese cities

Due to the advancement of digital technology, the digital economy has developed rapidly, profoundly changing human production and lifestyles, thereby promoting the dual digital transformation of the energy supply and demand sides and having a profound impact on energy utilization efficiency. Based on measuring the total factor energy efficiency (TFEE) of 268 cities in China from 2011 to 2019, we analyze the total and indirect effects of the digital economy on TFEE using a mediated effects model and examine the effects of urban heterogeneity from the perspectives of geographical location, city size, and resource endowment. The results show that the digital economy has a significant positive contribution to TFEE. In addition, the digital economy can promote TFEE through industrial structure upgrading, technological innovation, and environmental regulation. The test results of the subsample show that there is significant heterogeneity in the impact and mechanism of action of the digital economy on TFEE in different geographical locations, city sizes, and resource endowments. By understanding how the digital economy impacts TFEE, policymakers can formulate effective policies to simultaneously accelerate digital economy development and improve TFEE.

Nonlinear impact of digital economy on carbon intensity: the moderating role of low-carbon regulation

The development of the digital economy is an effective way to mitigate the carbon emission problem in the broader setting of the significant data era and green development. Based on the panel data of 271 cities in China from 2011 to 2019, this paper constructs a bidirectional fixed model to analyze the nonlinear effect of the digital economy (DE) on carbon intensity (CI) and the moderating role of low-carbon regulation from theoretical and empirical perspectives. The results show that (1) DE has an enormous inverted U-shaped impact on CI. The findings remain after introducing instrumental variables to mitigate endogeneity and robustness tests. (2) Low-carbon regulation (CP) can strengthen the inverted U-shaped impact between the two and shift the inflection point to the left. (3) Heterogeneity analysis shows that the inverted U-shaped effect of DE on CI is more significant in the central and western regions, high human capital (HC) regions, and high urbanization regions. (4) The mediating effect of energy mix (EM) and green technology innovation (GTI) still hold after introducing instrumental variables to alleviate the endogenous effect of the intermediary effect. This study suggests that the adoption of carbon emission reduction strategies, which will more effectively lower carbon intensity CI, should go hand in hand with the development of DE.

Impact of digital trade on regional carbon emissions

In the context of the dual carbon targets, digital trade brings new impetus to China's economic development to achieve low-carbon emission reduction. This article uses panel data from 30 provinces in China from 2011 to 2020, and uses a two-way fixed effect model to empirically investigate the impact of digital trade development on regional carbon emissions and its heterogeneity. The results show that the development of digital trade significantly reduces regional carbon emissions, and the conclusion is still valid after conducting the robustness tests. Digital trade can reduce regional carbon emissions by exploiting its effects of expanding economic scale, upgrading industrial structure, and promoting green technology innovation. In addition, the carbon reduction effect of digital trade varies due to differences in regions, trade openness, and carbon emission intensity. The carbon reduction effect of digital trade in central and western regions is larger than that in eastern regions, and the effect in inland regions is greater than that in coastal regions. As the degree of trade liberalization increases and carbon intensity decreases, the carbon reduction effect of digital trade will also weaken. The research conclusions have profound practical significance for achieving the carbon neutrality target, effectively addressing climate change, and promoting high-quality economic development.

Does environmental governance matter to the relationship between digital transformation and high-quality development? Evidence from manufacturing sector in China

Environmental governance has emerged as a crucial tactic to support the sustainable development of human civilization in light of the serious environmental issues. Meanwhile, during the process of promoting the high-quality development of China's economy, digital transformation plays a significant role in improving the total factor productivity of the manufacturing sector. We seek to find out whether urban environmental governance has an impact on micro-enterprises, and therefore, the study selects the data of A-share listed manufacturing companies from 2012 to 2020 to study the effect of digital transformation on the total factor productivity of the manufacturing industry and how the effect of environmental governance affects the relationship between digital transformation and total factor productivity. The results unveil that digital transformation can significantly contribute to the total factor productivity of the manufacturing industry. At the same time, digital transformation can promote the high-quality development of enterprises by promoting the fulfillment of corporate social responsibility. Additionally, it is shown that poor environmental governance will weaken the promoting effect of digital transformation on total factor productivity. Furthermore, in state-owned companies and non-heavy polluting industries, environmental governance has a more significant moderating influence on digital transformation and total factor productivity. This study enriches the literature on urban environmental governance and micro-enterprise development, and they support the notion that, from the standpoints of environmental protection and economic development, the level of environmental governance should be continuously optimized and the development of ecological civilization should be strengthened.

Spatio-temporal heterogeneity of the coupling between digital economy and green total factor productivity and its influencing factors in China

The synergy of the digital economy and green total factor productivity (TFP) is the foundation for achieving beneficial outcomes for both the economy and environment. This synergy is also the catalyst for high-quality development and sustainable economic growth in China. The study applied a modified Ellison-Glaeser (EG) index, super-efficiency slacks-based measure (SBM) with a Malmquist-Luenberger (ML) index, coupling coordination degree, and other models to explore the spatiotemporal heterogeneity of the coupling between the digital economy and green TFP from 2011 to 2020 and also analyzed the influencing factors of the coupling. The results show that the coupling between the digital economy and green TFP showed an overall upward trend from imbalance to synergy during the study period. The distribution of the synergistic coupling expanded from point-like to band-like, and there was a significant spreading pattern from the east to the center or west China. The number of cities in a transition state decreased significantly. Spatial jumps, a coupling linkage effect, and evolution in time were prominent. Additionally, the absolute difference among cities expanded. Although coupling in the west experienced the fastest growth rate, the coupling in the east and resource-based cities showed significant benefits. Coupling did not reach an ideal coordinated state, and a neutral interaction pattern remains to be formed. Industrial collaboration, industrial upgrading, government support, economic foundation, and spatial quality all positively impacted the coupling; technological innovation had a lagged effect; and environmental regulation has not reached its full potential. Further, the positive effects of government support and spatial quality performed better in the east and in non-resource-based cities. Due to the optimization of industrial structure, the coupling of the west and resource-based cities achieved better dividends; however, spatial quality needs further improvement. Therefore, the efficient coordination of China's digital economy and green TFP requires a scientific, reasonable, localized, and distinctive approach.

Spatial spillover effect of the synergistic development of inward and outward foreign direct investment on ecological well-being performance in China

Inward and outward foreign direct investment (FDI) can promote a country's economic growth, but the effect of inward and outward FDI on regional ecological well-being performance (EWP) is uncertain. Using the data of 30 Chinese provinces from 2004 to 2019, this study employs the spatial Dubin model to examine the spatial spillover effects of synergistic development of inward and outward FDI on regional ecological well-being performance and their mediating mechanisms. The result shows that the synergistic development of inward and outward FDI can significantly improve regional EWP and imply a positive spatial spillover effect. The dynamic effect analysis indicates that synergistic development of inward and outward FDI has a lag effect on the improvement of regional EWP. The mechanism test found that the synergistic development of inward and outward FDI can enhance the EWP of the region and the spatially related regions by promoting the rationalization, upgrading and technological innovation of the industrial structure. These findings have some insights into improving global ecological well-being in an open economy.

Does economic growth target constraint put pressure on green energy efficiency? Evidence from China

Building a sustainable energy system and achieving sustainable economic growth has always been China's development goal. However, under the promotion incentive and information asymmetry, local governments may choose to sacrifice the ecological environment to maintain expected economic growth goals. This paper analyzes the relationship between economic growth targets and green energy efficiency (GEE) by using panel data models and spatial econometric techniques. Moreover, the mediation effect model and threshold effect model are used to study their influence mechanism and the possible nonlinear relationship. The results indicate that economic growth targets reduce the efficiency of GEE. The impact of environmental regulation on GEE is "U" shaped. Environmental regulation plays a positive moderation role between economic growth targets and GEE. Additionally, higher levels of technological innovation, industrial upgrading, and environmental regulation result in a reduction in the negative effects of economic growth targets on the GEE. However, the improvement in the foreign direct investment can increase the negative influences of economic growth targets on the GEE.

Digitalization, Electricity Consumption and Carbon Emissions-Evidence from Manufacturing Industries in China

The development of China's manufacturing industry is constrained by factors such as energy and resources, and low-carbon development is arduous. Digitalization is an important method to transform and upgrade traditional industries. Based on the panel data of 13 manufacturing industries in China from 2007 to 2019, a regression model and a threshold model were used to empirically test the impact of digitalization and electricity consumption on carbon emissions. The research results were as follows: (1) The digitalization level of China's manufacturing industry was steadily increasing; (2) The proportion of electricity consumption in China's manufacturing industries in the total electricity consumption hardly changed from 2007 to 2019, basically maintaining at about 6.8%. The total power consumption increased by about 2.1 times. (3) From 2007 to 2019, the total carbon emissions of China's manufacturing industry increased, but the carbon emissions of some manufacturing industries decreased. (4) There was an inverted U-shaped relationship between digitalization and carbon emissions, the higher the level of digitalization input, the greater the carbon emissions of the manufacturing industry. However, when digitalization develops to a certain extent, it will also suppress carbon emissions to a certain extent. (5) There was a significant positive correlation between electricity consumption and carbon emissions in the manufacturing industry. (6) There were double energy thresholds for the impact of labor-intensive and technology-intensive manufacturing digitalization on carbon emissions, but only a single economic threshold and scale threshold. There was a single scale threshold for capital-intensive manufacturing, and the value was -0.5352. This research provides possible countermeasures and policy recommendations for digitalization to empower the low-carbon development of China's manufacturing industry.

Place-Based Policies and Carbon Emission Efficiency: Quasi-Experiment in China's Old Revolutionary Base Areas

Regional imbalance is a typical feature of economic and social development in China, and place-based policies aimed at promoting balanced regional development may bring challenges to low-carbon goals. This study uses the panel data of China's prefecture-level cities from 2003 to 2019 to investigate the impact of place-based policies on carbon emission efficiency using a quasi-experimental method. Results indicate that place-based policies significantly reduce the regional total-factor carbon emission efficiency. The difference-in-differences method based on propensity score matching and entropy balancing matching consistently supports the finding that carbon emission efficiency decreases after policy intervention. Place-based policies lead to a significant decline in capital allocation efficiency but have an insignificant impact on labor allocation efficiency. Moreover, place-based policies result in the expansion of carbon-intensive industries but hinder the progress of the financial technology of financial institutions. Nevertheless, place-based policies do not lead to the deterioration of environmental quality. Among the advantages of these policies are the significant promotion of regional digitization and increased fiscal expenditure on science and technology. Political promotion, carbon regulation, trade policies, and other conditional factors may be optimally designed to promote low-carbon development in the old revolutionary areas.

Increasing short-term lending for long-term investment under environmental pressure: evidence from China's energy-intensive firms

To improve environmental quality and reduce pollutant emissions, China enacted the Environmental Protection Tax Law (EPTL) in 2018, leading to increase environmental pressure. Based on the data of energy-intensive firms listed in China's A-share market, this study examines firms' investment and financing behavior, increasing the short-term loans for long-term investment. Using the Difference-In-Differences (DID) method, empirical evidence supports the idea that environmental pressure causes energy-intensive firms to increase short-term lending for long-term investment (SLLI). Specifically, environmental pressure leads firms to increase long-term investment activities, such as fixed assets, environmental protection, and innovation. In contrast, long-term loans decrease, forcing firms to use short-term loans for long-term investments. Affected by rising environmental pressure, firms with low financing constraints are more likely to use short-term loans instead of long-term loans to support long-term investment activities, while firms with high financing constraints cannot obtain short-term loans. Our findings provide critical insights for promoting coordination between financial and environmental policies.

Exploring the Mechanism of the Impact of Green Finance and Digital Economy on China's Green Total Factor Productivity

In the context of the "double cycle," promoting the development of a green economy is an important goal for China's high-quality economic development in the digital age. This paper uses data from 30 provinces (municipalities and autonomous regions) in China during the 2006-2019 period using the Compiled Green Finance Index (GF) and Digital Economy Index (DE). The interrelationship between green finance, digital economy and green total factor productivity (GTFP) is empirically tested by conducting multiple regressions on panel data from 2006-2019 to perform an empirical analysis. Based on this, further analysis was performed with the threshold model. This study found that green finance and digital economy can contribute well to green total factor productivity, but the combination of the two does not have a good effect on green total factor productivity. Further study found that the green finance and digital economy's contribution to green total factor productivity is mainly derived from technological progress. The regression results based on the panel threshold model show that the more underdeveloped the digital economy is in certain regions, the stronger the role of green finance in promoting efficiency improvement. Therefore, policymakers should formulate differentiated green financial policies according to the level of development of the digital economy and give play to the role of green finance and the digital economy in promoting green total factor productivity.

Power of Digital Economy to Drive Urban-Rural Integration: Intrinsic Mechanism and Spatial Effect, from Perspective of Multidimensional Integration

The consensus that the digital economy drives urban-rural integration has been gradually reached both in practice and theory. Besides, the way by which the digital economy drives urban-rural integration remains updated iteratively. The coming period is an important opportunity to break down the dualistic urban-rural structure and improve the urban-rural integration development. It is also a critical stage for China to promote the deep integration of the digital economy and the real economy. In this study, the intrinsic mechanism of the digital economy in driving the four dimensions of urban-rural integration was elaborated. An analysis was made of the spatial effects in 30 provinces (municipalities and autonomous regions) of China during 2011-2019 using Bivariate Global Moran's I and geographically and temporally weighted regression (GTWR) models. As revealed by the results: (1) the digital economy and the four dimensions of urban-rural integration advance steadily, in which the convergence degree of urban and rural resident consumption is comparatively higher; (2) there is a significant spatial auto-correlation between the digital economy and the four dimensions of urban-rural integration, with the influence gradually strengthened with time; (3) the digital economy exerts mainly positive impacts on the equivalent allocation of urban and rural factors, integration of three industries in urban and rural areas, and convergence degree of urban and rural resident consumption, but inhibits the equalization of urban and rural public services in nearly half research areas; (4) both digital equipment basis and user basis play a vital role in promoting the four dimensions of urban-rural integration.

Coupling Coordination Measurement and Evaluation of Urban Digitalization and Green Development in China

The coordinated promotion of urban digitalization and green development is an inevitable requirement for sustainable development in the digital age. Based on the coupling mechanism of urban digitalization and green development, in this study, we took 282 cities at the prefecture level and above in China from 2011 to 2019 as the research object, and we constructed the evaluation index system and calculated the coupling coordination degree (CD&GDD) of the two through the coupling coordination degree model. We further used the Dagum Gini coefficient, kernel density estimation, Markov chain and Moran's I to assess the spatial effects of the regional differences, dynamic evolution trends and degree of coupling coordination. The results show the following: (1) The level of urban digitalization and green development show a fluctuating upward trend, and the interaction between the two is obvious. (2) Although the CD&GDD of most cities is continuously improving, it is still at a low level. There are large differences in the levels between the regions. (3) The inter-regional differences are the main source of the large overall differences in the CD&GDD in China, and these are mainly composed of the hypervariable density and net differences between the regions. (4) The phenomenon of "club convergence" exists in the CD&GDD. (5) The coupling coordination relationship between cities has a substantial spatial effect, and the spatial effect has obvious regional heterogeneity. The results and conclusions provide a reference for developing countries to promote green and low-carbon urban development.