Although the digital economy (DE) and sustainable urban systems have drawn growing attention, how DE drives urban energy transition (UET) remains insufficiently understood. Employing panel data from 266 Chinese cities spanning 2011–2021, this study applies fixed-effects, mediation, moderation, and spatial Durbin models to examine the impact of DE on UET. UET is measured by a composite index that captures energy system performance and transition readiness. The results show that DE is positively associated with UET, with a one-unit increase in DE corresponding to a 0.1566-unit increase in UET. This finding remains robust after employing an instrumental-variable approach and a battery of robustness checks, including an exogenous policy shock. This positive effect is partially mediated by reduced resource misallocation and industrial structure upgrading. When electricity intensity is treated as a moderating factor, cities with higher electricity intensity exhibit a more pronounced positive effect of DE on UET. Further evidence indicates that DE advances UET in the eastern, central, and western regions, but has a limited impact in the northeastern region. Additionally, DE exerts positive spillover effects, thereby advancing energy transition in neighboring cities.
The digital economy (DE) is a nascent economic model with the potential to mitigate urban industrial pollution (UIP) while encouraging high-quality economic expansion. This paper utilized panel data from 258 Chinese cities and employed the fixed-effects model, the mechanism test model, panel threshold model, and the spatial Durbin model to undertake an empirical investigation into the DE on UIP emissions. The research outcomes suggest that developing the DE has a positive influence on UIP reduction and that the effect of the DE on UIP reduction varies significantly across regions with different levels of industrial development, digital infrastructure, and environmental regulatory intensity. Further examination shows that the DE can reduce UIP by promoting public environmental concern and green technology innovation. Additionally, when the DE is used as a threshold variable, the DE’s impact on UIP emissions exhibits a nonlinear double-threshold effect, with two key turning points of 0.0921 and 0.5515, which constitute a three-stage model of “weak effect—strong effect—weak effect”. When human resource leve is used as a threshold variable, the impact of the digital economy on reducing urban industrial pollution is gradually increasing and exhibits a nonlinear single threshold effect. Under different geographical and economic distance spatial weight matrices, the DE’s development has a substantial negative spatial spillover effect on UIP emissions. That is, developing the local DE can directly reduce local UIP and significantly suppress UIP in neighboring areas indirectly through information sharing and technology diffusion. The findings of this study provide important management insights for government managers to advance environmental governance and promote green development.
Mingzhao Xiong, Yize Li, Haoyi Qi et al.· Frontiers in Environmental S...· 0 citations
This study addresses the existing literature gap concerning the non-linear effects and operational mechanisms of impact of the digital economy (DE) on urban-rural integration (URI). To this purpose, panel data from 110 cities within the Yangtze River Economic Belt (YREB) are employed, spanning the period 2013–2022. Building upon the quantification of the DE and URI, this study employs the Panel Smooth Transition Regression (PSTR) model and the mediation effect model to examine the impact and of the DE on URI from a dynamic, non-linear perspective. The results showed that from 2013 to 2022, both the DE and URI in the YREB followed a consistent upward trend year on year, while regional disparities gradually narrowed. The DE showed increasing marginal effects across all dimensions of URI—economic, social, spatial, and social cohesion—exhibiting a nonlinear pattern. Moreover, it mitigated urban-rural resource misallocation to foster integrated development, with labor misallocation mitigation serving as the primary pathway. Furthermore, the role of the DE in alleviating capital misallocation remained less pronounced, compared to other mechanisms. These findings provide quantitative evidence and theoretical support for leveraging the DE to foster URI.
Yanxiao Yin, Xuanguo Xu, Haoyu Lin· Frontiers in Human Dynamics· 0 citations
This study addresses the urbanization-energy paradox by evaluating whether structural shifts in Indonesia can facilitate a systemic decoupling of energy intensity from economic growth. While industrialization is traditionally associated with rising resource demand, we test the hypothesis that urban agglomeration functions as a latent efficiency mechanism. Utilizing an Error Correction Model (ECM) on national time-series data (2000–2021), this study models the long-term equilibrium and short-term stochastic shocks that define the energy-economy nexus. The empirical results uncover a strategic duality: industrialization remains a primary driver of energy intensity, yet urbanization exerts a statistically significant downward pressure. This inverse relationship suggests that agglomeration economies enhanced by density-driven infrastructure and optimized resource distribution effectively neutralize the energy burdens of industrial scaling. The Error Correction Term (ECT) provides robust evidence of an adjustment mechanism, indicating that the energy system consistently reverts to a long-term efficiency trajectory. The findings move the discourse beyond reactive conservation toward systemic decarbonization. We conclude that leveraging urban density is critical for Indonesia’s Carbon Neutrality mandates. Policy recommendations focus on the institutionalization of Energy Service Companies (ESCOs) and polycentric urban planning as essential frameworks for sustaining structural energy efficiency.
P. Suwarno, Mochamad Ali Imron· Journal of Intelligent Decis...· 0 citations
Over the past two decades, Asia's economic transformation has driven by digitalization and urbanization, and yet its environmental impact remains insufficiently understood. Using panel data from 22 Asian countries between 2000 and 2021, this study investigates whether internet usage influences carbon emissions and whether urbanization (urban population) amplifies this effect. The results reveal that urbanization intensifies the environmental impact of internet usage (digitalization). Testing for endogeneity concerns using a quasi-natural experiment, the results confirm that the moderating effect persists under stable economic conditions; however, the impact is not prominent during crises such as COVID-19. The discoveries emphasize the growing challenge of integrating digital expansion, rapid urban development, and environmental sustainability. More importantly, the study highlights the need for synchronization between environmental engineering strategies and urban planning methods that align with digital infrastructure. This evidence contributes to the debate on sustainable urban transitions in emerging economies and offers insights into how environmental engineering and urban planning can reduce the environmental pressure of digitalization.
Mohd Ashari Bakri, Masnun Al Mahi, Abdul Rahim Ridzuan· E3S Web of Conferences· 0 citations
Despite the digital economy’s potential to support decarbonization, the role of population dynamics in shaping this association remains unclear. More empirical and theoretical studies are needed to understand this relationship. Based on this background, this study aims to explore the complex associations between the digital economy, population, and carbon emissions based on China 31 provinces panel data from 2000 to 2020 sourced from the China Statistical Yearbook. The study innovatively employs a population distance matrix to analyze how population factors condition the digital economy-emissions association and utilizes a structural equation model to overcome the limitations of traditional single-pathway mediation analyses. The findings suggest that the digital economy is significantly negatively associated with carbon dioxide emissions across China, with notable spatial spillover associations. Additionally, there is a strong negative-emissions association between population ageing and the digital economy, while population mobility exhibits a significant negative association. Moreover, as population density increases, the association between the digital economy and emissions initially intensifies, then diminishes.
Xuyang Du, Xinyang Chen, Lingli Guo et al.· Frontiers in Environmental S...· 0 citations
Digital-intelligent transformation (DIT) has become an important driver of sustainable urban development, yet its impact on urban eco-efficiency (EE) remains insufficiently understood. Using panel data for 281 prefecture-level cities in China from 2010 to 2023, this study examines the effect of DIT on urban EE, incorporating mechanism analysis, heterogeneity, and spatial effects. DIT is measured using the entropy-weight method, and urban EE is calculated based on the super-efficiency slack-based measure (Super-SBM) model. A two-way fixed effects framework, combined with mediation, moderation, and spatial econometric models, is employed for empirical analysis. The results show that DIT significantly improves urban EE, and this finding remains robust after multiple robustness checks and endogeneity treatments. The effect operates mainly through innovation-driven development and industrial structure upgrading, while human capital and fiscal transparency further strengthen this relationship. Significant heterogeneity is observed across regions, industrial structures, and environmental regulation levels, with stronger effects in northeastern and western regions, in cities with lower industrial dependence, and in areas with weaker environmental regulation. In addition, DIT generates positive spatial spillover effects, while also being associated with a potential widening of regional disparities. This study integrates DIT and urban EE into a unified analytical framework, providing new empirical evidence on their mechanisms and spatial dynamics, and offering useful implications for policy design.
