Technological innovation and high-quality economic development are inevitable requirements of sustainable development, and the digital economy has gradually become a new engine to enhance technological innovation and the high-quality development of China’s economy. Deeply discussing the effect of digital economy on high-quality economic development and clarifying the mechanism behind it can effectively grant the boosting power of digital economy to China’s high-quality development, which is of great practical significance to China’s sustainable economic development. In this study, the mechanism, effect, and regional heterogeneity of the impact of the digital economy on the level of high-quality economic development in 30 Chinese provinces from 2011–2019 were measured and empirically tested using a mediating effects model and a spatial Durbin model, among others. The results showed that the overall level of digital economy and high-quality development is not high, and there were both high agglomeration and low agglomeration, with obvious spatial path dependence and spatial lock-in. Digital economy could promote the high-quality development level of the economy, and the spatial spillover effect was remarkable. In addition, the function of digital economy in promoting high-quality economic development in the eastern, central, and western regions was gradually weakened. Besides, the technological innovation was an important transmission path of digital economy to high-quality economic development. Based on these findings, it is proposed that decision-makers should strengthen digitalization efforts so that the digital economy can become a powerful tool to narrow the digital divide. Further, the dynamic and differentiated digital economy development strategy should be implemented to reduce regional development imbalances in an effective manner.

Technological innovation is an important driving force for a country’s sustainable economic development and social progress, and can be achieved through R&D investment, which would lead to sustainable economic growth. This process is one of the important steps for China to realize the transformation of the economic growth mode and the development from extensive to intensive type. Since R&D investment, technological innovation, and economic growth are mutually influential and inseparable, it is particularly important to understand the interrelationship between the three. By collating data from China from 1995 to 2016, this paper established an indicator system of R&D investment, technological innovation, and economic growth as research variables. Vector autoregression model, impulse response function, and variance decomposition function were adopted. A long-term stable dynamic interrelationship among the three was revealed. The empirical analysis showed that in recent years, the growth of R&D investment, technological innovation, and economic growth stagnated or even slowly declined, which indicated that the economic development had insufficient stamina. The conversion efficiency of R&D investment was not high, and R&D investment for short-term profit was ubiquitous. The innovation ability of scientific and technological achievements was not strong, the conversion rate of scientific and technological achievements was not high, and the market integration process was relatively slow. Overall, a good circular mechanism has not been established among R&D investment, technological innovation, and economic growth. Based on this, China should improve the mutual influence and interrelationship among R&D investment, technological innovation, and economic growth. The transmission mechanism among the three should be optimized and stable economic growth promoted, for example, by increasing R&D investment, enhancing the efficiency of R&D funds, improving the incentive system for scientific and technological innovation, and promting the effective use and marketization integration of innovation achievements.

China is currently in a strategic opportunity period for green and high-quality development, and developing the digital economy is an important choice to achieve environmental pollution control, improve regional ecological efficiency, and enhance social welfare. In this context, the impact of the digital economy on ecological well-being performance and the role of environmental regulation need to be examined. In this study, the super-efficiency SBM-DEA model was used to measure the level of ecological well-being performance in 30 provinces of China from 2011 to 2019. On this basis, the mediating effect model and spatial Durbin model were adopted to explore the transmission mechanism and regional heterogeneity of the impact of the digital economy on ecological well-being performance. The empirical results show that the digital economy significantly contributes to regional ecological well-being performance in China, and there is significant spatial spillover as well. Moreover, the findings still hold under robustness tests. The results also show that environmental regulation is an important transmission path for the digital economy to enhance regional ecological well-being performance, and the impact of environmental regulation on ecological well-being performance varies by region; specifically, the impact in eastern China is positive but not significant. However, the digital economy plays a significant positive role in promoting ecological well-being performance in the central and western regions, and is more obvious in the central region. Finally, suggestions are put forward to enhance the role of the digital economy in regional ecological well-being performance, which is of great significance for promoting green economic growth and high-quality development.

As global urbanization accelerates amidst compounding risks, comprehensive urban resilience assessment has emerged as a pivotal issue in optimizing risk governance pathways. Grounded in the Pressure–State–Response (PSR) theoretical framework, this study constructs a multidimensional evaluation system for comprehensive urban resilience. Through the integration of a combined weighting method and the TOPSIS model, we systematically measure resilience levels across 13 prefecture-level cities in Jiangsu Province, with the obstacle degree model employed to identify critical resilience constraints. The findings reveal significant spatial heterogeneity in regional resilience patterns. High-resilience cities establish positive feedback mechanisms through economic foundations, innovation-driven strategies, and institutional coordination. Conversely, low-resilience cities face multidimensional constraints, including industrial structure imbalance, inadequate social security systems, and infrastructure deficiencies. The resilience disparity stems from the coupling effects of systemic multidimensional elements, with three core obstacles identified: energy consumption and population pressure in the Pressure dimension, medical resource scarcity and innovation deficit in the State dimension, and fiscal expenditure inefficiency in the Response dimension. The study proposes strategic interventions, including fiscal structure optimization, cross-regional resource coordination enhancement, and innovation–translation mechanism improvement, to facilitate urban systems’ transformation from passive resistance to proactive adaptation. This research provides novel perspectives for analyzing complex system resilience evolution and offers scientific grounds for urban agglomeration risk prevention and sustainable development.

Regional carbon efficiency (CE) improvement is critical to China’s “taking concerted efforts to achieve ecological protection” strategy in the Yangtze River Economic Belt (YREB) and their program to build a leading demonstration belt for ecological civilization. This study applied the super efficiency slacks-based measure to calculate the regional differences and evolution characteristics of the YREB’s CE from the year of 2006 to 2017. It also constructed a coupling evaluation model to empirically analyze the interactions between CE and technology absorptive capacity (TAC). The results showed that (1) the CE for all YREB provinces followed a “U-shaped” trend. TAC generally increased and incrementally decreased in the sequence of the upper stream, middle stream, and downstream. The gap among the downstream, upper stream, and middle stream increased; (2) coupling between the CE and TAC for the YREB provinces can be characterized as a relatively stable medium to low coupling degree and medium-to-high coordination degree. To improve coupling and achieve balanced, sustainable development in the YREB, this study proposes several measures, including promoting balanced, high-quality economic development, building the YREB talent pool, appropriately guiding foreign capital flows, implementing the strategy of driving economic development through innovation, and launching the network for coordinated technological innovation in YREB.

Improving green innovation efficiency (GIE) is crucial for reducing enterprise carbon emissions and fostering enterprise sustainability. Meanwhile. most of the research has not considered the micro-level influence of carbon trading on GIE. Therefore, the research objective of this paper is to assess the impact of carbon trading policy (CTP) on the GIE of enterprises and its specific mechanism. This paper uses data from China’s listed enterprises from 2010 to 2019 and treats the 2013 CTP in seven regions as a quasi-natural experiment. The Super-SBM model is applied to calculate the GIE. The difference-in-difference-in-differences (DDD) method assesses policy impact by comparing pre- and post-policy efficiencies. The results reveal that CTP improves the GIE of enterprises in high-carbon emission sectors in pilot areas. It primarily boosts GIE by increasing the environmental attention and resource allocation efficiency of enterprises. CTP significantly promotes the GIE of non-state-owned enterprises (non-SOEs), large-scale enterprises, and enterprises in regions with strict environmental regulations. Finally, policy recommendations are made for more environmentally friendly and sustainable enterprise development.