This paper investigates the role of the digital economy in reducing carbon emissions, with a particular focus on the moderating and threshold effects of green finance. An analysis of data from 30 Chinese provinces shows that the digital economy significantly reduces carbon emission intensity by restructuring energy consumption and promoting green technological innovation. Green finance plays a crucial moderating role by alleviating financial barriers to digital transformation and supporting the implementation of emission-reducing technologies. The study reveals a nonlinear relationship, with green finance exhibiting a “strong initial, weak subsequent” threshold effect. At the same time, the digital economy’s impact on carbon reduction strengthens over time as technological development progresses. These findings contribute to understanding how digitalisation and green finance can work synergistically to drive sustainable low-carbon development.

The deep integration of intelligent technology and the manufacturing industry is a crucial driving force for promoting green and low-carbon development, which is a key strategy for achieving sustainable development. Using panel data from 30 provinces in mainland China from 2010 to 2022, this study measures the level of intelligent development and the total factor carbon emission performance (TFCEP). Additionally, a mediating effect model is constructed to explore the impact of intelligent manufacturing (IM) on carbon emission performance (CEP) and its underlying mechanisms. The findings reveal that (1) the intellectualization of the manufacturing industry significantly enhances CEP, a conclusion that remains robust under various tests; (2) the impact of IM on CEP varies by regional geographical locations, the degree of economic agglomeration (EA), and whether the province is a low-carbon pilot area; and (3) the mechanism analysis indicates that IM improves CEP by promoting EA. Given that China is the world’s largest manufacturing country and the largest carbon emitter, analyzing the impact of its IM on CEP provides valuable theoretical insights and practical experiences for China and other manufacturing countries aiming to achieve a win–win situation of sustainable economic development and environmental improvement.

Purpose: This study aims to explore the behavioral drivers of stock performance in the low-altitude economy sector, a strategic emerging industry in China. Design/methodology/approach: This study analyzes market data from 70 low-altitude economy companies using a two-way fixed effects model, incorporating investor attention measured by Baidu search index and market sentiment measured by emotions extracted from forum posts to assess their combined impact on stock performance. Findings: Empirical research indicates that increased investor attention is significantly associated with higher stock returns and greater return volatility. Market sentiment has an asymmetric effect on stock valuation, with positive sentiment leading to stronger upward movements in stock prices compared to the downward pressure from negative sentiment. Additionally, quantile regression reveals that the influence of investor attention varies across different levels of stock returns, with medium to high-yield stocks being more positively impacted. Robustness checks and heterogeneity analyses confirm the reliability of the findings. Practical implications: The findings provide valuable implications for investors and policymakers. Investors can use insights from investor attention and market sentiment to better predict stock returns and volatility. Policymakers can leverage these findings to develop strategies for fostering investor confidence and optimizing market dynamics in the low-altitude economy sector. Originality/value: This study contributes to the understanding of stock price formation in the emerging low-altitude economy sector, an area that has not been extensively explored. It offers insights into how behavioral factors, specifically investor attention and market sentiment, drive stock performance in this rapidly growing industry.

The reconfiguration of global value chains has raised concerns about the resilience and upgrading of manufacturing supply chains. This study examines whether digital infrastructure improves manufacturing supply chain capabilities, using the 2016 “Information for the People” pilot city program as a quasi-natural experiment. Based on panel data from Chinese prefecture-level cities from 2006 to 2023, a difference-in-differences model is employed to identify the causal effect. The results show that digital infrastructure significantly enhances manufacturing supply chain capabilities, and this finding remains robust after multiple tests. Heterogeneity analysis indicates that the effect differs across China’s eight economic regions and strengthens with longer policy implementation, showing regional and cumulative characteristics. Mechanism analysis suggests that innovation-oriented talent inflow is an important transmission channel. Further analysis shows that financial development positively moderates the impact of digital infrastructure by improving cities’ capacity to absorb and allocate digital and innovation resources. These findings suggest that policymakers should shift from uniform digital infrastructure investment to region-specific strategies that integrate talent attraction, financial support, and supply chain modernization.

Faced with industrial transformation and environmental constraints, exploring the synergistic transition towards digitalisation and greening in manufacturing is of great significance. Using panel data from 30 Chinese provinces (2011–2023), this paper employs the modified distance synergy model, XGBoost, and PVAR to measure the synergistic transition level, identify key characteristics, and reveal regional heterogeneity. The findings show that: (1) The synergistic level has risen steadily, forming a pattern of “East leading, Central catching up, West stable, Northeast slowing”. (2) Digital content resources, internet address resources, the share of high-tech new product revenue, and environmental protection expenditure are key characteristics. (3) Regional heterogeneity is evident: the Northeast exhibits bidirectional synergy; the East and West show short-term digitalisation promoting greening and long-term greening driving digitalisation; the Central region shows short-term suppression of digitalisation by greening, with no significant reverse effect. These findings provide empirical evidence for advancing digital-green synergy and regional high-quality development.