As global climate change intensifies and the Paris Agreement advances low-carbon transformation, frequent local policy adjustments under China’s dual carbon goals have made climate-policy uncertainty a core challenge for corporate sustainability. Environmental, social, and governance (ESG) performance has grown exponentially in international capital markets, evolving from a peripheral concept to a key investment decision-making dimension. This study uses China’s carbon peaking and neutrality policies as a quasinatural experiment, applying the difference-in-differences (DID) method to the panel data of Chinese A-share listed companies (2014–2023). Taking high-energy-consuming enterprises as the treatment group, this study identifies net policy effects via the interaction of policy and time dummy variables. The results show that carbon peaking and neutrality policies significantly suppress the ESG performance of energy-intensive firms; mediating effect tests confirm that the policy harms ESG performance by increasing uncertainty. Implications include enhancing policy transparency and predictability and optimizing resource allocation to strengthen ESG resilience. Future research should focus on micro-level policy indicators and long-term effect tracking to provide theoretical and practical support for synergizing dual carbon goals with high-quality economic development.

With the global climate governance development, climate policy uncertainty has shifted as one of the most important institutional factors influencing corporate sustainability. However, existing studies have shown mixed evidence regarding the effects of governance and have paid little attention to the boundary conditions that climate policy uncertainty shapes corporate sustainability. The relationship between climate policy uncertainty and corporate sustainability performance will be investigated in this study using a sample of Chinese A-share listed firms from 2016 to 2025, which is proxy measured through ESG (environmental, social, and governance) performance scores. We utilized a two-way fixed-effects model, including various robustness, endogeneity, and heterogeneity tests. The empirical findings suggest that the uncertainty of climate policies boosts corporate sustainability. Moreover, this positive impact is particularly significant for enterprises situated in southern China, firms engaged in sectors benefitting from industrial policy support and large enterprises. According to this finding, climate policy uncertainty’s governance impact is predicated on the interaction of external institutional settings and firms’ organizational features. By offering a more comprehensive clarification of how climate policy uncertainty affects governance, this study contributes to the literature on corporate sustainability and climate policy uncertainty and advances our knowledge of firms’ sustainability responses in the context of policy uncertainty.

Digital technology innovation is a core driver of sustainable industrial development. However, our understanding of its underlying transmission mechanisms and complex effects remains limited. Based on panel data from 256 prefecture-level cities in China from 2007 to 2023, this study systematically examines the direct effects, mediating mechanisms, and heterogeneity of digital technology innovation on sustainable development performance. Our findings show that digital technology innovation has a significant enabling effect on sustainable development performance, a conclusion that holds even after a series of robustness and endogeneity tests. Mechanism analysis suggests that the impact of digital technology innovation on sustainable industrial development may be linked to digital sharing and Industrial synergy: the former may facilitate the circulation of data as a factor of production and the optimal allocation of resources, whilst the latter may help to generate structural dividends. Together, these two channels may form a potential endogenous mechanism through which digital technology innovation advances sustainable industrial development. The empirical findings outlined above provide evidence consistent with the proposed mediating mechanisms. Furthermore, heterogeneity analysis reveals that the impact of digital technology innovation on industrial sustainability performance significantly differs within the “core-periphery” structure; its enabling effect is more pronounced in regions with robust industrial foundations and abundant technological endowments, whereas no significant heterogeneity emerges with respect to geographic location and public data platforms. This study provides new theoretical perspectives and empirical evidence for a deeper understanding of the relationship between digital technology and sustainability.

This study explores the impact of industrial intelligent transformation on industrial carbon emission efficiency and its spatial spillover effect, which is closely related to industrial sustainability. Based on panel data of 284 cities in China from 2011 to 2023, we find that intelligent transformation significantly improves urban industrial carbon emission efficiency, and reducing energy consumption intensity and promoting green technological innovation are two critical mediating channels. Moreover, both marketization level and environmental regulation stringency strengthen the promoting role of intelligent transformation on industrial carbon emission efficiency. Heterogeneity analysis demonstrates that the promotional effect of intelligent transformation on industrial carbon emission efficiency is strongest in Eastern China, followed by Central China, and weakest in Western China. In addition, this effect is significant in non-resource-based cities but insignificant in resource-based cities. Furthermore, intelligent transformation exerts a negative “competitive spillover effect” on industrial carbon emission efficiency of geographically adjacent cities, while generating a positive “demonstration spillover effect” on cities with similar economic development levels.

Corporate resilience has become a critical capability for firms to cope with increasing environmental uncertainties and external shocks. Against the backdrop of the rapid development of the digital economy, this study examines whether digital transformation enhances corporate resilience and further investigates whether environmental, social, and governance (ESG) performance serves as a complementary transmission mechanism in this relationship. Drawing on resource orchestration theory, this study uses panel data of Chinese A-share listed companies from 2016 to 2024 and estimates a series of firm fixed-effects models. The results indicate that digital transformation significantly enhances corporate resilience, and the findings remain robust after a series of robustness checks and endogeneity tests are conducted. Further analysis reveals that ESG performance partially mediates the relationship between digital transformation and corporate resilience, suggesting that responsible business practices complement the resilience-enhancing effect of digital transformation. The results of the heterogeneity analysis further indicate that the positive effect of digital transformation is significantly stronger for high-tech firms. In addition, firms exhibit substantial variation in the consistency between digital transformation communication and actual digital investment. Further analysis suggests that greater alignment between digital transformation communication and substantive implementation is associated with stronger resilience outcomes, providing supplementary evidence on the implementation process of digital transformation. This study contributes to the literature on digital transformation and corporate resilience by revealing the resource orchestration process through which digital transformation creates organizational value and identifying ESG performance as a complementary transmission mechanism. The findings also have practical implications for firms seeking to strengthen their resilience and achieve sustainable development in an increasingly uncertain environment.