With the digital transformation of the capitalist economy, some contemporary scholars have put forward the Techno-Feudalism narrative of the digital economy. This narrative emphasizes that digital platform enterprises, as emerging market entities in the digital economy, have many practices that are highly similar to those of feudal lords. For example, digital platform enterprises plundering user data is similar to feudal lords plundering land; digital platform enterprises collecting digital rent is similar to feudal lords collecting land rent; digital platform enterprises controlling users and workers is similar to feudal lords controlling slaves. However, this narrative has many theoretical fallacies. Marx's theory of surplus value shows that the above phenomena are essentially still the contemporary form of capital seizing surplus value through technological innovation. The techno-feudalism narrative ignores the internal logic of capital using technological iteration to reconstruct the exploitation mechanism and falls into a superficial misjudgment. In contrast, the Chinese governance practice of digital economy breaks the monopoly of platforms on data elements through the innovation of the separation of three rights of data property rights; promotes fair competition and optimal allocation of resources in the digital economy by strengthening anti-monopoly supervision and promoting the construction of digital infrastructure; proves that the socialist system can break the capital proliferation cycle and achieve "people-centered" development by building a labor rights protection system to promote the creation and sharing of value and transcending the techno-feudalism phenomenon of the digital economy.

Following the 18th National Congress of the Communist Party of China, the central government elevated the construction of ecological civilization to a central position within national strategy and introduced environmental governance indicators as mandatory criteria for evaluating officials, alongside GDP. These indicators served as an additional "threshold" for performance assessments. In the context of changes in the central government's development ideology and policies, this study utilizes matched data on the turnover of municipal party secretaries and local enterprise carbon emissions from 293 prefecture-level cities in China between 1990 and 2021. The research finds that turnovers of municipal party secretaries after the 18th National Congress have led to a significant reduction in carbon emissions from local enterprises, a trend that was not evident prior to the congress. This effect is more pronounced in situations where official turnover is primarily driven by promotion incentives, and less influenced by collusive behavior between the government and enterprises. Further analysis reveals that the decline in carbon emissions is more significant for private enterprises, non-heavy polluting enterprises, those located in the eastern region, and those in general prefecture-level cities, before and after municipal party secretary turnovers. This study enhances understanding of the relationship between the promotion incentives of Chinese officials and the carbon emissions of local enterprises, offering valuable insights for improving the official promotion assessment system and advancing local carbon reduction efforts.

This study investigates the influence of smart supply chain management on the Environmental, Social, and Governance (ESG) performance of Chinese manufacturing firms spanning from 2009 to 2022. Our findings reveal a positive association between smart supply chain management and enhanced ESG performance, a relationship consistently upheld across various analytical methodologies. Additionally, we uncover that smart supply chain practices stimulate corporate social responsibility (CSR) disclosure, contributing to heightened transparency and subsequently bolstering ESG metrics within firms. Furthermore, our analysis demonstrates that the positive effect of smart supply chain management on ESG outcomes is particularly pronounced among firms that are operating in less competitive and more environmentally impactful industries, receiving heightened media scrutiny, and influenced by Confucian principles. This research provides actionable insights for firms seeking to advance their ESG initiatives.

We conducted a nationwide field experiment with 4,800+ Chinese-listed companies, randomly raising ESG concerns to their management teams via high-visibility and high-stakes online platforms. Tracking the full impact-generating process, we find that companies respond to our concerns by providing high-quality answers, publishing ESG reports, and making commitments to investors. Over time, Environmental (E) inquiries boost stock valuations, while Governance (G) concerns prompt skepticism. Productive and opaque firms are more likely to respond, consistent with a signaling model where costly ESG actions signal firm quality under information asymmetry. Overall, ESG actions are likely driven by profit-oriented signaling rather than values-based motives.

The growing significance of sustainable development has underscored the importance of integrating corporate sustainability indicators into corporate strategies. As external stakeholders increasingly emphasize corporate environmential performance, social responsibility and governance (ESG), understanding its impact on corporate value becomes essential, especially in emerging markets like China. This research aims to bridge these knowledge gaps by empirically investigating the influence of ESG ratings on firms’ value among Chinese listed firms, with a special emphasis on the mediating roles played by financial distress and financing constraints. By analyzing data from listed companies of China over the period 2018 to 2022, this research explores the correlation between firms’ value and ESG ratings. The findings indicate a positive association between firms’ value and ESG ratings. Enhanced ESG ratings directly boost market valuation and indirectly elevate firm value by mitigating financing constraints and financial distress. Further analysis reveals the positive effects of ESG ratings are more noticeable in industries that are not heavily polluting and in state-owned enterprises. This research provides valuable insights for enterprise management by systematically examining how ESG ratings contribute to corporate value through the mitigation of financial distress and constraints, while also highlighting the variations in ESG strategy implementation across different types of enterprises.

The role of institutional investors in the development of Environmental, Social, and Governance (ESG) criteria lacks consensus in the academic community. This study utilizes a quasi-natural experiment involving Chinese mutual funds that have signed the United Nations Principles for Responsible Investment (UNPRI) to investigate whether institutional Investors’ ESG investment commitments can significantly reduce ESG rating disagreement among the companies in their portfolios. We first find that companies held by ESG commitment institutional Investors exhibit less disagreement in ESG rating compared to those held by Non-ESG commitment institutional Investors. we then show that institutional Investor’ ESG investment commitment influence ESG rating disagreement by enhancing the quality of ESG disclosure and attracting external ESG attention. We further discover that institutional investors’ ESG investment commitments significantly mitigates the ESG rating disagreement among domestic ESG rating agencies and firms with a higher level of corporate governance.

How enterprises can leverage frontier technologies to achieve synergy between environmental governance and high-quality development has become a critical issue amid the deepening global push for sustainable development and the green economic transition. Based on micro-level data of Chinese enterprises from 2009 to 2023, this study systematically examines the impact of artificial intelligence (AI) on corporate green governance performance and explores the underlying mechanisms. The findings reveal that AI significantly enhances green governance performance at the enterprise level, and this effect remains robust after accounting for potential endogeneity. Mechanism analysis shows that AI empowers green transformation through a dual-path mechanism of “cognition–behavior,” by strengthening environmental tendency and increasing environmental investment. Further heterogeneity analysis indicates that the positive effects are more pronounced in nonheavy polluting industries and state-owned enterprises, suggesting that industry characteristics and ownership structure moderate the green governance impact of AI. This study contributes to the theoretical foundation of research at the intersection of digital technology and green governance, and provides empirical evidence and policy insights to support AI-driven green transformation in practice.

Under the goal of carbon peaking and carbon neutrality, taking environment, social responsibility, and corporate governance (ESG) as the important investment factor has become an action guide and standard for capital market participants. The practice of the ESG concept is not only a new way for enterprises to form new asset advantages and realize green and low-carbon transformation, but also important access for promoting high-quality and sustainable development. Based on Chinese-listed companies within the period of 2009 to 2015, we investigate the impact of ESG responsibility performance on export performance as well as its mechanism. We theorize and find out show that ESG responsibility performance can significantly and stably promote enterprises’ export performance. Mechanism analysis shows that ESG can improve export performance by reducing financing costs and easing financing constraints, and the green technology innovation effect is also an important channel for ESG to affect export performance. Therefore, government should strengthen the supervision and incentive of ESG performance, encourage enterprises to improve their environmental, social and governance performance in order to adapt to the goal of carbon peak and carbon neutrality and promote the high-quality development of export trade. Future research may consider combining ESG accountability with other factors such as supply chain management, intermediate imports, and transnational spillovers to more fully understand its impact on export performance, so as to create more value for society.

The growing emphasis on Environmental, Social, and Governance (ESG) principles, particularly in corporate sectors, shapes investment trends and operational strategies, whose shift is supported by the increasing role of media in monitoring and influencing corporate ESG performance, thereby driving the energy innovation. Therefore, based on reported events from Baidu News and patent text information of Chinese A-share listed companies from 2012 to 2022, this study innovatively applied machine learning and text analysis to measure ESG news sentiment and corporate energy innovation indicators. Combing with reputation, stakeholder, and agency theories, we find that a good reputation conveyed by positive ESG textual sentiments in the media significantly promotes corporate energy innovation, and the effect is mainly realized through alleviating financing constraints and agency problems and promoting green investment. Further analysis shows that ESG news sentiment promotes corporate energy innovation mainly among private firms, non-growth-stage firms, high-energy-consuming firms, and regions with better green finance development and higher ESG governance intensity. From the perspective of ESG news content and information content, greater ESG news attention can also exert an energy innovation incentive effect, in which the incentive effect exerted by positive media sentiment in the environmental (E) and social (S) dimensions, as well as excellent attention, is more robust. This study provides new insights for promoting green and low-carbon development and understanding the external governance role of media in corporate ESG development.

Environmental disclosure in emerging markets remains poorly understood, despite its critical role in sustainability governance. Here, we analyze 42,129 firm-year environmental disclosures from 4,571 Chinese listed firms (2008-2022) using machine learning techniques to characterize disclosure patterns and regulatory responses. We show that increased disclosure volume primarily comprises boilerplate content rather than material information. Cross-sectional analyses reveal systematic variations across industries, with manufacturing and high-pollution sectors exhibiting more comprehensive disclosures than consumer and technology sectors. Notably, regional rankings in environmental disclosure volume do not align with local economic development levels. Through examination of staggered regulatory implementation, we demonstrate that market-based mechanisms generate more substantive disclosures compared to command-and-control approaches. These results provide empirical evidence that firms strategically manage environmental disclosures in response to institutional pressures. Our findings have important implications for regulatory design in emerging markets and advance understanding of voluntary disclosure mechanisms in sustainability governance.