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.

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.

It has been widely recognized that firms’ environmental, social, and governance (ESG) performances are crucial for shaping their information environments. Nonetheless, the impact of ESG performances on important analyst report attributes still remains clear. Our study reveals that superior firm. ESG performances significantly enhance the analyst report readability. The mechanism analysis demonstrates that this effect is primarily driven by increased information accessibility (the information acquisition channel) and greater analysts’ research efforts (the analyst effort channel). As expected, this effect is more pronounced in firms operating in highly polluted industries, firms with opaque financial infomration and state-owned enterprises (SOEs). Finally, our findings reveal that the release of analyst reports triggers higher market reactions for firms with superior ESG performances. In overall, our study highlights the criticial role of firm ESG performances in boosting financial analysts’ information production process.

This study examines how full-time external supervisors affect corporate irregularities using listed Chinese state-owned enterprises (SOEs) as a research sample. We find that full-time external supervisors restrain corporate irregularities. This outcome continues to hold after accounting for potential endogeneity concerns. Further mediating effect analysis shows that full-time external supervisors mitigate corporate irregularities by curbing managers' opportunistic behavior. Additionally, the heterogeneity analysis demonstrates that the impact of full-time external supervisors on corporate irregularities varies significantly across different types of SOEs and internal control environments. Overall, this paper enriches and expands the literature on the effectiveness of full-time external supervisors in emerging economies and provides new insights for dealing with corporate irregularities.

This paper aims to clarify the relationship between key audit matters (KAMs) disclosure and corporate financialization. The findings reveal that key audit matters (KAMs) disclosure can provide incremental information value, thereby impeding corporate financialization in China. Moreover, this effect is more pronounced in the samples with low media attention, low shareholding of institutional investors, and non-state-owned enterprises. Further research indicates that reducing managerial myopia and easing financing constraints serve as key channels through which key audit matters (KAMs) disclosure affects corporate financialization. This study provides empirical evidence on efficiently preventing excessive financialization of enterprises, as well as some insights for mitigating systemic financial risks from the key audit matters (KAMs) disclosure perspective.

This study examines how housing purchase restrictions (HPRs) affect firms' robotics adoption through labor cost increases. Exploiting policy-driven housing price shocks across Chinese cities, we find firms significantly accelerate robot adoption in response to higher labor costs. Effects are pronounced among financially unconstrained firms, state-owned enterprises, and firms with skilled or educated workforces. Automation investments subsequently improve firm productivity, profitability, and market positions. Our findings highlight unintended spillovers from housing regulations to firm-level technological decisions and suggest policymakers consider these indirect effects when designing local market interventions.

This paper analyzes the impact of risk disclosures in bond prospectuses on the credit risk premium in the Chinese corporate bond market through six textual characteristics comprehensively. In the empirical analysis, the collected 5199 bond prospectuses and structured data concerning control variables from 2006 to 2021 are used to perform the fixed effect regression analysis. The results show that fewer Words, less Boilerplate, higher Fog Index, more HardInfoMix, more Redundancy, and higher Specificity of risk disclosures in bond prospectuses will lead to a higher credit risk premium. Further tests demonstrate that ceteris paribus, the negative impact of Words and Boilerplate will be strengthened by implicit government guarantees carried by a state-owned enterprise but be weakened by better corporate business performance. However, ceteris paribus, positive effects of the Fog Index, HardInfoMix, Redundancy, and Specificity will be weakened when the bond issuer is state-owned but be strengthened by better corporate business performance.

We use a sample of China’s listed firms and employ a naïve Bayesian machine learning algorithm to reveal that environmental information intangibility superficially promotes green innovation. We demonstrate that this effect is channelled through the acquisition of institutional resources, including bank loans and government subsidies. The impact of environmental information intangibility on green innovation is most pronounced within state-owned enterprises, large firms, and politically connected firms. Furthermore, we confirm that environmental information intangibility does not lead to improvements in innovation efficiency or quality. This implies that green innovation may serve as a symbolic environmental activity. Our findings contribute to the understanding of the consequences of environmental information intangibility, greenwashing behaviour, and their relationship to green innovation.

This study analyzes the network structures of institutional shareholders and examines the influence of institutional investor cliques on corporate innovation. Our empirical results reveal that institutional investor cliques significantly enhance both innovation input and output. To mitigate endogeneity concerns and establish causality, we adopt multiple empirical strategies. Further evidence suggests that the beneficial impact of institutional investor cliques on firm innovation can be attributed to increased innovation investment efficiency, enhanced employee productivity, reduced information asymmetry, and decreased managerial myopia. Additionally, we find that the positive effect of institutional investor cliques on firm innovation is more pronounced in non-state-owned enterprises and is particularly evident in firms with severe agency conflicts, CEO duality issues, highly competitive product markets, and for firms that have low stock liquidity.

We empirically investigate the impact of state ownership on the private economic value and the scientific value of Chinese publicly listed firms’ innovation from 2003 to 2020, and explore its mechanism. We show that the stock-market-based methodology of estimating patent value proposed by Kogan et al. (2017) applies to the Chinese economy, and follow their approach to evaluate patents issued to Chinese listed firms. Using this new data and patent citation data, we find that state-owned enterprises have lower private value of innovation than non-state-owned enterprises, while their scientific values of innovation are not significantly different. We also provide evidence that the state-owned enterprises’ low profit-oriented R&D performance is due to their insufficient capabilities rather than ownership-specific corporate objectives.