Utilizing data from Chinese A-share listed companies, this study investigates the effects of digital transformation (DT) on total factor productivity (TFP) and the moderating function of ESG performance. The results indicate that DT boosts TFP, but ESG performance negatively moderates this effect, revealing the green paradox. A dynamic model of factor allocation efficiency shows that DT improves capital allocation by reducing financing constraints, information asymmetry, and enhancing operational capacity. However, ESG weakens the positive link between DT and operational capacity, thus diminishing its impact on TFP. Similarly, DT increases labor productivity, but ESG undermines this effect by weakening the link between DT and labor efficiency. The positive impact of DT is stronger when firms focus on ‘Practical Application Technologies’ rather than ‘Underlying Technologies’. This effect is especially evident in smaller, asset-intensive, non-state-owned firms, and those located in the Beijing-Tianjin-Hebei region. Additionally, ESG’s negative moderation is more pronounced where DT exerts a stronger positive influence. A notable distinction emerges: asset-intensive firms gain more from DT in terms of TFP, whereas ESG’s adverse effect is stronger in labour-intensive firms. This study offers a novel perspective on the interplay between DT, ESG performance, and productivity. It provides valuable insights for firms seeking to align digital strategies with ESG goals, thereby fostering technological innovation alongside sustainable development.

This paper investigates how institutional investors’ site visits affect firm productivity by using a dataset of China’s A-share listed firms. The findings reveal that site visits have a constructive effect on firm productivity. Moreover, mechanism analysis indicates that reducing information asymmetry and improving stock price informativeness are two channels through which site visits influence firm productivity. Heterogeneity analysis demonstrates that the nexus between site visits and firm productivity is more pronounced for non-state-owned firms and firms with intenser product market competition. Overall, this study brings new insights into the benefits of site visits and highlights the importance of investor activism.

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 paper examines how macroeconomic surprises affect corporate risk-taking in China. Using well-identified business cycle shocks to proxy the unexpected fluctuations of the Chinese aggregate economy, we find that the risk-taking level of publicly listed firms positively correlates with business cycle shocks in general. The underlying mechanism is the evolvement of firms’ financial constraints. However, this finding of full sample analysis is driven mainly by positive business cycle shocks, as the subsample analysis shows that firms also tend to increase risk-taking due to agency problems as adverse business cycle shocks get larger. Moreover, firm-level characteristics, such as managerial shareholdings, growth opportunities, and cash holdings, significantly affect the magnitude of corporate risk-taking’s response to business cycle shocks.

Enterprise digital transformation has become an inevitable trend in the digital economy era that can significantly impact enterprises. This paper takes the data of A-share listed companies from 2006 to 2022 as a sample to explore the effect of enterprise digital transformation on listed companies' corporate social responsibility and the mechanism of its role. It was found that corporate digital transformation can significantly enhance Csr(Corporate social responsibility), and enterprise digital transformation has a noticeable enabling effect on Csr, which can dramatically improve Csr. The relationship between the two still holds after the robustness test. It has been found that digital transformation can affect Csr by enhancing the green innovation capability of enterprises, the fairness of internal compensation distribution, and the sustainable development capability of enterprises. Heterogeneity analysis reveals that corporate digital transformation's impact on Csr fulfillment performance is more significant for non-state-owned firms and firms in the central and eastern regions. In addition, corporate financing constraints and government innovation subsidies influence Csr.

The corporate maturity mismatch is highly likely to trigger systemic financial risks, which is a realistic issue commonly faced by businesses. In the context of the intelligent era, the impact of artificial intelligence on maturity mismatch has emerged as a focal point of academic inquiry. Leveraging data from Chinese A-share companies over the 2011–2023 timeframe, this research employs a double machine learning approach to systematically examine the influence and underlying mechanisms of artificial intelligence on maturity mismatch. The findings reveal that artificial intelligence significantly exacerbates maturity mismatch. However, this effect is notably mitigated by government subsidies, media attention, and collectivist cultural. Further analysis indicates that in high-climate-risk scenarios, collectivist culture exerts a notably strong moderating influence. By contrast, government subsidies and media attention exhibit stronger moderating influences in low-climate-risk environments. This study constructs a multi-stakeholder collaborative governance framework, which helps to reveal the 'black box' between artificial intelligence and maturity mismatch, thereby offering a theoretical basis for monitoring maturity mismatch.

This paper extracts investor risk concern from the text of investormanagement communications and examines their impact on insider opportunistic sales. Utilizing data from listed companies holding online earnings communication conferences (OECCs) in China from 2007 to 2022, we find that heightened investor risk concern significantly curbs insider opportunistic sales, as manifested by reduced frequency and magnitude of such transactions. This governance effect of investor risk concern persists irrespective of motivation strength behind opportunistic sales. Further analysis reveals that the governance effect intensifies when investors exhibit superior information processing capabilities and when management’s risk statements better align with investor expectations. Notably, while mitigating opportunistic sales, elevated investor risk concern also significantly decreases the firm’s cost of equity capital. Our findings underscore the importance of fostering transparent and engaging investor-management communication in promoting effective corporate governance and mitigating insider misconduct.

The impact of Artificial Intelligence (AI) on firm performance is an emerging issue in both practice and research. However, discussions surrounding the effect of AI on productivity are enshrouded in a paradoxical quandary. This study examines the relationship between AI implementation and total factor productivity (TFP), considering the moderation effects of digital infrastructure quality, business diversification, and demand uncertainty. Using data from 2155 Chinese firms over 2016-2021, our empirical analysis reveals a nuanced pattern: while moderate AI implementation achieves the best TFP, excessive and insufficient implementation yields diminishing returns. The curvature of this inverted U-shaped relationship flattens with higher levels of digital infrastructure quality but steepens when firms undertake diversified businesses and face heightened demand uncertainty. The findings suggest that the impact of AI on TFP is not universally beneficial, and the relationship between AI and TFP varies across different contexts. These findings also provide implications on how firms can strategically implement AI to maximize its value.

China's SMIC and Taiwan's TSMC are caught on opposite sides of the "Global Chip War." TSMC, despite having extensive commercial ties and fabs in the Mainland, is a beneficiary of U.S. efforts to stifle competition from Mainland competitors like SMIC. Geopolitical considerations, therefore, are increasingly influencing TSMC’s business decisions, as shown by TSMC’s construction of fabs in Japan and the United States despite founder Morris Chang’s longstanding opposition to overseas fabs due to their high costs. SMIC, meanwhile, is the Mainland’s best hope for creating a “red chip supply chain” and achieving 70% semiconductor self-sufficiency via domestic suppliers, which has taken on even more importance due to U.S. sanctions on advanced chips for AI model development. This article analyzes SMIC founder Richard Chang’s dream of building a red chip giant on the Mainland that can rival or even replace TSMC, which will directly conflict with Chang's former co-worker and fellow Taiwanese Morris Chang’s dream of solidifying TSMC and Taiwan’s position as the irreplaceable center of the semiconductor industry well into the 21st century.

Trade credit is a vital external source of financing, playing a crucial role in redistributing credit from financially stronger firms to weaker ones, especially during difficult times. However, it is puzzling that the redistribution perspective alone fails to explain the changes in trade credit when firms get involved in major litigation, which can be seen as an external shock for firms. Based on a firm-level dataset of litigations from China, we find that firms involved in major litigation not only exhibit an increased demand for trade credit but also extend more credit to their customers. Our further analysis reveals that whether as plaintiffs or defendants, litigation firms experience an increase in the demand and supply of trade credit. Moreover, compared to plaintiff firms, defendant firms experience a more pronounced increase in the demand for trade credit. Using firms’ market power and liquidity as moderators, we find that the increase in the demand for trade credit is more likely due to firms’ deferred payments rather than voluntary provision by suppliers, and the increase in the supply of trade credit appears to be an expedient measure to maintain market share. Generally, our results provide evidence of credit contagion effect within the supply chain, where the increased demand for trade credit is transferred from firms’ customers to themselves when they get involved in major litigations, while the default risk is simultaneously transferred from litigation firms to upstream firms.