Purpose-This study empirically examines the relationship between the blockholder exit threats (ETs) and management tone manipulation, based on two competing hypotheses: the "governance hypothesis" and the "market pressure hypothesis." The study aims to explore the impact and mechanisms of ETs on the quality of textual information disclosure. Design/methodology/approach-This study uses ordinary least squares multivariate regressions on panel data from Chinese A-share listed companies spanning 2007 to 2022. Building on Huang et al. (2014), we construct a benchmark model of managerial tone and use its residuals to measure abnormal positive tone. Blockholder exit threat (ET), following Dou et al. (2018), is proxied by the interaction between stock liquidity and blockholder competition. To address endogeneity, we employ propensity score matching, the Heckman two-stage method and lagged models. Robustness checks include alternative variable definitions and different textual dictionaries. Findings-The results show that external blockholder ETs significantly increase the degree of abnormal positive managerial tone, thereby supporting the market pressure hypothesis. Further analyses reveal that the positive association between ETs and abnormal positive tone is stronger in subsamples where managerial market pressure is higher, the level of blockholder expropriation is greater and insider trading is more prevalentindicating a stronger collusion motive between external blockholders and management. Mechanism tests show that ETs manipulate managerial tone by increasing the sensitivity of managerial wealth to share price fluctuations. Research limitations/implications-This study is limited to Chinese A-share listed companies, whose unique institutional and regulatory environment may restrict the generalizability of the findings to other markets. Differences in disclosure rules, legal enforcement and investor protection between China and developed economies suggest that the identified mechanisms may not apply universally. Additionally, our reliance on annual report narratives for measuring managerial tone may overlook other communication channels. Future research could extend the analysis to other market segments or countries and incorporate additional data sources to test the robustness and broader applicability of our conclusions. Practical implications-The results highlight the need for enhanced regulatory oversight of narrative disclosures to prevent managerial “window dressing” and mitigate information asymmetry. Regulators should strengthen cross-validation between financial and non-financial information and promote mechanisms that increase the cost and risk of blockholder–management collusion. Investors are advised to critically assess managerial tone and remain alert to overly optimistic language. Additionally, increased supervision of tunneling and insider trading, along with stronger legal protections for minority shareholders, is essential for fostering transparency and integrity in China’s capital markets and improving overall market quality. Originality/value-This paper contributes to understanding the impact of external blockholder ETs on managerial tone manipulation in narrative disclosures from the perspective of ownership structure in China’s unique institutional environment. The findings of the study provide new insights into the governance role of blockholders and offer policy implications for improving information transparency and the healthy development of emerging capital markets.

Against a backdrop of economic transformation and industrial upgrading, financing constraints have become a significant barrier to the growth of microeconomic entities. Investor sentiment, a recognized source of irrationality in capital markets, is understood to influence the financing environment through various channels. Concurrently, advances in generative artificial intelligence (AI) are generating novel methods for the precise measurement of this sentiment. Leveraging data from Chinese A-share listed corporations from 2011 to 2023, this study constructs a double machine learning framework to examine the impact of investor sentiment on financing constraints and its underlying transmission mechanisms. Our findings indicate that elevated investor sentiment significantly reduces these constraints. This effect operates primarily through an enhanced capacity for debt financing, a reduction in market scrutiny, and a stimulation of consumer demand that boosts corporate revenue. Conversely, periods of subdued sentiment tend to trigger risk-averse behavior, intensify liquidity pressures, and further restrict access to capital. A heterogeneity analysis reveals that the effects of sentiment vary across industries, ownership structures, and regional levels of information infrastructure. The impact is particularly pronounced within the real estate sector and in more digitally advanced regions. Interestingly, the effect does not fundamentally differ across ownership types, suggesting a degree of market neutrality. In sum, this study offers fresh empirical evidence on the mechanisms through which sentiment drives financing behavior. It also expands the application of generative AI, demonstrating its value as a tool for financial research.

This study examines the role of artificial intelligence (AI) adoption in the market for corporate control using a sample of Chinese listed firms from 2011 to 2021. We construct a novel firm-level AI Index through textual analysis of annual reports and find that AI adoption significantly enhances both the likelihood of becoming an acquisition target and the valuation premiums commanded in M&A transactions. Specifically, a one-standard-deviation increase in the AI Index is associated with a significant increase in the probability of being acquired and higher deal premiums measured by price-to-earnings multiples. We identify two channels through which AI adoption creates value recognized by the M&A market: an efficiency channel, whereby AI reduces agency costs and improves profitability, and an innovation channel, evidenced by increased high-quality patent output. The persistence of these effects over time further suggests that AI adoption generates substantive improvements in firm fundamentals rather than serving as a transitory informational signal. Importantly, we document significant heterogeneity across ownership structures: the positive effects of AI adoption are substantially weaker for State-Owned Enterprises (SOEs) than for non-SOEs. Our findings contribute to the literature on digital transformation and corporate finance by demonstrating that AI adoption serves as a value-relevant firm attribute that shapes outcomes in the market for corporate control.

Firm survival, as a key indicator of regional economic resilience, has gained increasing attention in the context of global economic uncertainty and the deep adjustments in industrial structures. In the Pearl River Delta (PRD), a core region of China’s Guangdong-Hong Kong-Macau Greater Bay Area, the characteristics of firm life cycles are crucial for understanding spatial development inequalities and institutional effects in emerging economies. This study focuses on firms in the PRD, using full life-cycle data from registration, operation, to deregistration. An XGBoost regression model is employed, incorporating the SHAP explanation algorithm, to systematically analyze the main factors influencing firm survival. The results show that: (1) Firm establishment time is the primary factor influencing survival, with significant “survival threshold” and “growth leap” effects—mature firms exhibit a distinct survival advantage; (2) Among spatial structure variables, moderate industry specialization and diversity enhance firm survival rates, while excessive concentration and diversification show diminishing or negative returns, reflecting an “ecological threshold” effect; (3) External shocks have a significant suppressive impact on startups, while policy support and capital size show limited explanatory power; (4) The ownership structure, especially state-holding, has a positive moderating effect on firm survival in specific contexts, indicating that private enterprises’ flexibility and adaptability can compensate for institutional gaps. This study offers insights into the spatial heterogeneity of firm survival mechanisms, providing quantitative evidence for regional economic policy adjustments and firm resilience-building. Recommendations include promoting differentiated policies, optimizing industrial ecological spatial layouts, and piloting systems to enhance survival resilience, especially for mixed-ownership firms.

This paper investigates how foreign institutional investors, specifically Qualified Foreign Institutional Investors (QFIIs), influence the investment strategies of Chinese mutual fund management companies (FMCs) in which they hold shares. By analysing panel data from 1,766 mutual funds managed by 44 foreign-invested FMCs in China between 2005 and 2021, we explore whether QFII-invested FMCs (Q-FMCs) learn more from their domestic counterparts (D-FMCs) than other foreign-invested FMCs (NQ-FMCs). Our findings show that Q-FMC-managed mutual funds exhibit portfolio allocations more closely aligned with local DFMCs than those managed by NQ-FMCs. This imitation is particularly pronounced when selecting new stocks, enhancing portfolio performance, but not when rebalancing existing positions. Additionally, Q-FMCs trade more actively than NQ-FMCs. Robustness checks confirm these results across various ownership structures, fund characteristics, market conditions, and regulatory changes. These findings highlight the dual role of QFIIs as both investors and learners in China’s evolving financial landscape, offering insights into how foreign capital integrates into emerging mutual fund markets, informing regulatory policy aimed at fostering cross-border financial development.

This paper examines how economic policy uncertainty (EPU) affects mergers and acquisitions (M&As) between companies with different levels of financing constraints. Existing literature overlooks the interactive effect of EPU and financing constraints on M&As, and empirical evidence regarding EPU's influence on financially constrained firms remains limited. China's unique ownership structure provides a valuable context for this analysis, as state-owned enterprises (SOEs) face fewer financing constraints than private firms. Using a 2007-2021 sample of Chinese listed state-owned enterprises (SOEs) and private companies, we find that high EPU decreases the likelihood of private firms acquiring SOEs, while increases the likelihood of private firms being acquired by SOEs. These results suggest that under high EPU, financially constrained firms experience greater survival pressure, limiting their capacity to alleviate constraints by acquiring less-constrained targets. Conversely, less-constrained firms enhance their bargaining power and are more likely to acquire financially stressed counterparts. EPU facilitates control transfers from high-constraint to low-constraint firms, contributing to long-term market returns and improving financial market allocation efficiency. Our study contributes to the literature by shedding light on how EPU shapes divergent M&A behaviors based on firms’ financing constraints.

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.

When examining corporate governance in China, it is crucial to recognize the unique socio-economic structures and legal systems at play. The mechanisms of corporate governance theorized in the West might not necessarily have the same impact in China. In particular, given China’s distinct feature of the domestic economy and its socio-political structure, the results of introducing a hostile takeover system might not align with common anticipations that scholars and policymakers in China and elsewhere broadly share. In greater detail, this paper highlights the significant market imperfections in the Chinese economy, stemming from information asymmetry, imperfect product markets, and capital-market inefficiency. These market imperfections suggest that an active hostile takeover regime might not function effectively in China, as its disciplinary mechanism operates successfully in other advanced countries. Additionally, this paper underscores that due to China’s distinctive features—including its state-owned corporate landscape, the dominance of controlling shareholders in private corporations’ ownership structures, and its unique brand of socialism—the introduction of an active takeover regime could produce unintended consequences in the Chinese economy. Overall, challenging the prevailing perspective, I posit that within the Chinese hostile takeover framework, corporate governance is not as influential as one might assume.

Despite nearly twenty years of privatization, mixed-ownership reform has been the mainstay of SOE reform in China in recent years. This raises the question of whether the financial performance of mixed-ownership firms (Mixed firms) is better than private-owned enterprises (POEs). Although Mixed firms suffer more from government intervention, unclear property rights, and interest conflicts between state shareholders and private shareholders, they can also benefit from the external resources controlled by the state. Therefore, the performance of Mixed firms is still unclear. Collecting data from the Chinese A-share listed market, we divide the firms into POEs, Mixed firms controlled by the state (MixedSOEs), and Mixed firms controlled by the private sectors (MixedPOEs). Measuring profitability using ROA and ROE, we find that on average, POEs perform better than Mixed firms, and MixedPOEs have a higher profitability than MixedSOEs. Within Mixed firms, more state shares are related to lower profitability, and more private shares are related to higher profitability. Using the NBS survey data, we further find that on average, SOEs exhibit the lowest profitability, with MixedSOEs and MixedPOEs in the middle, and POEs have the highest profitability. We try to address the endogeneity challenge in several ways and get similar results. Overall, our analysis provides new evidence on the financial performance of mixed-ownership firms.

The relationship between corporate Environmental, Social, and Governance (ESG) performance and its value has garnered increasing attention in recent times. However, the utilization of ESG scores by rating agencies, a critical intermediary in the linkage between ESG performance and value, presents challenges to ESG research and investment as a result of inherent subjectivity, hysteresis, and discrepant coverage. Fortunately, news can provide an objective, timely, and socially relevant perspective to augment prevailing rating frameworks and alleviate their shortcomings. This study endeavors to scrutinize the influence of ESG-related news on the Chinese stock market, to showcase its efficacy in supplementing the appraisal of ESG performance. The study's findings demonstrate that (1) the stock market is significantly impacted by ESGrelated news; (2) ESG-related news with different attributes (sentiments and sources) have notably diverse effects on the stock market; and (3) the heterogeneity among enterprises (industries and ownership structures) affects their ability to withstand ESGrelated news shocks. This study contributes novel insights to the comprehensive and objective assessment of corporate ESG performance and the management of its media image by providing a vantage point on ESG-related news.