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.

Against the backdrop of global green development and China’s sustainable economic transition, many firms exaggerate green-transition disclosures to cater to national strategies and capital market preferences, leading to a severe "Say–Do Gap". Based on signaling theory, this study uses the phased establishment of environmental courts in 208 prefecture-level cities as a quasi-natural experiment, adopting a staggered DID design with 2007–2023 panel data of Chinese A-share listed firms for empirical tests. Results show widespread corporate green pandering, with improved disclosure not translating into actual carbon reduction. Environmental courts effectively curb this behavior, with environmental litigation risk as the core mediating channel. Heterogeneity tests reveal stronger deterrence in regions with weaker regulation/heavier pollution and polluting firms with stronger environmental technology. This study enriches literature from a judicial deterrence perspective and provides implications for substantive corporate green transition.

Breaking away from being “large but not strong” and accelerating the internal “dual circulation” reform to integrate the manufacturing and service industries is a daunting challenge. This study examines how environmental regulations and financial instruments can simultaneously drive servitization evolution and green transformation. Utilizing the Green Credit Guidelines (GCG) policy rollout by China in 2012 as a quasi-natural experiment, we analyze 2007-2021 data from A-share listed manufacturing corporations through DID model to evaluate the policy ramifications and investigate servitization direction. The results show that: (1) While GCG generally promotes overall servitization, it biases firms toward traditional rather than modern servitization pathways. (2) Contrary to typical innovation compensation effects, GCG induces short-sight in managerial decisions, favoring quick wins over innovation-driven progress. These results highlight why firms have tended to advance traditional servitization while constraining modern servitization efforts. (3) Heterogeneity analysis shows stronger policy impacts in firms with domestically-oriented executives and domestic ownership, where both overall and traditional servitization are significantly enhanced.

This study challenges democratic citizenship theory by examining altruistic behaviour in authoritarian China. We find that financial resources influence prosocial engagement primarily through psychological mediators such as long-term planning and self-discovery, rather than directly providing material means for participation. Communist Party membership shapes specific domestic ideological orientations, but not attitudes toward market regulation or income equality, while cultural tradition emerges as a stronger predictor of certain political attitudes than party affiliation. Cluster analysis identifies three distinct citizen profiles: (1) future-oriented altruists; (2) status-driven contributors; and, (3) short-termpragmatists, revealing motivational heterogeneity within authoritarian publics. These findings suggest that authoritarian citizenship operates through psychological mediation and plural motivational pathways fundamentally different from democratic societies, with potential applicability to other single-party regimes where states actively structure prosocial behaviour. The study contributes to comparative authoritarianism literature by theorizing how regime type moderates the relationship between socio-economic resources, political identity, and civic engagement.

With the rapid development of the global shipping industry, maritime traffic continues to grow, and maritime traffic risks are becoming increasingly prominent, posing serious threats to economic development, the ecological environment, and public safety. In this context, this study develops an environmental data-driven dynamic Bayesian network (DBN) model to simulate the dynamic evolution process of maritime traffic risks from the massive data of complex shipping systems. Firstly, based on the systems theoretic accident model and processes (STAMP) accident causation analysis framework, risk influencing factors (RIFs) are identified through the analysis of maritime accident report systems. Secondly, addressing the dynamic nature of maritime risks, a novel transition probability matrix (TPM) learning mechanism integrating environmental data is proposed, constructing a DBN model capable of characterizing temporal risk performance. Finally, a case study of typical routes along the Chinese coast reveals that risk performance evolution exhibits significant spatiotemporal heterogeneity across sea areas, with the East Sea and South China Sea regions being the most prominent. Their fluctuations are highly correlated with seasonal meteorological and hydrological changes, and the distribution of accident risks is also closely associated with extreme weather events such as typhoons. Sensitivity analysis validates the model's reliability. This study provides a quantitative tool for the dynamic risk management of intelligent shipping systems and offers policy insights for intelligent maritime transportation safety regulation.

The COVID-19 pandemic has reshaped regional economic landscapes. However, academic research has not yet sufficiently addressed how external investment in regions has been transformed under the impact of the COVID-19 pandemic and its influence on industrial evolution patterns. In this paper, we integrate insights from economic geography literature and develop a conceptual framework to further theorise the relationship between external shocks, changes in the industrial heterogeneity of investment from regional core cities, and local industrial dynamics. Using the COVID-19 pandemic and the Yangtze River Delta region as a case study, we employ an intensity-based Difference-in-Differences (DID) approach and draw on business registration and enterprise investment databases to estimate the impact of the pandemic shock on the evolution of local industrial dynamics between 2018 and 2024. Our findings indicate that after the core cities underwent the shock of the COVID-19 pandemic, the path dependence of industrial evolution in their surrounding areas significantly increased. The stronger the economic linkage with Shanghai, the more pronounced this effect. However, this impact also exhibits spatial heterogeneity across the Yangtze River Delta, associated with regional industrial division of labour and cooperation. This paper offers an innovative examination of how changes in the industrial heterogeneity of investment inflows from core cities—specifically, dimensions such as relatedness to local industries, industrial upgrading, and diversification—shape the mechanisms of local industrial evolution following the COVID-19 shock. Our findings offer important implications for regional development and adaptive responses in the post-pandemic era.

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.

Capital market internationalization is widely regarded as an important pathway to improving resource allocation efficiency and enhancing governance quality, while simultaneously imposing higher requirements on corporate sustainability and social responsibility. However, its impact on firms’ internal income distribution remains subject to academic debate. This study treats the inclusion of China’s A-shares in the MSCI Emerging Markets Index as a landmark exogenous shock of capital market internationalization. Based on a sample of Chinese A-share listed firms from 2014 to 2022, we manually compile firm-level MSCI inclusion data and construct a multi-period difference-in-differences model for empirical testing. The results indicate that firms’ inclusion in the MSCI Index significantly increases their labor income share. The mechanism analysis reveals that this promoting effect operates mainly through three channels: alleviating financing constraints, fostering innovative development, and strengthening investor governance. Further heterogeneity analysis shows that the effect is more pronounced among technology-intensive firms, firms under greater competitive pressure, and firms with higher degrees of internationalization. By incorporating income distribution outcomes into the framework of capital market internationalization, this paper enriches the evidence on the economic and social effects of internationalization and provides policy implications for emerging economies to advance high-level capital market opening and optimize income distribution.

Traditional production function theory treats executive characteristics as exogenous fac-tors, failing to capture how managerial heterogeneity dynamically influences productiv-ity. This study integrates Upper Echelon Theory and Dynamic Capabilities Theory to develop an endogenous production function framework where executive attributes serve as dynamic parameters reshaping capital and labor elasticities. Using fixed effect-s panel-data models, we analyze Chinese listed companies, examining how executives’ education, experience, and compensation interact with production parameters. Re-sults show executive characteristics significantly moderate factor productivity: higher education and board independence enhance capital productivity, while compensation intensity transforms labor elasticity from negative to strongly positive values. Hetero-geneity analysis reveals effects vary across ownership types and technology intensity, with technology-intensive firms showing strongest responsiveness. This research recon-ceptualizes executives as active architects of production processes, provides a rigorous framework for endogenizing management factors, and offers evidence-based guidance for corporate governance and talent strategy optimization.

The essay delves into the impact of environmental uncertainty on asymmetric mispricing utilizing the data from listed firms in China spanning from 2007 to 2023. Our analysis reveals that environmental uncertainty amplifies stock mispricing within capital markets, whether upward or downward. Diverging from prior research, we distinguish between upward and downward mispricing and reveal the black box of environmental uncertainty affecting stock mispricing from dual channels. Specifically, environmental uncertainty intensifies upward mispricing through heightened earnings management and exacerbates downward mispricing by boosting investor irrationality. Furthermore, we explore the heterogeneous impact of different media coverage. In the downward mispricing sample, negative media exacerbated the relationship between the two, while positive coverage played a mitigating role. In the upward mispricing sample, only negative reports have a significant impact, and mitigate the impact of uncertainty on mispricing. Our research on media heterogeneity once again proves that it is a double-edged sword. Our research indicates that improving the capacity to recognize different mispricing mechanisms in various market directions can greatly boost decision-making efficiency. Meanwhile, it is vital to strengthen professional ethics in media organizations and encourage more objective reporting. These efforts can jointly contribute to improve he efficiency of emerging capital markets.