We examine the impact of government social media on capital markets using China's staggered adoption of local government microblogs. A difference-indifferences design reveals economically significant increases in firm value, with stronger effects for more content-rich, original, and interactive microblogs. We find improvements in the corporate information environment and reductions in perceived uncertainty, with larger effects for firms with limited external information coverage and in stronger business environments. During the COVID-19 Wuhan lockdown, firms in regions with more active microblogs achieved better stock performance. Overall, government social media is a powerful tool for enhancing transparency, firm valuation, and market resilience.

Purpose-This study explores how inconsistency in environmental, social and governance (ESG) ratings affects the information environment of publicly traded companies in emerging markets. Design/methodology/approach-Drawing on data from six ESG rating agencies covering listed Chinese firms from 2010 to 2022, we construct measures of pairwise ESG rating divergence and average them across 15 unique rater pairs. We then employ a battery of econometric methods to examine how inconsistencies in ESG ratings affect stock return synchronicity in the Chinese capital market. Findings-Our findings indicate that greater ESG rating divergence correlates with increased stock return synchronicity, suggesting a decline in the dissemination of firm-specific information. Supporting evidence for this relationship includes reduced private information flow, heightened opportunistic executive sales and decreased stock turnover for firms associated with higher ESG rating divergence. Our analysis suggests that such divergence hinders informed trading by institutional investors and the effect is more pronounced for firms with lower transparency, such as those with fewer analysts, limited investor oversight and sparse ESG disclosure, as well as for firms in non-polluting industries. These findings emphasize that ESG rating divergence exacerbates uncertainty about firms' future performance, discourages informed trading and ultimately restricts the integration of firm-specific information into stock prices. Originality/value-This study adds to the literature on ESG ratings and market efficiency by highlighting the importance of standardizing rating methodologies and improving corporate disclosure to counteract the adverse impacts of rating divergence.

Digital technologies are often portrayed as disruptive levers for decarbonisation, yet many digital green initiatives improve transparency and efficiency without redesigning how environmental value is authorised, coordinated, and appropriated. We address this puzzle by theorising green digital business model innovation as the evolution of venture-level configurations under multi-domain selection in policy-steered sustainability transitions. Building on the activity-system view of business models and on innovation-studies, we define business model radicality as coupled reconfiguration across content, structure, and governance rather than technology novelty alone. We further theorise a cross-domain convergence requirement: configurations are retained only when they align simultaneously with institutional role allocations, market interfaces, technological infrastructures, and ecological verification demands. A comparative longitudinal study of three blockchain-enabled initiatives in China’s energy-finance nexus shows that radical disintermediation is screened out early when any single domain withholds authorisation or credible settlement, whereas incumbent-compatible configurations are retained through sequencing, interpretive pruning, and boundary-spanning alignment work. The study contributes to innovation studies by treating business models as meso-level selection objects, sharpening configuration-level radicality, and explaining why digital green opportunities often remain incremental in regulated transition systems.

We examine the relationship between government data opening and corporate leverage manipulation. Leveraging the staggered establishment of province-level open government data platforms in China as a quasi-natural experiment, we find that government data opening significantly reduces corporate leverage manipulation. This policy effect is more pronounced among firms with low capital intensity, firms with limited analyst coverage, and those located in regions with low banking competition. Mechanism analysis suggests that government data opening affects the cost-benefit tradeoff of corporate leverage manipulation by alleviating financing constraints and enhancing corporate governance, thereby mitigating leverage manipulation practices. Our research contributes to the literature on government data opening, highlighting its role in reducing leverage manipulation and offering valuable implications for mitigating significant financial risks.

A central premise of mandatory disclosure regulation is that greater transparency reduces information asymmetry and lowers borrowing costs. We challenge this premise by examining industry-level operational disclosure - a regulatory form that reveals horizontally comparable information across peer firms rather than refining individual firm fundamentals. Exploiting the staggered introduction of mandatory industry-specific disclosure guidelines by Chinese stock exchanges between 2013 and 2019, we find that enhanced industry disclosure significantly widens bond credit spreads by approximately 54 basis points - the opposite of what standard disclosure theory predicts. This counterintuitive effect is more pronounced in non-homogeneous industries, among smaller firms, and for bonds restricted to institutional investors. Mechanism tests confirm two opposing channels: disclosure reduces information asymmetry while simultaneously intensifying product market competition by exposing strategically sensitive operational metrics. Our evidence challenges the one-size-fits-all approach to disclosure regulation and highlights that the competitive implications of disclosed information - not merely its quantity - shape credit risk pricing.

This study examines the impact of Economic Policy Uncertainty (EPU) on the stock price crash risk of Chinese commercial banks. In addition, it explores how Governance and Digital Transparency curtail the effect of EPU on stock price crash risk. Using a sample of 50 Chinese A-share-listed banks from 2012 to 2024, the study reveals that EPU significantly increased the banks’ stock price crash risk. The findings are robust to alternative measures of EPU and stock price crash risk. Further, governance and FinTech adoption mitigate the positive effect. The mitigating effect persists across high- and low-risk bank subsamples. In addition, we perform a battery of analyses to support our main findings. These findings have important theoretical and practical implications.

Purpose – Estimates disclosure of human capital management for Chinese listed companies. Investigate the patterns ofthe disclosure of human capital management acrossindustries and regions. Examine the determinants of human capital management disclosure in China. Examine the association between human capital management disclosure and firm performance. Design/methodology/approach – We employ natural language processing techniques on annual reports’ management discussion and analysissections.We construct exposuremeasuresforten human capitalmanagement dimensions and synthesize them into one comprehensive measure of human capital management disclosure. We conduct empirical analysis on the measure using a sample of Chinese listed companies during 2009–2022. Findings – We construct a measure of human capital management disclosure for 5,153 Chinese companies during 2009–2022. We find that firms with high HCM disclosure are more labor intensive and have more cash holdings and R&D expenditure but have lower sales growth, market-to-book ratio and leverage. HCM disclosure is associated with better future accounting performance but poor future market valuation. There are substantial variations in HCM disclosure across industries, geographic regions and ownership types. HCM disclosure has increased significantly during the COVID-19 pandemic. Social implications – The increased HCM disclosure and its association with firm operating performance and market valuation indicate the relevance of HCM in corporate management and underscore the need for more robust and standardized disclosure of HCM in China. Our findingssupport recent regulatory efforts by CSRC to enhance the transparency and accountability in HCM disclosures and advocate for more explicit and specific HCM disclosure requirements in the future. Originality/value – We propose a quantitative measure of human capital management disclosure, which can be modified to apply to other markets. We construct a comprehensive, ready-to-use dataset for HCM disclosure for Chinese listed companies and conduct descriptive analysis on the dataset. We identify the patterns of human capital management disclosure and its determinants in China.

This paper investigates whether firm-level freight activity captures corporate fundamentals and predicts stock returns. Using smartphone geolocation data of truck drivers from 2019 to 2024, we construct a novel freight growth index (FGI) to quantify firms’ freight activity in the Chinese stock market. We find that firms’ freight growth is strongly associated with current operating performance and predicts future stock returns. A long-short portfolio sorted on FGI generates significant risk-adjusted monthly returns ranging from 57 to 72 basis points. Further evidence suggests that freight growth forecasts earnings announcement returns and is more predictive for firms with low information transparency. Moreover, freight growth provides incremental information in predicting stock returns beyond analyst forecasts. Our findings highlight that firm-level freight activity contains novel insights into firm fundamentals and stock pricing.

Traditional information asymmetry theories suggest that greater corporate transparency should reduce investor disagreement. Using Chinese mutual fund holdings, we document the opposite pattern: transparency amplifies disagreement among institutional investors. Mechanism tests show that transparency discourages herding while intensifying private information acquisition among fund managers. The effect is stronger for growth-oriented and high-skill funds, and during periods of elevated market sentiment, and among firms with lower credibility, excessive disclosure frequency, and greater investor attention. Further analysis indicates that this transparency-induced disagreement stems from informed trading rather than noise, thereby enhancing price informativeness and market efficiency. Overall, the evidence reveals the dual nature of transparency as both an informational input and a behavioral catalyst that increases disagreement in financial markets.

This study investigates how the development of digital finance influences the geographical distribution of corporate supply chains using data from Chinese A-share listed companies from 2010 to 2023. We examine whether digital finance enables firms to overcome traditional geographical constraints and adopt different supply chain distribution strategies. The analysis identifies two primary mechanisms through which digital finance influences supply chain geography: governance effects, which operate through enhanced risk management and information transparency, and financing effects, which function through alleviated capital constraints and trade credit provision. We further explore heterogeneous impacts across four dimensions: regional economic development, regional digital infrastructure, industry market competition, and enterprise lifecycle stages. By examining the geographical distribution of supply chains as an outcome of digital finance development, this study provides novel evidence on the micro-governance implications of digital finance. Our findings contribute to understanding how digital finance fundamentally changes the geographical constraints that have historically shaped supplier selection decisions and enables firms to develop more flexible supply chain configurations.