This paper investigates the supervisory incentive effects of employee stock ownership plans based on a corporate risk-taking perspective using data from a sample of Chinese A-share listed companies from 2006-2021. The results show that employee stock ownership plans significantly enhance corporate risk-taking. The specific mechanism is that employee stock ownership plans reduce the two-tier agency costs between shareholders and managers and managers and employees, alleviate corporate financing constraints, and thus enhance the level of corporate risk-taking. It is also found that employee stock ownership plan enhances the level of corporate risktaking with high quality, because employee stock ownership plan not only promotes R&D investment which is beneficial to corporate value growth, but also reduces excessive investment and high debt which are detrimental to corporate value, and the corporate risk-taking is of higher quality and more substantial value effect. In addition, differences in the institutional design of employee stock ownership plans have different effects on corporate risk-taking: employee stock ownership plans that are leveraged, highly discounted, with longer lock-up periods and duration, and entrusted to third-party institutions have a stronger effect on corporate risk-taking; employee subscriptions can promote corporate risk-taking more than executive subscriptions; employee stock ownership plans in China do not have the problem of "free-riding There is no "free-rider" problem in China's employee stock ownership plan. The larger the issuance ratio of the employee stock ownership plan, the greater the number of participants, and the larger the scale of capital, the better the implementation effect.

Comprehensive evaluation and identification of the critical regulatory determinants of carbon emission efficiency (CEE) are very important for China’s low-carbon transition. Accordingly, this paper first employs an undesirable global super-hybrid measure approach to calculate the CEE of China’s iron and steel industry (ISI). We then further use spatial error and threshold regression models to examine the spatial and non-linear effects of heterogeneous environmental regulations on CEE, respectively. Our empirical results show that (1) CEE varies significantly across China’s regions, with the eastern region having the highest CEE score, followed by the western and central regions, with the northeast region ranking the lowest; (2) command-and-control and market-incentive regulations both promote CEE, whereas the public participation approach does not significantly contribute to performance gains; (3) all three types of environmental regulations exhibit a non-linear threshold effect on CEE; (4) openness level, technological progress, and industrial concentration enhance efficiency gains, while urbanization level exerts a negative impact on CEE. Our findings have important implications for the design of environmental regulations.

Digital transformation (DT) is an ongoing and costly process that requires careful planning and the motivation of top executives (CEOs). This research analyze the CEOs compensation as a motivation to embrace DT by reducing agency issue. We determine the extent of DT through a textual analysis method and utilize data from Chinese publicly traded companies spanning the period between 2007 and 2020. Our study findings are threefold, (a) we observe a positive relationship between CEOs' pay gap and DT, highlighting the significant role CEOs compensation plays in encouraging CEOs to adopt digitalization, (b) we find that managerial shareholding significantly enhances this relationship, (c) we note that the relationship between CEOs pay gap and DT is more pronounced in state-owned enterprises compared to non-stateowned enterprises. Additionally, we discover through channel analysis that agency cost and audit quality mediate the relationship between CEOs pay gap and DT potentially by reducing the agency problem between CEOs and shareholders. These findings are vital for comprehending the pay practices and behaviors of corporate executives regarding digitalization in China. Importantly, the study results remain robust when considering instrumental variables (IV), propensity score matching (PSM), and alternative techniques.

Purpose – This study aims to investigate whether firms purchase directors’ and officers’ liability (D&O) insurance when the country-level economic policy uncertainty (EPU) is high. Design/methodology/approach – This study uses D&O insurance data from Chinese listed firms between 2003 and 2019 to conduct regression analyses to examine the association between D&O insurance and EPU. Findings – The results show that government EPU, despite being an exogenous factor, increases the likelihood of firms’ purchasing D&O insurance, and this effect is more pronounced when firms are exposed to great share price crash risk and high litigation risk, suggesting that firms intend to purchase D&O insurance possibly due to the accentuated stock price crash risk and litigation risk associated with EPU. In addition, the results indicate that the effect of EPU on the D&O insurance purchase decision is moderated by the provincial capital market development and internal control quality. Practical implications – The study highlights the role of uncertain economic policies in shareholder approval of D&O insurance purchases. Originality/value – The study enriches the literature on the determinants of D&O insurance purchases by documenting novel evidence that country-level EPU is a key institutional factor shaping firms’ decisions to purchase D&O insurance.

Software and accounting advances have led to a rapid expansion in and proliferation of loyalty tokens, typically bundled as part of product price. Some tokens, such as in the airline industry, already account for tens of billions of dollars and are a major contributor to revenues. An open question is whether, as technology evolves, firms will have a strong incentive to make loyalty tokens tradable, raising regulation issues, including with monetary and banking authorities. This paper argues that for the vast majority of tokens, issuing firms have a strong incentive to make them non-tradable. The core incentive for token issuance here is that an issuer can earn a higher rate of return on the ``float'' (tokens issued but not yet used) than its retail customers can, much like a bank. Our main finding is that an issuer earns higher revenue by making tokens non-tradable even though the consumer would be willing to pay a higher price for tradable tokens. We further show that an issuer with stronger market power tends to allow more frequent token redemption, and its revenue is more token-dependent. We test the model's predictions with data on airline mileage and hotel reward programs and document consistent empirical results that align with our theory.

In the digital era, the information value of online prices, characterized by weak price stickiness and high sensitivity to economic shocks, deserves more attention. This paper integrates the high-frequency online inflation rate into the dynamic Nelson-Siegel (DNS) model to explore its relationship with the term structure of interest rates. The empirical results show that the weekly online inflation can significantly predict the yield curve, particularly the slope factor, while the monthly official inflation is predicted by yield curve factors. The mechanism analyses indicate that, due to low price stickiness, online inflation is more responsive to short-term economic conditions and better reflects money market liquidity, thereby having predictive power for the yield curve. Specifically, online inflation for non-durable goods and on weekdays shows stronger predictive power for the slope factor. The heterogeneity in price stickiness across these categories explains the varying impacts on the yield curve.

When examining corporate governance in China, it is crucial to recognize the unique socioeconomicstructures 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.

The healthy operation of the stock market relies on sound liquidity. We utilize the semantic information from disclosure texts of listed companies on the China Science and Technology Innovation Board (STAR Market) to construct a daily corporate network. Through empirical tests and performance analyses of machine learning models, we elucidate the relationship between the similarity of company disclosure text contents and the temporal and spatial correlations of stock liquidity. Our liquidity indicators encompass trading costs, market depth, trading speed, and price impact, recognized across four dimensions. Furthermore, we reveal that the information loss caused by employing Minimum Spanning Tree (MST) topology significantly affects the explanatory power of network topology indicators for stock liquidity, with a more pronounced impact observed at the document level. Subsequently, by establishing a neural network model to predict next-day liquidity indicators, we demonstrate the temporal relationship of stock liquidity. We model a liquidity predicting task and train a daily liquidity prediction model incorporating Graph Convolutional Network (GCN) modules to solve it. Compared to models with the same parameter structure containing only fully connected layers, the GCN prediction model, which leverages company network structure information, exhibits stronger performance and faster convergence. We provide new insights for research on company disclosure and capital market liquidity.

This paper explores the ethical dimensions of firm-level digitalisation and its impact on ESG metrics during a decade (2010-2020) of rapid technological progress, focusing on Chinese-listed companies. Utilising a text-based index to measure digitalisation, we find that while digitalisation positively influences ESG ratings, supporting resource-based and dynamic capability theories, its relationship with corruption reveals complex dynamics. Surprisingly, corruption strengthens digitalisation’s positive impact on ESG, raising concerns about technology being used to enhance ESG appearances artificially. A distinct difference emerges between state-owned enterprises (SOEs) and non-SOEs; SOEs use digitalisation more ethically and are less influenced by corruption, indicating a more responsible approach to technology adoption. Through examining cash holdings, internal controls, and audit fees, we unpack how corruption influences the digitalisation-ESG nexus. These insights underscore the need for policy that encourages ethical digitalisation and highlight the potential role of SOEs in leading the charge towards sustainable and ethical digitalisation.

The influence of informal institutions such as history and culture on corporate behavior has been widely recognized, but few studies have been analyzed from the perspective of the ruling party culture. Based on the data of the old revolutionary base areas (ORBA) in China, this paper makes an empirical test on the role of Red Culture in promoting enterprises green innovation. First, this paper finds that the stronger the Red Culture in the region where the enterprise is located, the higher the level of green innovation.Secondly, in the samples with high political sensitivity and less cultural conflict, the promoting effect of Red Culture is more obvious. This paper not only expands the relevant literature on the influence of informal system on enterprise green innovation, but also enriches the research on the influence of Chinese unique culture on enterprise management decision-making.