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This paper investigates the impact of financial integration on the capital structure of the firms operating in mainland China, examining the firm-level and country-level integrating variables for 2,878 listed Chinese firms over the period of 1991–2016 in regard to the firms' capital structures. Finally, the study revisits the associations for the state-owned and multinational firms in the context of China.

A large sample of unbalanced data from firms were used to explore the relationship firm-level and country-level integrating variables has with firm leverage and maturity; this is accomplished using the fixed effect model. For robustness, a system-generalised method of moments was used.

The results indicate that internationalisation positively impacts the leverage and debt maturity of all listed Chinese firms and multinational firms and that state-owned firms are financed mainly by the state. For country-level integration, the authors find that credit and equity markets are negatively related to a firm's leverage. A negative relation with credit markets suggests that Chinese firms have much cheaper financing options than the benefits that arise from credit market integration. Moreover, the effect of equity market integration is more pronounced on Chinese firms' capital structure and debt maturity than credit market integration.

The results provide valuable implications of financial integration for policymakers as well as capital structure decision-making for managers in China.

Few studies have examined the impact of integration on firms' capital structures in developing countries. After controlling for unobserved heterogeneity and endogeneity, this study adds new multilevel integration evidence on the capital structure of Chinese firms.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This study aims to explore how earnings management techniques are affected by corporate financial debt risk (FDR), internal control (IC) effectiveness and CEO education.

The study uses a sample from listed firms in China from 2010 to 2017, comprising different industries, including agriculture, forestry, livestock farming and fishing; mining; manufacturing; electric power, gas and water production and supply; construction; transport and storage; information technology; the real estate industry; social services; and communication and cultural. The regression analysis is used to test the hypotheses. The two-stage least squares technique is used to check for endogeneity issues.

The study finds that firms are less likely to manage real earnings when they have more robust IC and FDR. Likewise, companies with weak ICs are more likely to manipulate real earnings. Besides, the study finds an influence of CEO education on the relationship between IC, FDR and real earnings management (REM). These results can be applied to the sectors in the sample covered by the research, and the authors do not overlook the energy industry sector for the importance of its role in the economy.

There are some limitations for the researcher when performing any research, and this study is no exception. Researchers are urged to take these circumstances into consideration when generalizing or comparing the results because the methods used to calculate the measurement variables in each study may differ somewhat from those used in other research. In addition, expanding the current research design to incorporate additional nations may be an area of interest for future research and could aid in evaluating the effects of nation-specific elements (such as inflation, culture, legal systems and political considerations) on the usefulness of IC and decreasing FDR. Second, the current study focuses on the impact of IC and FDR on REM; this paper does not dissect the “black box” of IC and consider how each element affects earnings management. Future research may need to focus specifically on how effective IC would affect earnings management and precisely what IC mechanisms would discourage the management of earnings.

Helping companies listed in China to make decisions and improve investors’ vision of the results of real companies’ businesses, as well as helping management to avoid falling into debt risk and the consequent effects and manipulation of earnings.

By highlighting the significance of IC and debt risk in enhancing information quality in China, the results contribute to the body of work examining the relationship between IC, FDR and REM. In addition, this study uses a CEO’s education to moderate this link.

This paper aims to examine whether chief executive officer’s (CEO) information technology (IT) background can affect enterprises’ continuous green innovation (CGI).

This study uses the data of China’s listed enterprises from 2011 to 2019.

The statistical results reveal that when a company hires a CEO with an IT background, its CGI can be higher. Firm ownership, firm digitization and industry bias alter the impact of CEO’s IT background on firms’ CGI. This effect is most pronounced in non-state-owned enterprises (non-SOEs), high-digitalized enterprises and skill-biased industries, while not in SOEs, low-digitalized enterprises and labor-biased industries.

This study has practical implications, as it measures CGI of enterprises. It also points to the necessity for a CEO’s IT background to enhance CGI.

The findings provide new strategies for incentivizing sustainable development and green innovation.

To the best of the authors’ knowledge, this study is the first to discuss the association between CEO’s IT background and enterprises’ CGI. The conclusions enrich both upper echelons theory and enterprise green innovation literature.

This study aims to investigate the influence of digital transformation on the overall financial performance of firms, with a specific focus on Chinese-listed companies from 2010 to 2021. It seeks to understand the impacts on various accounting and financial indicators in emerging economies such as China.

This study employs a text-mining approach to construct a digital transformation index based on the data sample of 11,814 firm-year observations from China’s A-share listed companies. This index serves as a proxy to measure the extent of digital transformation and its impact on financial performance and health.

The findings indicate that digital transformation significantly enhances overall financial performance and health, as evidenced by increased profitability, reduced operational costs, and lowered financial risks. The study reveals a time-lagged effect, where the benefits of digital transformation become more apparent after about one year. Further analysis shows that the value of digital transformation is more evident in a firm’s asset items. This raises the possibility of recognising the by-product, such as data resources, in the digital transformation process.

This research offers a unique contribution by linking digital transformation to financial performance using a large dataset from China's A-share listed firms. Doing so enhances our understanding of the tangible effects of digital transformation on corporate performance. Furthermore, this research provides valuable insights for the advancement of future accounting practices and the development of standards.

This study aims to examine the effect of board gender diversity on corporate litigation in China’s listed firms. The key questions this study addresses are: what are the effect of board gender diversity on corporate litigation in terms of both the frequency and severity of consequence, is there any heterogeneous effects of the relationships across firm performance?

A sample consists of 25,668 firm-year observations from over 3,340 firms is examined using logistic regression analysis and negative binomial regression analysis. The authors also use event study method and ordinary least square (OLS) regression to explore female directors’ effects on reducing the negative consequences of litigation. The logistic regression and OLS regression are reestimated with interaction terms when examining the firm performance heterogeneity.

The authors document that firms with greater female representation on their boards experience fewer and less severe corporate litigations. Moreover, in high-performing firms, board gender diversity plays a more potent role in reducing the frequency and consequences of corporate litigation than low-performing firms.

This study is among the first to examine the relationship between board gender diversity and the comprehensive corporate litigations under Chinese context. It sheds new light on China’s boardroom dynamics, offering valuable empirical implication to Chinese corporate policymakers on the role of female directors.

Based on the textual-analyzed data covering 2148 IPO firms in China’s stock market during the 2007–2018 period, the authors’ purpose is to examine the influence of anti-takeover provision (ATP) adoption on initial public offerings (IPO) underpricing and identify the reducing effect of the former.

The authors examine the sample consisting of Chinese A-share listed IPO firms between 2007 and 2018 from China Stock Market Accounting Research and Chinese Research Data Services, with ATP data collected from the IPO firm chapters. Specifically, the authors use text analysis to identify whether there are ATPs in the IPO firm chapters, as well as the number of ATPs. H1: IPO underpricing is less severe for firms adopting ATPs. H2: The effect of ATP adoption on IPO underpricing is more salient for firms in worse information environments.

The authors examine the influence of ATP adoption on IPO underpricing and identify the reducing effect of the former. This effect can be explained by the fact that adopting ATPs in IPO firm chapters can reduce information asymmetry to a large extent by helping external investors obtain more private information, which alleviates IPO underpricing. The authors also find that the reducing effect is more significant in the worsened information environment. Furthermore, the authors explore the influence of adopting ATPs on other IPO characteristics and find positive effects on IPO over-subscription, funds raised and trading activity and negative effects on listing fees.

This study mainly contributes to the literature from the following two aspects. First, the study enriches the literature about the influencing factors of IPO underpricing. Second, the study also enriches the literature about the economic consequences of ATP adoption. This study also has important policy implications. With the coming of the era of decentralized ownership in China’s capital market, ATP adoption has become more important and attracted more attention. Also, investors focus more on pricing efficiency. The findings in this paper provide a more comprehensive understanding of the relationship between ATP adoption and IPO underpricing.

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.

This paper examines whether technological changes that promote communications between investors and managers help bridge the gap in the cost of equity capital among firms in different regions.

We use the online interaction platforms of listed firms in China and utilize brokerage presence (BP) to capture the geographic distribution of financial factors. We explore whether online interactions would reduce the cost of equity to a greater extent for firms located in low brokerage presence regions (hereafter “low-BP firms”) than those in high brokerage presence regions (hereafter “high-BP firms”).

We find low-BP firms benefit more from an improved information environment created by online interactions. We also find that posts about low-BP firms are more value-relevant and useful in processing corporate disclosures. Further, a higher number of interactions significantly enhances more informational efficiency for low-BP firms, and the effect of reducing the gap in financing costs is more pronounced when corporate information is complex.

We conclude that online interactions alleviate geography-induced information frictions and create a relatively level playing field for firms located in all regions.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.