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With growing evidence of financial misconduct spreading through director networks, research on financial fraud contagion has garnered significant attention. This study incorporates the regulatory enforcement perspective into existing literature to examine how regulatory penalties mitigate financial fraud contagion within director networks.

This study uses a panel dataset of A-share listed Chinese firms covering 2007–2022. Based on the nature of the dataset, we construct ordinary least squares regression models with firm- and year-fixed effects. Data are collected from the China Stock Market and Accounting Research, Wind Information Co., Ltd and China Research Data Services. We use Python to scrape the coordinates of regulators and firms and retrieve travel distances from the Baidu Maps API.

This study verifies the existence of financial fraud contagion in director networks. Our findings indicate that regulatory penalties can mitigate the contagion between director-interlocked firms, improving accounting quality. Moreover, the mitigation effects are mediated by independent directors’ dissent and auditors’ efforts at director-interlocked firms and are more pronounced when these firms have superior network centrality and internal control quality.

This study enriches the literature on financial fraud contagion by examining director networks and regulatory penalties. We propose mediating effects of auditor effort and director dissents on the relationship between regulatory penalties and financial fraud contagion. Our findings provide insights for regulators to alleviate pressures and highlight the importance for directors to consider financial risks within their networks.

This paper investigates the influence of CEO power on financial statement comparability using a multidimensional CEO power index and a comprehensive measure of financial statement comparability for ASX-listed companies.

This study applies ordinary least squares regression analyses to a sample of 3,562 firm-year observations spanning 2004–2015. A propensity score matching procedure, lagged regression models, instrumental variable two-stage least squares regressions and first difference models were performed for endogeneity correction and robustness purposes.

The results suggest that powerful CEOs are more likely to produce more comparable financial reports. We also analyse four dimensions of CEO power and find that the influence of CEO power on FS comparability mainly stems from ownership and expert power dimensions. Additionally, we report that the influence of CEO power on FS comparability is more pronounced for firms that operate under high market competition and industry-related shocks, but governance characteristics do not make a material impact on the uncovered relationship.

Given the pressure exerted by regulatory bodies on companies to reduce information asymmetry, the study’s empirical evidence offers valuable insights to policymakers, corporations and other stakeholders as it provides evidence on the importance of corporate leadership in improving FS comparability.

The extent to which CEO power is linked with the comparability of corporate disclosures is new to the literature. Investigating such a link is important because corporate disclosure is primarily a management practice that emanates from the board and generally affects the firm, its shareholders and other market participants.

The current research investigates how the adoption of Artificial Intelligence (AI)—a set of technologies designed to enhance decision-making and automate processes—impacts Integrated Financial Reporting (IFR) in Gulf Cooperation Council (GCC) listed firms, which present the typical features of emerging economies. It is postulated that their IFR is enhanced as firms within these markets experience AI adoption. In addition, the study also focuses on the role of audit quality towards AI adoption and the IFR relationship within these regions. To this effect, the study examines the moderation effect of audit quality (using its sub-components i.e. audit fee, audit industry specialization and restatement) on the relationship between AI adoption experience and IFR in GCC.

The investigation draws upon panel data consisting of 2,912 non-financial firm-year observations covering the period from 2010 to 2023 across GCC markets. To achieve its purpose, the study applies the conventional ordinary least square (OLS) to estimate the effect of AI adoption experience on IFR. Subsequently, to guarantee the robustness of the results, this study utilizes the propensity score matching (PSM) technique.

The results from empirical analysis disclose a direct impact of AI adoption on the IFR of the firms within GCC markets. Furthermore, the study also discovers that the high level of audit quality moderates this positive relationship. Therefore, in the GCC regions, firms with higher AI adoption show higher IFR effectiveness, mainly in the presence of specialized auditors and increased audit fees, whereas their relationship is stronger in the absence of restatements. The results are robust when tested through the PSM technique.

The results of this study highlight the significance for policymakers to ensure comprehensive AI adoption in GCC markets, as well as the appointment of industry specialists and the standardization of audit fees to support the improvement of IFR in the regions.

This study proposes an analysis of the performance of companies that have assumed the responsibility of facilitating the digitalization of economic activities. Because of their potential to accelerate digitization, these companies have been financially supported. The monitoring of the performances recorded by these companies, including the evaluation of the impact of different determining factors, meets both the needs of the financiers (concerned with the evaluation of the efficiency of the use of nonreimbursable financing) and the needs of continuous improvement of the activities of the companies in the field.

The study assesses performance dynamics and the impact of its determinants. The model allows achieving a simplified vision of performance and its determinants, supporting decision-makers in the management process. The construction of an estimation model based on the multiple regression method was considered. Robustness tests were performed on the results, using parametric and nonparametric tests.

The results of the analysis at the level of the extended sample indicated that, during the analyzed period, the economic and commercial performances decreased, and significant influences in this respect include the financing structure, sales dynamics and volume of receivables. The analysis at the level of the restricted sample confirmed these interdependencies and provided additional evidence of the impact of other determinants.

The study contributes both to performance research and to the assessment of the prospects for accelerating digitalization in support of economic activities. Since the empirical research was carried out on a sample of Romanian companies that provide services in information technology, which accessed nonreimbursable financing, the representativeness of the results is limited to this sector. For the analyzed sample, the study provides support for improving performance.

The results of the study prove to be useful from a microeconomic and macroeconomic perspective as well, as they provide evidence on the performance of companies that have implemented information and communication technology (ICT) projects and on the efficiency of the use of non-reimbursable funding dedicated to business support.

The study fills the literature gap regarding the performance of companies that have developed ICT projects and received grant funding for the implementation of these projects. The literature review indicated that there are few studies conducted on these companies, which did not include Romanian companies.