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Findings in the literature indicate leading financial analysts attract high levels of market attention and provide more accurate earnings forecasts prior to becoming all-star analysts. Furthermore, these analysts significantly impact the investment decisions of other market participants and thus the market price of assets. Therefore, this study examines the information role of leading financial analysts and identifies two significant conclusions. First, the positive outcomes of these analyst leaders are more informative and attract more followers. Second, informational herding by followers of these analysts is not as naïve as suggested in previous studies, as followers who smartly use information from analyst leaders tend to perform better. We also find that analysts who practice smart learning by studying and selectively employing analyst-leader decisions achieve better career outcomes.

The purpose of this study is to examine the interplay between integrated reporting quality (IRQ) and capital markets. More specifically, the authors test the impact of IRQ on stock liquidity, cost of capital and analyst forecast accuracy.

The sample consists of listed firms on the Johannesburg Stock Exchange in South Africa, covering the period from 2012 to 2020. The IRQ measure used in this study is based on data from Ernst and Young. To test the proposed hypotheses, the authors conducted a generalized least squares regression analysis.

The empirical results evince a positive relationship between IRQ and stock liquidity. However, the authors did not find a significant effect of IRQ on the cost of capital and financial analysts’ forecast accuracy. In robustness tests, it was shown that firms with a higher IRQ score exhibit higher liquidity and improved analyst forecast accuracy. Additional analysis indicates a negative association between IRQ and the cost of capital, as well as a positive association between IRQ and financial analyst forecast accuracy for firms with higher IRQ scores (TOP ten, Excellent, Good).

The study stands as one of the initial endeavors to investigate the impact of IRQ on the capital market. It provides valuable insights for managers and policymakers who are interested in enhancing disclosure practices within the financial market. Furthermore, these findings are significant for investors as they make informed investment decisions.

This study aims to contribute to the emerging debate about materiality with novel insights about the signaling effects related to the disclosure of environmental, social and governance (ESG) information using the guidelines released by the Global Reporting Initiative (GRI) and the Sustainability Accounting Standards Board (SASB).

An empirical assessment using panel data analysis was built to evaluate the relationship between sustainability reporting standards and analysts’ forecast accuracy.

The analysis revealed that the proliferation of sustainability reports prepared on mandatory or voluntary basis mitigated the signaling effects related to the disclosure of ESG information by companies. Furthermore, the additional analysis conducted considering sustainability reporting quality and ESG performance revealed the existence of mixed effects on analysts’ forecasts accuracy. Therefore, the insights highlighted the need to consider a cautionary approach in evaluating the contribution of ESG data to financial evaluations.

The practical implications consist of identifying criticisms related to disclosing ESG information by listed companies. In detail, the analysis underlines the need to enhance reporting standards’ interoperability to support the development of more accurate analysis by investors and financial experts.

The analysis reveals increasing attention investors pay to socially responsible initiatives, confirming that financial markets consider sustainability reporting as a strategic driver to engage with stakeholders and investors.

This research represents one of the first attempts to explore differences between GRI and SASB using an empirical approach.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

This paper aims to empirically examine the impact of mandatory CSR disclosure on the CEO pay performance sensitivity.

Using the mandatory requirement of CSR disclosure as an exogenous shock, the authors compare the changes in CEO pay performance sensitivity for treatment firms with control firms through a difference-in-difference (DiD) approach.

The authors find that mandatory CSR disclosure enhances CEO pay performance sensitivity. The results also show that monitoring CEO power is a conduit through which mandatory CSR disclosure affects CEO pay performance sensitivity. The positive impact is more profound in firms with a powerful CEO, i.e. one who is politically well-connected, holds dual roles as both CEO and Chairman, and/or has had a long tenure. Furthermore, the increased CEO pay performance sensitivity after the mandate is prominent among state-owned enterprises (SOEs) only.

The findings of this paper have implications for other economies with similar institutional backgrounds as China. Although the mandatory CSR disclosure does not require firms to spend on CSR investment, the mandatory CSR disclosure alters firm behaviour, and mitigates agency problems.

This paper contributes to the studies on the impact of CSR disclosure on firms' behaviour. To the authors' knowledge, this is the first study to examine the effects of mandatory CSR disclosure on CEO pay performance sensitivity using the quasi-natural experiment settings.

This paper examines the relationship between the extent and quality of the four dimensions of corporate social responsibility disclosure (CSRD) namely community, environment, workplace and marketplace with the long-run share price performance of Malaysian initial public offering (IPO) companies.

This study utilised secondary data by the content analysis of the annual reports and Datastream of 115 IPOs listed from 2007 to 2015 in Malaysia. The IPO’s performance was determined by calculating the return measures under the equally weighted and value-weighted schemes of the mean abnormal returns and buy-and-hold abnormal returns covering the three years post-listing using the event-time approach.

The findings demonstrate that Malaysian IPOs experience substantial overperformance and underperformance when both the IPO performance measures are benchmarked against the matched companies and market. The results indicated that the extent and quality of the community and environment CSRD dimensions are positively and significantly correlated to the IPO’s performance. On the other hand, the extent and quality of the workplace and marketplace CSRD dimensions are negatively and significantly correlated to the IPO performance.

Malaysian regulators could benefit from these findings in their endeavour to carry out a reform process on CSRD to improve its quality. The results of this study are important to investors, regulators, non-government organisations, communities and policymakers. They also enhance the understanding of companies about the importance of disclosing greater CSR information to improve their performance and profitability.

To the researchers' best knowledge, this study provides new insights into the association between CSRD and the performance of Malaysian IPO companies, which is considered important.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors.

This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency).

The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities.

The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices.

Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests.

To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

Corporate disclosures are essential because they provide transparent and accurate information about a company's financial health, performance, risks and governance practices. They enable investors to make informed decisions, promote market efficiency and maintain trust in the financial system. This paper uses bibliometrics to identify the intellectual composition of the literature on corporate disclosure.

Based on the bibliometric information of 4,551 articles on corporate disclosure research, the authors conducted citation, keyword co-occurrence, bibliographic coupling and publication analyses to elucidate the leading articles, authors, sources, institutions, countries, themes and topics in the field of corporate disclosure from the 1960s to 2021.

The findings of this review demonstrate that corporate disclosure research is based on four broad themes – the role of disclosure in capital markets, non-financial disclosure, determinants of corporate disclosure and firm risk and intellectual capital disclosure. This review suggests that management should pay attention to the financial and non-financial corporate information that investors, regulators and the government emphasise.

This paper is the first comprehensive bibliometric review on corporate disclosure. It summarises the regulatory shifts, technological changes and industry trends that have influenced corporate disclosure research. Besides identifying broad research themes, the authors performed bibliographic coupling for research on disclosure sources, including annual reports, management forecasts, earnings calls, press releases, the Internet and social media, to reveal the thematic clusters related to these sources.

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.