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Human resource analytics (HRA) has developed as a new business trend and challenge, stressing the strategic relevance of human resource management (HRM) to senior management executives. HRA is a process that uses statistical techniques, to link HR practices to organizational performance. The purpose of this study is to carry out recent development in HRA, bibliometric analysis and content analysis to present a comprehensive account of HRA to fill the gap in the evolution and status of its research.

The study is based on the recent advances in HRA in terms of it evolution and advancement by analyzing and drawing conclusions 480 articles retrieved from the Web of Science (WoS) database from 2003 to March 2022. The methodology is divided into four steps: data collection, analysis, visualization and interpretation. The study performed a rigorous bibliometric assessment of HRA using the bibliometric R-package and VOS viewer.

The findings based on the literature survey, and bibliometric analysis, reveal the path-breaking articles, the prominent authors, most contributing institutions and countries that have contributed to the HRA scholarship. The results show that the number of publications has significantly increased from 2015 onwards, reaching a maximum of 101 journals in 2021. The USA, China, India, Canada and the United Kingdom were the most productive countries in terms of the total number of publications. Human Resource Management Journal, Human Resource Management, International Journal of Manpower, and Journal of Organizational Effectiveness-People and Performance are the top four academic outlets in the field of HRA. Additionally, the study identifies four clusters of HRA research and the knowledge gaps in HRA scholarship.

The present study is based on the articles retrieved from the WoS. The study underpins HRA research to understand the trends and presents a structured account. However, the study is not free from limitations. It is recommended that future research could be undertaken by combining WoS and Scopus databases to have a more detailed and comprehensive view. This study indicates that the field is still in its infancy stage. Hence, there is a need for more arduous research on the topic to help develop a better understanding of this field.

The findings of knowledge clusters will drive future researchers to augment the field. The evolution of the four clusters and their subsequent development will fill the gaps in the literature. This study enriches the HRA literature and the findings of this study may assist academicians, researchers and managers in furthering their research in the identified research clusters

This paper aims to investigate the impact of the revised Code of Corporate Governance 2017 (CCG-2017) clauses pertaining to board independence, mandatory inclusion of female directors, audit committee (AC) chair independence and directors’ expertise on earnings manipulation.

Using an unbalanced panel of 323 listed companies from 2015 to 2019, this study uses panel data regression models with a robust methodology called difference-in-differences to tackle the potential endogeneity.

This study’s findings show that, as compared to the pre-CCG-2017 period, board- and AC-related variables increased significantly in the post-CCG-2017 period. Furthermore, financial experts on the board and board independence have a negative effect on discretionary accruals (DAs), whereas female directors and DAs are positively related, as is real activity manipulation. The AC-related variables, such as AC independence, expertise in AC, and AC chair independence, are significantly different from the preperiod to the postperiod, whereas their relationship is not according to the hypotheses of the study. Moreover, these results are robust to additional analysis of the alternative proxies for female directorship and the endogeneity problem.

The findings of this study have implications for regulators and practitioners who are concerned with the functions of the board of directors (BOD). The findings of this research study show that earnings management (EM) may be reduced by independent and expert directors. However, board gender diversity is not reducing the EM. Therefore, the decision to appoint female directors to the board should be based on their business and professional attributes rather than simply filling quotas or blindly adhering to regulations. Moreover, the findings of this research may assist the regulator in encouraging listed firms to enhance board governance via independence, diversity and competency, which are useful for effective monitoring.

This study fills a gap in the literature by providing the first evidence of country-specific regulation (CCG-2017), concerning the BOD and AC-related clauses on EM in Pakistan, which is missing in the relevant literature general and in Pakistan in particular.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This study aims to advance knowledge on the direct impact of the investor’s protection level on the stock market volatility, that is, whether investor’s protection is an important stock market volatility determinant.

A panel data was estimated using a sample of 48 countries, from 2006 to 2018, totalizing 31,808 observations. To measure stock market volatility and the investor protection level, a generalized autoregressive conditional heteroskedasticity model and the World Bank Doing Business investor protection index were used, respectively.

The results evidence that the protection of investors’ rights reduces the stock market volatility. This result indicates that a high level of investor protection, which is the result of a better quality of laws and policies in place that protect investor’s rights, promotes the country as a “safe haven.”

The relationship that the authors intend to analyze becomes important, given that investor protection will give outsiders guarantees on the materialization of their investments. This study contributes important knowledge for investors and for the establishment of government policies as a way of attracting investment.

Although there have been a few studies addressing this relationship, to the knowledge, none of them directly analyses the influence of investor protection on the stock market volatility.

This study investigates the convergence-of-interest and entrenchment effects on the relationship between managerial ownership and financial distress using evidence from the Chinese stock market. It also analyzes whether the relationship is mediated by research and development (R&D) investment.

Using a dataset consisting of 19,059 firm-year observations of Chinese listed companies in the Shanghai and Shenzhen Stock Exchanges between 2010 and 2020, this study employs both piecewise and curvilinear models.

The results indicate that managerial ownership has a negative association with firm financial distress in both the low (below 12%) and high (above 18%) convergence-of-interest regions of managerial ownership, suggesting that managerial ownership in this region may contribute to improve firm financial status. Meanwhile, managerial ownership has a positive association with firm financial distress in the entrenchment region (12–18%), implying that managerial ownership in the entrenchment region may contribute to impair firm financial status. Furthermore, the results show that R&D investment mediates the association between managerial ownership and financial distress.

This study is the first to provide evidence of a nonlinear relationship between managerial ownership and financial distress, and identify the entrenchment region in the Chinese setting.

This study aims to examines both accrual and real-based earnings management (EM) behavior of listed corporations in tax-free countries during different economic situations. It also addresses the link between firm- and country-level determinants of accrual and real-based EM and explores economic conditions' influence on these determinants.

The study examines 1,608 firm-years, covers sixteen years (2004–2019), clustered into three periods according to the global financial crisis (GFC): four years prior (2004–2007), two years during (2008–2009), and ten years post the GFC (2010–2019). We employ the modified Jones model (performance-matched) developed by Kothari et al. (2005) to measure the accrual-based EM (positive and negative discretionary accrual EM) and the three levels model for Dechow et al. (1998) to measure the real-based EM (cash flow from operating, discretionary expenses and abnormal production cost).

The study finds a significant increase in EM practices in the listed corporations in tax-free countries during the economic downturn. These corporations are found to understate their earnings during the economic stress period. Simultaneously, the firm-level determinants of EM practices were at the same level of significance during different economic conditions in accrual-based EM. In contrast, the country-level EM determinants vary based on the economic conditions.

Financial reports' users gain a deep understanding of the quality of financial reports in the context of tax-free country. And, the study outcomes inspire policymakers to develop relevant legislation to mitigate financial reports' risk and adequately protect the financial reports' users.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

The global economy has been affected by the COVID-19 pandemic, which has placed greater responsibility on companies to fulfill their obligations to Corporate Social Responsibility (CSR) amid the crisis. This chapter investigates the role of a Chief Executive Officer (CEO) attributes in improving a firm's CSR in the emerging economy of Jordan and how the COVID-19 pandemic modifies this relationship. Using a Jordanian sample of 655 firm-year observations during the 2014–2021 period, the research results show that older CEOs, well-educated CEOs, CEOs' remuneration, and CEOs' ownership positively correlate with CSR reporting. However, long-tenured CEOs are associated with lower CSR initiatives. The subsample analysis findings also validate the significance of CEO attributes in improving CSR practice during the COVID-19 pandemic compared to the prepandemic period. These findings are beneficial for the regulatory setters to understand better whether CEO attributes are linked to engagement in CSR-related information. This research is among the limited number of studies that have explored how CEO attributes impact CSR reporting for the stakeholder's welfare. Moreover, it uniquely concentrated on contrasting the findings before and during the COVID-19 pandemic.

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.