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This study aims to examine the impact of ownership structure variables on the performance of Saudi listed firms.

The impact of ownership structure variables on firm performance is examined using fixed effects and dynamic panel generalised method of moments regression approaches for 70 listed firms over the period 2016–2021. Ownership structure variables are captured by examining government, institutional, insider, foreign and family ownership, and firm performance is gauged in terms of the accounting-based measures of return on assets and the return on equity and the market-based measures of Tobin’s Q and the market-to-book ratio.

The results show that government, institutional, insider and foreign ownership all positively affect both accounting and market-based performance measures, whereas family ownership exerts a negative impact across the models. The findings support resource dependence theory, agency theory and alignment effects arguments.

The findings have significant implications for Saudi regulators in their effort to improve domestic capital market efficiency and investor protection, while also highlighting the need for a corporate governance code to safeguard minority shareholders. The results demonstrate that government, institutional, insider and foreign ownership exert an important impact on firm operational and market performance.

This study expands the literature by examining how ownership structure variables affect performance in an interesting developing country corporate context.

As of now, the digitization of corporate finance presents a paradigm shift in business strategy, innovation, financing and managerial capability around the globe. However, the prevailing finance scholarly works hardly document the impact of the digitalization of corporate finance on firm performance with global evidence and analysis. Hence, the contemporary debate on whether firm performance is genuinely stimulated because of the digitalization of corporate finance or not has been a pressing issue in the relevant literature. Therefore, the purpose of this study is to identify a data-driven, concise response to an unaddressed finance issue if the performance of high-digitalized firms (HDFs) outperforms that of their counterpart peers for wealth maximization.

The first stage test models examine the firm performance of relatively high-digitalized firms as opposed to low-digitalized firms based on the system GMM. The second stage test of the probabilistic (logit) model infers that the probability of being HDFs explores because of better performance. Then, the authors execute robust checks based on the different quantile regressions and Z-score-based system GMM. In addition, the authors recheck and present the test results of the fixed effect and random effect to capture time-invariant individual heterogeneity. Finally, the supplementary test findings of firms’ credit strength by using Altman five- and four-factor Z-score models are presented.

By using cross-country panel analysis as 15 years’ test bed for HDFs and low digitalized firms (LDFs), the test results indicate that the overall firm performance of a digitalized firm is significantly better than that of a non-digitalized firm. The global evidence documents that HDFs are exposed to higher values and are financially more persistent as compared to their counterparts. The finding is remarkably concomitant across several possible subsample analysis, such as country–industry–size–period analysis.

This study can be remarkably effective in encouraging managers, policymakers and investors to acknowledge the need for adopting the required digitalization. Overall, this original study addresses a core research gap in the corporate finance literature and remarkably provides further direction to rethink the assumptions of firm digitalization on additive value and thereby identify optimal decisions for wealth maximization. The findings also imply that investors require an additional risk premium if they invest in relatively LDFs, which have relatively lower market value and weaker firm performance.

From an investors point of view, the academic novelty contributes to an innovative and unsettled issue on the impact of digitization of corporate finance on firm performance because there is a new question of high or low digitization of corporate finance in the global market. Hence, this academic novelty contributes to sharing global evidence of the digitalization of corporate finance and its effect on firm performances. In addition, an intensive critical review analysis is conducted based on the most recent and relevant scholarly works published in the top-tier journals of finance and business stream to fix the hypothesis. Overall, this study addresses a core research gap in the corporate finance literature; notably provides further direction to rethink firm digitalization; and thereby identifies optimal decisions for shareholders’ wealth maximization.

The purpose of this study is to investigate the association between three corporate governance (CG) idiosyncrasies, namely audit committee characteristics, external audit quality (AQ), board diversity and firm performance (FP) in the South Asian Association for Regional Cooperation (SAARC) nations.

The study used a sample of 200 listed nonfinancial firms in the SAARC nations from 2012 to 2021. The System Generalized Method of Moment model was applied to the data consisting of 2000 firm-year observations. The Generalized Estimating Equation population-averaged model was also employed for added robustness. The study employed Tobin's Q as the measure of FP.

The findings revealed that amongst the CG variables tested, external AQ exhibited a significantly positive relationship with Tobin's Q. Significant negative influences on FP have been demonstrated by the variables of audit committee meeting and board's independence. Furthermore, gender diversity, CEO duality, audit committee strength and independence failed to record any significant association.

This study is one of the first to investigate the association between CG idiosyncrasies and FP in the SAARC nations. The study findings have important implications for policymakers and regulators in the region.

This study aims to empirically investigate the impact of oil prices, political instability and changes in stability on the bank diversification of the two types of banking systems in the Middle East and North African (MENA) countries.

The study uses bank diversification, stability measurement of probability of default and Zscore by adopting the generalised method of moment for the data between 2007 and 2021. The authors estimate short- and long-run dynamic panel analysis and a robustness test.

The findings reveal that Islamic banks are slightly lower in diversification and stability than conventional peers in the region. Diversification increases with a positive increase in GDP growth, law and order, political stability, bank size, asset quality, oil price, return on equity, profitability and change in banking asset-based stability. The authors found consistency in the two stability measurements in both short- and long-run situations.

Despite the change in banking stability and economic growth and oil prices improved diversification, banks in the region are not diversifying during the crisis period and political instability. Therefore, policymakers should improve mechanisms to monitor the crisis and political unrest to avoid the systemic risk that adversely affects the system through macro-financial linkages in the region.

This study uses change dual stability measurements and oil prices to predict MENA region bank diversification. The authors extended the banking literature by estimating the relationship between crisis periods, political and banking stability, oil prices and other institutional indicators of banking diversification. This study uncovers the effect of the global crisis period on banking diversification and the impact of banking stability changes and validates the models through robustness tests.

Executive decisions regarding capital financing are an important management aspect, especially during financing constraints and growth opportunities. The current study examines the impact of managerial skills of a company on capital financing decisions. Furthermore, it analyzed this nexus in financing constraints and growth opportunity situations.

The authors use the GMM (generalized method of moments) estimation approach on a dataset of 20,651 firm-year observations of Chinese A-share companies from 2010 to 2019.

The authors’ findings are compatible with management signaling and reputation enhancement theories, since they show that managerial skill is connected with more substantial debt financing. Managers with high management skills are likely to have more debt financing as they can foresee the economic future of their companies and tactfully convey private information, lowering information inequality and enhancing their reputation. Furthermore, the authors also show that firms with restricted financial resources and growth opportunities make this relationship stronger. Capital structure and managerial skill findings are unaffected by alternative specifications, omitted factors, industry group bias and endogeneity.

This study sheds fresh light on the essential manager personality trait of managing ability and how it influences complicated corporate decision-making, particularly in the tough environment due to financing constraints and competitive growth. The authors argue that high-ability managers are compelled to use debt financing not only to lessen information asymmetry but also to guarantee that the market finds their superior ability. This work contributes significantly to the managerial ability literature and the capital structure literature supporting signaling theory.

Amidst the growing awareness regarding the social accountability of corporates, the study has attempted to investigate how firm characteristics like size and performance influence corporate social responsibility (CSR) activities in India.

236 Indian firms listed on the National Stock Exchange (Nifty 500 index) have been selected for the empirical analysis. The independent variable firm size has been defined through total assets, operation scale and resource access. Another important factor, firm's performance, is also considered as the independent variable. CSR, the dependent variable, has been measured using Bloomberg's Environmental, Social and Governance (ESG) disclosure scores.

Findings of the dynamic panel data analysis have revealed an inversed U-shape relationship between companies' size and CSR, i.e. CSR participation is positively related with small-sized firms, but as the firms become larger in size, their relationship with CSR becomes negative. A negative relationship has also been found between firm performance and CSR, while the age of the firm exhibits a positive association with CSR participation.

Poor performance of the larger firms suggests that government regulatory bodies need to take strict steps to enhance supervision. Clear regulations are required to be framed and enforced upon large companies to promote consistent participation in CSR. The present study has endeavoured to offer a distinct viewpoint by considering firm size and CSR to be related in a non-linear manner and has brought forward relevant information from the perspective of an emerging economy like India.

This study aims to study the impact of earnings quality on firms’ financial performance.

An unbalanced panel data of 237 small- and medium-sized Portuguese companies from the mold industry, using 2010–2018 yearly data was analyzed. While most studies focus only on earnings management when assessing earnings quality, in this study six proxies for earnings quality are used, namely, accruals quality (a proxy for earnings management), earnings persistence, earnings predictability, earnings smoothness, earnings timeliness and earnings conservatism. Moreover, two proxies of financial performance are considered, the return on assets and the economic value added. An econometric model was estimated using either a fixed-effects or a random-effects specification to account for the individual firm-specific effects and ensure heteroscedasticity corrected estimates.

The results show that managers must be concerned with the quality of reported earnings, as it can affect positively firms’ financial performance, especially regarding accruals quality. Persistence, predictability, smoothness, timeliness and conservatism are shown not to exert significant influence on financial performance in the sample.

This work contributes not only as a literature review on these thematic but also to firms’ managers and stakeholders, who have information that helps them select strategies that guarantee earnings quality and improve firms’ financial performance.

This study proposed an econometric model that studies the relationship between earnings quality (using several proxies for it) and financial performance that can be applied to all companies.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

This study sought to develop an aggregated assessment of the literature on the resource-based view (RBV). The main aim was to map the RBV field based on a systematic literature review (SLR) of 226 academic articles published in refereed journals from 1994 to 2022.

Two bibliometric analysis methods were used: bibliographic coupling and co-citation. These measures are complementary because bibliographic coupling is retrospective in nature and co-citation is forward-looking.

The analysis identified the most influential studies, top-cited articles and journals and six major thematic clusters: RBV, customer orientation and alliance portfolio, resource-based theory, firm performance, entrepreneurial orientation (EO) and dynamic capabilities.

This research was based on a combination of bibliographic coupling and co-citation analysis. The results provide a better understanding of the RBV field’s intellectual structure, which reveals potential new lines of future research.