Search Results (82)

This study examines the influence of ethical leadership on corporate sustainability and financial performance, highlighting the moderating effect of firms’ commitment to the United Nations Sustainable Development Goals (SDGs). Utilizing panel data from 420 automotive companies spanning 2015 to 2024, the analysis applies the System Generalized Method of Moments (GMM) to control for endogeneity and unobserved heterogeneity. All data were gathered from the Refinitiv Eikon Platform (LSEG) and annual reports. Panel GMM regression is used to estimate the relationship to deal with the endogeneity problem. The results reveal that ethical leadership significantly improves corporate sustainability performance—measured by ESG scores from Refinitiv Eikon and Bloomberg—as well as financial indicators like Return on Assets (ROA) and Tobin’s Q. Additionally, firms that demonstrate breadth (the range of SDG-related themes addressed), concentration (the distribution of non-financial disclosures across SDGs), and depth (the overall volume of SDG-related information) in their SDG disclosures gain greater advantages from ethical leadership, resulting in enhanced ESG performance and higher market valuation. This study offers valuable insights for corporate leaders, policymakers, and investors on how integrating ethical leadership with SDG alignment can drive sustainable and financial growth. Full article

This study investigates the relationship between CEO characteristics and firm performance across emerging and developed economies using both panel regression and machine learning techniques. Drawing on Upper Echelons Theory, we examine whether CEO age, tenure, gender, founder status, and appointment origin influence Return on Assets (ROA), Return on Equity (ROE), and market-to-book ratio. We apply the fixed and random effects models for inference and deploy random forest and XGBoost models to determine the feature importance of each CEO trait. Our findings show that CEO tenure consistently predicts improved ROE and ROA, while CEO age and founder status negatively affect firm performance. Female CEOs, though not consistently significant in the baseline models, positively influence market valuation in emerging markets according to interaction models. Firm-level characteristics such as size and leverage dominate CEO traits in explaining performance outcomes, especially in machine learning rankings. By integrating machine learning feature importance, this study contributes an original approach to CEO evaluation, enabling firms and policymakers to prioritise leadership traits that matter most. The findings have practical implications for succession planning, diversity policy, and performance-based executive appointments. Full article

This study aims to analyze the determinants of bank profitability in Angola by employing panel data econometric models, specifically, the Generalized Method of Moments (GMM), to assess the impact of internal and external factors on the financial indicators ROE, ROA, and NIM for the period 2016 to 2023. The results reveal that credit risk, operational efficiency, and liquidity are critical determinants of banking performance. Effective credit risk management and cost optimization are essential for the sector’s stability. Banking concentration presents mixed effects, enhancing net interest income while potentially undermining efficiency. Economic growth supports profitability, whereas inflation exerts a negative influence. The COVID-19 pandemic worsened asset quality, increased credit risk, and led to a rise in non-performing loans and provisions. Reforms implemented by the National Bank of Angola have contributed to strengthening the banking system’s resilience through restructuring and regulatory improvements. The rise of digitalization and fintech presents opportunities to enhance financial inclusion and efficiency, although their success relies on advancing financial literacy. This study contributes to the literature by providing updated empirical evidence on the factors influencing bank profitability within an emerging economy’s distinctive institutional and economic context. Full article

This study investigates the relationship between disclosures related to Sustainable Development Goal 7 (SDG 7) and the financial profitability of Romanian commercial banks during the 2017–2023 period. Using an unbalanced panel dataset of 17 banks and applying fixed-effects regression models, the paper examines how transparency around energy-related sustainability practices influences various dimensions of bank profitability: recurring earning power (REP), loan yield (LY), return on assets (ROA), and return on equity (ROE). Macroeconomic energy indicators, such as the energy intensity level of primary energy (EnInt) and renewable energy consumption (REnC), are also controlled for. The findings indicate that SDG 7.1 disclosures are negatively associated with all profitability measures, except for LY, suggesting potential short-term trade-offs between sustainability transparency and financial outcomes. In contrast, SDG 7.2 disclosures positively impact REP, ROA, and ROE, underscoring the financial relevance of renewable energy financing. SDG 7.a disclosures show no significant relationship with profitability, indicating limited operational involvement in global energy cooperation. Additionally, higher energy intensity negatively affects REP and LY, supporting existing evidence that energy efficiency improves banking performance. These findings have implications for banking strategy, emphasizing the need to align sustainability disclosures with business priorities while recognizing the long-term benefits of green finance and energy efficiency. Full article

The Crayfish Optimization Algorithm (COA) has limitations that affect its optimization performance seriously. The competition stage of the COA uses a simplified mathematical model that concentrates on relations of distance between crayfish only. It is deprived of a stochastic variable and is not able to generate an applicable balance between exploration and exploitation. Such a case causes the COA to have early convergence, to perform poorly in high-dimensional problems, and to be trapped by local minima. Moreover, the low activation probability of the summer resort stage decreases the exploration ability more and slows down the speed of convergence. In order to compensate these shortcomings, this study proposes an Improved Crayfish Optimization Algorithm (ICOA) that designs the competition stage with three modifications: (1) adaptive step length mechanism inversely proportional to the number of iterations, which enables exploration in early iterations and exploitation in later stages, (2) vector mapping that increases stochastic behavior and improves efficiency in high-dimensional spaces, (3) removing the X_shade parameter in order to abstain from early convergence. The proposed ICOA is compared to 12 recent meta-heuristic algorithms by using the CEC-2014 benchmark set (30 functions, 10 and 30 dimensions), five engineering design problems, and a real-world ROAS optimization case. Wilcoxon Signed-Rank Test, t-test, and Friedman rank indicate the high performance of the ICOA as it solves 24 of the 30 benchmark functions successfully. In engineering applications, the ICOA achieved an optimal weight (1.339965 kg) in cantilever beam design, a maximum load capacity (85,547.81 N) in rolling element bearing design, and the highest performance (144.601) in ROAS optimization. The superior performance of the ICOA compared to the COA is proven by the following quantitative data: 0.0007% weight reduction in cantilevers design (from 1.339974 kg to 1.339965 kg), 0.09% load capacity increase in bearing design (COA: 84,196.96 N, ICOA: 85,498.38 N average), 0.27% performance improvement in ROAS problem (COA: 144.072, ICOA: 144.601), and most importantly, there seems to be an overall performance improvement as the COA has a 4.13 average rank while the ICOA has 1.70 on CEC-2014 benchmark tests. Results indicate that the improved COA enhances exploration and successfully solves challenging problems, demonstrating its effectiveness in various optimization scenarios. Full article

This study explores the relationship between firm-level carbon productivity (CRP), home country environmental performance (HCEP), and firm performance—both financial and international—in the global meat exporting industry. While prior research has examined these dynamics in manufacturing sectors, limited attention has been paid to the meat industry, which is both economically significant and environmentally intensive. Using a multiple case study approach, we analyze data from three leading meat-exporting firms—Agrosuper (Chile), BRF (Brazil), and Danish Crown (Denmark)—over the period 2020–2023. CRP is operationalized as the ratio of firm output to CO₂ emissions, while HCEP is measured by national emissions per million USD of GDP. Financial performance is assessed via return on assets (ROA), and international performance through export intensity. Our findings reveal a nuanced relationship between CRP and firm performance. Contrary to theoretical expectations, a higher CRP does not consistently translate into improved financial performance, suggesting potential trade-offs between sustainability investments and profitability. However, a positive association is observed between CRP and international performance, particularly in firms operating within environmentally advanced countries. These results highlight the importance of home country environmental contexts in shaping firms’ global competitiveness. This research contributes to the literature by introducing CRP as a firm-level metric in the meat industry and by emphasizing the moderating role of HCEP. The findings offer practical implications for policymakers and managers seeking to align environmental responsibility with economic and international performance goals. Full article

Transparency in ESG financial materiality disclosure by corporations is now in doubt due to the inconsistent ESG framework that governs ESG disclosures, particularly in developing nations like South Africa. This is evident in the financial performance of banks and manufacturing firms as a result of the higher rate of susceptibility to ESG issues. Hence, this study empirically investigated the effect of ESG financial materiality disclosure on the financial performance of banks and manufacturing firms in South Africa from 2015 to 2024. Also, the moderating role of ESG transparency on the relationship between ESG financial materiality disclosure and financial performance was investigated. Descriptive analysis, a correlation matrix, and panel regression analysis were employed for analysis purposes. The financial metrics include ROA, ROE, and Tobin’s Q, while ESG financial materiality disclosure and the ESG disclosure score of the firms were the independent variable and moderating variable, respectively. The results show that ESG financial materiality exerts a significant adverse impact on ROA and ROE but an insignificant positive effect on Tobin’s Q in banks. For manufacturing firms, the impact is insignificant and negative on ROA, ROE, and Tobin’s Q. Also, the interactive effect of transparency insignificantly weakens the effect of ESG financial materiality disclosure on financial performance in both banks and manufacturing firms. This concludes that the transparency in ESG financial materiality disclosure is not sufficient to improve financial performance in both sectors but should be integrated in the core business objectives of firms. Also, it suggests that over-disclosure and greenwashing of ESG reports should be avoided. Full article

In order to evaluate the impact of k-means clustering on portfolio optimization, this study groups enterprises based on profitability, liquidity, and solvency indicators. The study confirms the positive correlation between risk, return, and risk-adjusted performance through an analysis of historical financial records. After the companies were divided into two groups, equal-weighted portfolios were created using these groupings. Although they produced higher returns, cluster 1 portfolios, which included more risky companies, also showed more volatility. Cluster 0 portfolios, on the other hand, offered less risk and more consistent results. Portfolios clustered by ROA, OCFM, and GPM outperformed the market benchmark and produced the highest returns adjusted for risk, according to Sharpe Ratio analysis. Furthermore, the study emphasizes that although solvency and liquidity metrics play a role in portfolio selection, increased liquidity does not always translate into improved risk-adjusted performance. In terms of methodology, Silhouette Analysis outperformed the Elbow technique in determining the optimal number of clusters. All things considered, the results show how data-driven clustering techniques may be used to align portfolio strategies to investors’ risk tolerances. Full article

In natural resource-dependent economies, global resource price volatility makes financial systems more vulnerable to economic shocks. The relationship between natural resource rent and bank stability lies in how fluctuations in resource revenues can affect financial institutions’ stability. The purpose of this paper is twofold. First, it explores the effect of natural resource rent (NRR) on bank stability (BS) in the Middle East and North Africa (MENA) region. Second, it examines whether institutional quality (IQ) moderates the association between BS and NRR. To achieve these goals, we used a sample of 68 conventional banks located in the MENA region between 2005 and 2020 and performed the System Generalized Method of Moments (SGMM) as an econometric approach. The empirical findings show that NRR is negatively and significantly associated with BS, while IQ significantly enhances BS in the MENA region. Additionally, the outcomes support evidence that the MENA banks benefit from an interaction between IQ and NRR. This result was confirmed for both the Z-ROA and Z-ROE as measures of BS. The results of this paper could have several useful applications for policymakers and bankers. Policymakers should prioritize strengthening institutional frameworks to mitigate the adverse effects of resource dependence on financial stability. In addition, bankers are invited to focus on improving institutional quality by fostering an institutional environment, including compliance with anti-corruption standards and coordination with regulatory bodies to boost financial resilience. Full article

Regenerative organic agriculture (ROA) combines ecological and organic principles to promote soil health, biodiversity, and long-term sustainability. This narrative review explores the connection between soil quality, food nutritional value, and human health, highlighting how ROA can enhance phytochemical content and reduce harmful residues in plant-based foods. Empirical studies report increases in vitamin C, zinc, and polyphenols in crops such as leafy greens, grapes, and carrots grown under regenerative systems, along with reductions in nitrates and pesticide residues. We summarize recent literature (2000–2025) that links soil-driven improvements in food composition to antioxidant activity and potential health benefits. By addressing current research gaps, this review supports the role of ROA in building resilient food systems and preventing chronic disease. Full article

Measuring financial performance is pivotal not only for assessing a firm’s current health but also for informing strategic decisions that shape its long-term trajectory. This study investigates how macroeconomic volatility affects the firm profitability across five major sectors in Türkiye—industrial manufacturing, food, beverage and tobacco, chemicals and plastics, technology, and energy—during the turbulent period from 2016 to 2023. Using return on assets (ROA) and return on equity (ROE) as performance indicators, we apply panel data regression to test the impact of inflation, interest rates, unemployment, and a novel Macroeconomic Stress Index (MSI), which combines inflation and exchange rate volatility. The results reveal significant sectoral differences: firms in chemicals and manufacturing outperformed others in ROA, likely benefiting from export incentives and scale efficiencies, while energy and food sectors underperformed, constrained by regulations and cost rigidity. Notably, MSI showed a consistent and significant positive effect on both ROA and ROE, suggesting that many firms responded to macroeconomic stress by restructuring operations and improving efficiency. In contrast, interest rates had a strong negative effect on profitability, confirming the sensitivity of firms to financing costs. These findings underscore the need for targeted sector-level policy support and highlight the importance of internal adaptive capabilities in maintaining the firm’s performance under sustained economic stress. Full article

The present study examines the relationship between the cash conversion cycle (CCC) and profitability in major service sectors in Greece, including hotels, education, healthcare, transfer—rentals, and information technology. Using financial data from 343 public limited companies for the year 2023, the research applies descriptive statistics, Pearson correlation analysis, and ANOVA to evaluate how CCC components affect profitability, measured through return on assets (ROA). The results indicate that firms across all sectors maintain a negative CCC, suggesting efficient liquidity management, with the education sector exhibiting the most negative CCC due to upfront tuition payments. Additionally, the study finds a significant positive correlation between CCC and ROA, implying that firms with longer negative CCC values tend to achieve higher profitability. However, firm size, measured by total assets and sales, does not appear to influence CCC efficiency or profitability. These findings underscore the importance of industry-specific financial strategies and highlight the role of CCC optimization in enhancing financial performance. The study contributes to the literature on working capital management and provides practical implications for improving liquidity and profitability in service-oriented firms. Full article

The problem of predicting profitability is exceptionally relevant for investors and company owners making decisions about investment and business development. The global literature contains a number of studies where researchers predict the profitability of firms using various methods, including modern machine learning. However, these works hardly take advantage of panel data. This paper takes advantage of additional capabilities offered by panel data and proposes hybrid forecasting methods based on panel data, which allow significantly improving the accuracy of predicting the profitability. Our calculations show that when predicting the profitability, investors and company owners should take into account the profitability of the previous years and the trend in its change. The work shows that this approach can be successfully applied to high-tech companies whose profitability is characterised by increased volatility. Prediction forecasting includes STL-decomposition of time series, regression with random effects and machine learning (LSTM and CatBoost), and clustering. The training sample includes 1811 companies and data for 2013–2018 (panel data, 10,866 observations). The test sample contains data for these companies for 2019. As a result, the authors propose an approach significantly improving the accuracy of predicting ROA and ROE based on the panel nature of the data. The panel data allowed using the profitability of the previous years in forecast models and applying the STL-decomposition of the profitability of the previous years into three variables (Trend, Seasonal, and Residual), considerably improving the quality of the constructed forecast models (STL-CatBoost, STL-LSTM, and STL-RE hybrid models). Full article

This study investigates the influence of Environmental, Social, and Governance (ESG) disclosure on the profitability of Saudi-listed non-financial firms in the context of Saudi Vision 2030. The study uses a sample of 100 non-financial organizations from 2019 to 2023 (500 firm-year observations). This study uses panel data analysis and a random-effects regression model to examine the relationship between ESG disclosure and firm profitability as assessed by return on assets (ROA). To assess ESG disclosure, this study developed a comprehensive ESG disclosure index based on worldwide ESG guidelines and Saudi-related regulations. The regression results show a significantly positive relationship between ESG disclosure and firm profitability, emphasizing the financial benefits of corporate transparency and sustainability. This finding is consistent with the stakeholder theory, implying that firms with strong ESG commitments boost investor trust, improve risk management, and increase operational efficiency. Thus, this study adds to the ESG literature by presenting empirical evidence from Saudi Arabia, a growing country that is undergoing regulatory transition. Additionally, this study’s notable contribution is the development of a comprehensive ESG disclosure index tailored for the Saudi corporate landscape, integrating global reporting standards with local regulatory requirements. This index enhances the assessment of ESG transparency and offers a thorough tool for examining business sustainability strategies. The results offer substantial insights for policymakers, investors, and corporate leaders, emphasizing the significance of ESG in sustainable financial performance. Full article

The internationalization process helps firms accumulate business knowledge and experience; however, firms also enjoy the benefit of decreasing risk due to diversification. The Taiwanese food industry has encountered some difficulties in internationalization, including insufficient production capacity, high tariffs, the lack of long-term planning by the government, and inadequate support from internal organizations. Overall, it is relatively problematic for the food industry to achieve internationalization, and Environmental, Social, and Governance (ESG) is the trend of sustainable development for enterprises to fulfill. This paper empirically explores the joint impact of the degree of internationalization and ESG ratings on the financial performance of the Taiwanese food industry from 2015 to 2021. Our empirical results found that international diversification and ESG performance have joint positive and significant effects on the return on assets (ROA), return on equity (ROE), and return on sales (ROS) of the food industry, respectively. This means that the higher the internationalization of overseas companies in the food industry, the better the ESG performance would significantly improve its financial performance. Full article