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Maintaining adequate liquidity while preserving profitability remains a central challenge for commercial banks because liquid assets strengthen resilience but typically generate lower returns than loans and other earning assets. This study investigates the effect of liquidity on the profitability of U.S. commercial banks using 8,000 quarterly bank observations for 2010–2024. Profitability is measured by return on assets (ROA), with return on equity (ROE) used for robustness, while liquidity, capital adequacy, the loan-to-asset ratio, and bank size are modeled as explanatory variables. Pooled OLS, fixed-effects, and random-effects estimators are compared, and diagnostic tests support a two-way fixed-effects model with standard errors clustered by bank and quarter. The preferred estimates show that a one-percentage-point increase in the liquidity ratio reduces annualized ROA by 0.0183 percentage points (SE = 0.0031; p < 0.001). A one-standard-deviation rise in liquidity, equal to 5.52 percentage points, lowers ROA by approximately 0.101 percentage points, representing 9.2% of the sample mean ROA of 1.097%. Capital adequacy increases ROA by 0.0530 percentage points, and the loan-to-asset ratio increases it by 0.0148 percentage points, both at p < 0.001, whereas bank size is insignificant (β = 0.1008; p = 0.352). The ROE robustness model also yields a negative liquidity coefficient of −0.1074 (p < 0.001). The findings confirm a measurable liquidity–profitability trade-off and support risk-sensitive liquidity regulation that protects financial stability without encouraging persistently excessive holdings of low-yield liquid assets.

Monitoring and Evaluation (M&E) are fundamental processes that provide administrators, policymakers, and stakeholders with methods for learning from experience and improving implementation through the reallocation of resources. However, the success of these interventions depends heavily on effective project monitoring and evaluation (M&E) practices. This study therefore examined the effect of project monitoring and evaluation practices on the success of the rural school feeding program in Rutsiro District, Rwanda. The specific objectives were to determine the effect of an M&E baseline survey on the success of the rural school feeding program in Rutsiro District; analyze the effect of M&E planning on program success; assess the effect of M&E data management on program success; and evaluate the effect of M&E stakeholder involvement on program success. The study adopted both the Theory of Change and Utilization-Focused Evaluation. It used descriptive and correlational research designs and adopted a census approach involving 103 respondents, including 89 teachers, 10 staff members, two representatives of school feeding committees at the school level, and two SEIs. Data were collected through questionnaires, interviews, and document reviews. A pilot test was conducted with 10 respondents to determine the instrument's ability to produce consistent results over time. Data were analyzed using descriptive and inferential statistics, including correlation and regression analyses. The findings revealed that all M&E components (baseline survey, planning, data management, and stakeholder involvement) had a strong and significant positive influence on program success. Respondents showed high levels of agreement, indicating that effective M&E practices improve decision-making, resource allocation, accountability, and overall program performance. The study concluded that well-implemented M&E systems are essential for enhancing the effectiveness, sustainability, and impact of rural school feeding programs. Based on these findings, the study recommends strengthening baseline surveys, improving M&E planning frameworks, enhancing data management systems, promoting active stakeholder involvement, and ensuring adequate resource allocation to support long-term program success.

Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.

This paper aims to develop a conceptual and measurement framework for assessing environmental, social and governance (ESG) disclosure quality in Nigerian banks. It also aims to demonstrate how ESG disclosure quality can be distinguished from ESG disclosure quantity, ESG performance, ESG practices, ESG ratings and sustainability reporting. We employed a conceptual review and framework development approach by synthesising stakeholder theory, institutional theory, Nigerian sustainable banking regulation, international sustainability reporting standards and related banking literature. The materials analysed include the CBN Sustainable Banking Principles, SEC Sustainable Financial Principles, NGX Sustainability Disclosure Guidelines, Nigeria’s IFRS Sustainability Disclosure Standards adoption roadmap, IFRS S1/S2, GRI, TCFD, PCAF, the Basel Core Principles for Effective Banking Supervision and literature on ESG disclosure, banking risk, financial stability and disclosure quality. The main findings of the study demonstrate that: (i) ESG disclosure quality is a distinct construct; and (ii) bank ESG disclosure quality should be assessed across environmental, social and governance dimensions. The paper proposes the ESG Disclosure Quality Index framework which provides a graded 0–5 scoring scale and three empirical model specifications for future panel data studies. The framework provides a basis for assessing ESG disclosure quality and examining its relationship with bank-level outcomes in Nigeria and comparable emerging market banking systems.               

Studies on the impact of digitalisation on bank credit allocation are relatively scarce. Digital technologies have a significant impact on economic growth, the labour market, commodity and asset prices, and international trade. The recent surge in innovation and digitalisation within the financial sector has brought about tremendous changes in bank business models and credit distribution, significantly affecting economic growth. Digital transformation has led to a new banking business model of collaboration between emerging Fintechs and conventional commercial banks, often called a “partnership model”. Here, the banking system is viewed as the evolutionary outcome of monetary financial institutions, constantly adapting to technological change. This ongoing evolution has determined the pattern of credit allocation, ultimately shaping its effects on economic growth. Drawing upon authoritative primary data and sector-specific lending indicators, this study seeks to advance existing scholarly research regarding the impact of digital transformation on bank credit allocation. The contribution of this research stems from comparing the digital transformation of banking systems in the UK and Denmark and examining how digitalisation has led to divergent trajectories in bank credit allocation. The study explores credit allocation under the digital transformation of banking and its effect on overall economic growth. In this sense, bank credit allocation extends beyond traditional industrial firms to reach various other sectors of the economy. Specifically, this research demonstrates how technological advancements in the banking sector directly impact overall economic performance, drawing on empirical evidence from the UK and DK as selected case studies. Empirical evidence demonstrates that bank lending has prioritised credit for financial market trading and real estate mortgages at the expense of the productive sector. This is particularly evident in the ever-growing volume of lending directed toward already existing assets. The prevalence of non-productive credit effectively illustrates that the banking system is increasingly driving the financialisation of the economy.  

Maintaining adequate liquidity while preserving profitability remains a central challenge for commercial banks because liquid assets strengthen resilience but typically generate lower returns than loans and other earning assets. This study investigates the effect of liquidity on the profitability of U.S. commercial banks using 8,000 quarterly bank observations for 2010–2024. Profitability is measured by return on assets (ROA), with return on equity (ROE) used for robustness, while liquidity, capital adequacy, the loan-to-asset ratio, and bank size are modeled as explanatory variables. Pooled OLS, fixed-effects, and random-effects estimators are compared, and diagnostic tests support a two-way fixed-effects model with standard errors clustered by bank and quarter. The preferred estimates show that a one-percentage-point increase in the liquidity ratio reduces annualized ROA by 0.0183 percentage points (SE = 0.0031; p < 0.001). A one-standard-deviation rise in liquidity, equal to 5.52 percentage points, lowers ROA by approximately 0.101 percentage points, representing 9.2% of the sample mean ROA of 1.097%. Capital adequacy increases ROA by 0.0530 percentage points, and the loan-to-asset ratio increases it by 0.0148 percentage points, both at p < 0.001, whereas bank size is insignificant (β = 0.1008; p = 0.352). The ROE robustness model also yields a negative liquidity coefficient of −0.1074 (p < 0.001). The findings confirm a measurable liquidity–profitability trade-off and support risk-sensitive liquidity regulation that protects financial stability without encouraging persistently excessive holdings of low-yield liquid assets.

This study examines whether risk asset exposure affects the financial performance of commercial banks in Cameroon, a bank-dominated economy of the Central African Economic and Monetary Community (CEMAC). Risk asset exposure is measured by lending intensity (the loan-to-deposit ratio) and credit expansion (annual loan growth), and performance by return on assets (ROA). The data form a balanced panel of ten commercial banks over 2014–2024, compiled from the prudential reporting system of the Central African Banking Commission (COBAC) as published by Cameroon's National Economic and Financial Committee. Bank fixed-effects regressions with bank-clustered standard errors are complemented by a wild-cluster bootstrap suited to few clusters, Driscoll–Kraay standard errors, lagged regressors, panel Granger non-causality tests and a within–between (Mundlak) decomposition that separates changes in a bank's own exposure from persistent differences between banks. The main findings are that (i) neither lending intensity nor credit expansion is significantly associated with profitability in any specification (bootstrap p = 0.81 and 0.30), and the confidence intervals exclude effects larger than about one percentage point of ROA; (ii) lending intensity is unrelated to profitability both within banks over time and between banks (between-effect bootstrap p = 0.88); and (iii) the COVID-19 years of 2020–2021 were associated with ROA about 0.70 percentage points lower (bootstrap p = 0.009). The results indicate a limited role for lending exposure, while significant bank fixed effects and the COVID-19 coefficient point to persistent bank heterogeneity and common systemic shocks. Because the sample comprises ten banks under a single regulator, the findings should be interpreted with caution.

Monitoring and Evaluation (M&E) are fundamental processes that provide administrators, policymakers, and stakeholders with methods for learning from experience and improving implementation through the reallocation of resources. However, the success of these interventions depends heavily on effective project monitoring and evaluation (M&E) practices. This study therefore examined the effect of project monitoring and evaluation practices on the success of the rural school feeding program in Rutsiro District, Rwanda. The specific objectives were to determine the effect of an M&E baseline survey on the success of the rural school feeding program in Rutsiro District; analyze the effect of M&E planning on program success; assess the effect of M&E data management on program success; and evaluate the effect of M&E stakeholder involvement on program success. The study adopted both the Theory of Change and Utilization-Focused Evaluation. It used descriptive and correlational research designs and adopted a census approach involving 103 respondents, including 89 teachers, 10 staff members, two representatives of school feeding committees at the school level, and two SEIs. Data were collected through questionnaires, interviews, and document reviews. A pilot test was conducted with 10 respondents to determine the instrument's ability to produce consistent results over time. Data were analyzed using descriptive and inferential statistics, including correlation and regression analyses. The findings revealed that all M&E components (baseline survey, planning, data management, and stakeholder involvement) had a strong and significant positive influence on program success. Respondents showed high levels of agreement, indicating that effective M&E practices improve decision-making, resource allocation, accountability, and overall program performance. The study concluded that well-implemented M&E systems are essential for enhancing the effectiveness, sustainability, and impact of rural school feeding programs. Based on these findings, the study recommends strengthening baseline surveys, improving M&E planning frameworks, enhancing data management systems, promoting active stakeholder involvement, and ensuring adequate resource allocation to support long-term program success.

Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.

The study was directed by the following specific objectives: (i) to examine the impact of the result-based approach on the performance of the National Agriculture Insurance Scheme, and (ii) to analyze the effect of the participatory approach on the performance of the scheme, and (iii) to investigate the role of the reflexive approach in enhancing the program’s outcomes. The theoretical framework drew on decision-making theory, agricultural insurance theory, and contingency theory. The target group for this study comprises roughly 1,463 people. From this group, a stratified sampling technique was been employed to select 313 respondents. Information for the research obtained via questionnaires, interviews, and document analysis, including monthly district reports. The instruments were pilot-tested, resulting in a Cronbach’s alpha of 0.94, which confirms strong reliability. Data analysis involved descriptive and inferential statistics, specifically correlation and regression at a 0.05 significance level, with the assistance of SPSS Version 28. Ethical standards was upheld by securing informed consent from participants and ensuring the confidentiality of all responses.