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Research Article
The Relationship Between Board of Directors Characteristics and Bank Value: Does Bank Loan Quality Matters (Empirical Study on EGX Listed Banks)
Kareem Ahmed Omran*
Issue:
Volume 1, Issue 1, March 2026
Pages:
1-20
Received:
5 September 2025
Accepted:
20 October 2025
Published:
31 January 2026
Abstract: This study examines the relationship between board of directors’ characteristics and bank value and investigates whether bank loan quality mediates this relationship. Data were collected from banks listed on the Egyptian Stock Exchange over a 10-year period (2014–2023). The study uses a Tobin’s Q–based measure as a proxy for bank value. Seven board characteristics are analyzed: board size, CEO duality, board independence, gender diversity, education level, meeting frequency, and CEO experience. Bank loan quality is measured using non-performing loans. The analysis employs the SPSS PROCESS tool with 5000 bootstrap samples to estimate the total, direct, and indirect effects of board characteristics on bank value. Results confirm that bank loan quality significantly mediates the relationship between board characteristics and bank value. Banks with certain board characteristics show different levels of bank value compared to those without these characteristics. When bank loan quality is held constant, the effect of board characteristics on bank value remains significant. This research answers two key questions: How do board characteristics influence bank value? And does bank loan quality transfer the influence of these characteristics on bank value? The study offers practical recommendations for policymakers, bank managers, and investors.
Abstract: This study examines the relationship between board of directors’ characteristics and bank value and investigates whether bank loan quality mediates this relationship. Data were collected from banks listed on the Egyptian Stock Exchange over a 10-year period (2014–2023). The study uses a Tobin’s Q–based measure as a proxy for bank value. Seven board...
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Research Article
Stakeholders, Sustainable Finance and Governance in the Classical Faculties of the University of Yaoundé 1 (Cameroon)
Kana Etoundi Rene Rodrigue Lionel*
Issue:
Volume 1, Issue 1, March 2026
Pages:
21-26
Received:
26 June 2025
Accepted:
21 January 2026
Published:
31 January 2026
Abstract: This scientific reflection questions the low sustainability of financial governance practices within the faculty institutions of the University of Yaoundé 1. The global challenges of university governance call for more virtuous management practices. This is why, in 2017, the Conference of Ministers of Education of the States and Governments of La Francophonie recommended not only the integration of sustainable financing principles into sectoral and sub-sectoral budgetary guidelines for education, but also a transformation of financial management practices in educational institutions. Today, the reality of university governance in Cameroon is quite different. Indeed, the report on medium-term expenditure planning (2020-2022) reveals that Cameroon is struggling to integrate sustainable finance practices into sectoral education governance, particularly in public higher education institutions. So why is it that state university faculties do not integrate the principles of sustainable finance into their day-to-day financial management? Taking the University of Yaoundé 1 as a case study, the methodological approach is hypothetical-deductive. The analysis combines qualitative and quantitative methods. The field survey targeted managers at three levels of intervention in the financial governance chain: institution directors and/or their deputies (N=03), department heads (N=20) and teaching and non-teaching staff (N=85). The results reveal a real lack of understanding of the principles of sustainable finance in the financial governance chain. This lack of knowledge is accompanied by insufficient consideration of extra-financial criteria, such as stakeholders and social issues, in the day-to-day financial management of the faculties of the University of Yaoundé 1.
Abstract: This scientific reflection questions the low sustainability of financial governance practices within the faculty institutions of the University of Yaoundé 1. The global challenges of university governance call for more virtuous management practices. This is why, in 2017, the Conference of Ministers of Education of the States and Governments of La F...
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Research Article
Determinants of Deposit Growth in Selected Private Commercial Banks in Ethiopia
Worku Desalegn Adelegn*
Issue:
Volume 1, Issue 1, March 2026
Pages:
27-36
Received:
1 December 2025
Accepted:
31 December 2025
Published:
6 February 2026
Abstract: This study examines the factors affecting deposit growth in selected private commercial banks in Ethiopia. An explanatory research design was applied using secondary panel data from 2013 to 2022, covering 12 private commercial banks selected through purposive sampling. Data were collected from the National Bank of Ethiopia, the World Bank, and banks’ annual reports . Panel regression techniques are employed, with fixed-effects models and clustered standard errors used as the preferred specification. The results show that customer growth and capital adequacy have a strong and statistically significant positive effect on deposit growth (p < 0.01), while foreign remittance growth is also positively associated with deposits (p < 0.05). Treasury-bill rates exhibit a positive effect in some model specifications (p < 0.10), whereas government expenditure is found to be negatively and significantly related to deposit growth (p < 0.05). In contrast, GDP growth, inflation, and branch expansion do not show robust effects across models. Robustness checks using alternative estimators and diagnostic tests confirm the reliability of the findings. The study contributes to the limited empirical literature on deposit dynamics in Ethiopian private banks by employing a decade-long panel dataset and incorporating additional macroeconomic variables, notably Treasury-bill rates and government expenditure, while providing policy-relevant insights for banks and monetary authorities.
Abstract: This study examines the factors affecting deposit growth in selected private commercial banks in Ethiopia. An explanatory research design was applied using secondary panel data from 2013 to 2022, covering 12 private commercial banks selected through purposive sampling. Data were collected from the National Bank of Ethiopia, the World Bank, and bank...
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Research Article
A Hybrid Genetic Algorithm–analytic Hierarchy Process Approach to Optimal Portfolio Selection: Evidence from the Amman Stock Exchange
Issue:
Volume 1, Issue 1, March 2026
Pages:
37-54
Received:
27 October 2025
Accepted:
26 January 2026
Published:
24 February 2026
Abstract: This study investigates the effectiveness of a hybrid decision-support framework that integrates a Hybrid Genetic Algorithm (HGA) with the Analytic Hierarchy Process (AHP) to identify optimal investment portfolios in the Amman Stock Exchange (ASE). Using daily stock return data for companies listed on the ASE over the period January 1, 2015 to December 31, 2015, the HGA is employed to generate and evolve 10,000 candidate portfolios, each consisting of six stocks. The generated portfolios are evaluated based on the risk–return trade-off, and the efficient frontier is constructed. Subsequently, the AHP is applied to rank the efficient portfolios according to seven evaluation criteria: expected return, risk, beta, liquidity, Sharpe ratio, Treynor ratio, and Jensen’s alpha. The results demonstrate that the proposed HGA–AHP framework effectively identifies portfolios located on the efficient frontier and selects an optimal portfolio that exhibits superior risk-adjusted performance relative to the market benchmark. The hybrid approach successfully addresses nonlinear constraints and discrete asset selection issues that limit traditional optimization techniques. This study contributes empirical evidence from an emerging market and provides a replicable hybrid portfolio optimization framework for investors, portfolio managers, and financial institutions.
Abstract: This study investigates the effectiveness of a hybrid decision-support framework that integrates a Hybrid Genetic Algorithm (HGA) with the Analytic Hierarchy Process (AHP) to identify optimal investment portfolios in the Amman Stock Exchange (ASE). Using daily stock return data for companies listed on the ASE over the period January 1, 2015 to Dece...
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Research Article
Effects of Implementing E-Procurement on Organizational Performance: The Case of African Union
Belayihun Shewangzaw*,
Amana Omer,
Abrham Aydagn
Issue:
Volume 1, Issue 1, March 2026
Pages:
55-77
Received:
14 February 2026
Accepted:
2 March 2026
Published:
10 March 2026
Abstract: This study examined the effect of e-procurement implementation on organizational performance in the African Union. A descriptive and explanatory research design employing both quantitative and qualitative approaches was adopted. The study targeted 230 employees, from which 146 respondents were selected using simple random sampling. Primary data were collected through structured questionnaires and analyzed using descriptive and inferential statistical techniques with SPSS version 26. Validity and reliability tests were conducted to ensure data quality. The findings revealed a statistically significant positive relationship between e-procurement practices and organizational performance. Regression results further confirmed that e-procurement dimensions significantly predict organizational performance. Among the components, e-tendering emerged as the most dominant practice, while e-sourcing, e- payment, and efficiency also demonstrated positive effects on performance outcomes. Overall, the study concludes that effective implementation of e-procurement enhances organizational performance. The study recommends strengthening e-procurement policies, improving stakeholder participation, and creating a supportive institutional environment to sustain performance improvement.
Abstract: This study examined the effect of e-procurement implementation on organizational performance in the African Union. A descriptive and explanatory research design employing both quantitative and qualitative approaches was adopted. The study targeted 230 employees, from which 146 respondents were selected using simple random sampling. Primary data wer...
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Research Article
A Hybrid PSO-SNA Framework for Enhanced Conversion Prediction in Meta Advertising Campaigns
Zaid Kraitem*
Issue:
Volume 1, Issue 1, March 2026
Pages:
78-84
Received:
18 February 2026
Accepted:
2 March 2026
Published:
12 March 2026
Abstract: This study introduces a novel hybrid methodology that integrates Particle Swarm Optimization (PSO) and Social Network Analysis (SNA) to enhance conversion prediction in Meta digital advertising campaigns. Real-world data was collected from four international Meta ad accounts promoting coaching programs, structured across three dimensions: demographic targeting (age, gender), platform placement, and daily performance metrics. Following an initial cleaning and balancing process, a baseline Random Forest classifier was trained, achieving an F1-score of 0.81. PSO was then employed to optimize hyperparameters, resulting in an improved F1-score of 0.83. In parallel, we applied SNA techniques to construct behavioral graphs based on feature similarity and centrality, generating new network-based predictors. Finally, we combined both optimized hyperparameters and SNA-derived features into a hybrid PSO-SNA model. The hybrid model demonstrated superior performance, achieving an accuracy of 0.89, precision of 0.90, recall of 0.90, and an F1-score of 0.87, significantly outperforming previous models. These results underscore the effectiveness of integrating topological behavioral insights with traditional optimization techniques. By bridging swarm intelligence and social graph analysis, this hybrid model offers a scalable and explainable approach for advertisers seeking to maximize conversion rates without altering Meta's black-box algorithms.
Abstract: This study introduces a novel hybrid methodology that integrates Particle Swarm Optimization (PSO) and Social Network Analysis (SNA) to enhance conversion prediction in Meta digital advertising campaigns. Real-world data was collected from four international Meta ad accounts promoting coaching programs, structured across three dimensions: demograph...
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