Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 3 / 6 publications (50.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 21 Oct 2026 07:23 UTC — 22 Oct 2026 03:22 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2026 | All selected publications | 6 | 6 | 3/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2026 | All selected publications | 2 | 6 | 3/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2026 | All selected publications | 2 | 6 | 3/6 | 6/6 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 6 / 6 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-21T07:23:09.631720+00:00 — 2026-10-22T03:22:37.234834+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 6 | 6/6 |
| 2018 | All selected publications | 0 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 0 | 6 | 6/6 |
| 2022 | All selected publications | 0 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 0 | 6 | 6/6 |
| 2025 | All selected publications | 0 | 6 | 6/6 |
| 2026 | All selected publications | 2 | 6 | 6/6 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2026 | 6 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 2 | 2 | 2 | 2/2 | 1.0 | 1.0 | 100.0 | 2/2 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 3 | — | 0 | 3/3 | — | — | — | 0/3 · 0.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
This study explored the bank-specific and macroeconomic factors influencing capital adequacy in South African commercial banks. In this research, a balanced panel data set comprising 11 recapitalized banks was employed, spanning the period from 2008 to 2019. Employing panel regression techniques including OLS, Fixed Effects, Random Effects, and the Generalized Method of Moments (GMM), the analysis examines the influence of profitability (ROA), bank size, leverage, broad money supply, and the central bank’s monetary policy rate on the Capital Adequacy Ratio (CAR). The results indicate that profitability, bank size, leverage, and the broad money supply are critical determinants of capital sufficiency. Banks with increased profitability and increased exposure to the money supply typically demonstrate more robust capital positions. Larger bank size and increased leverage levels negatively affect capital adequacy ratios. The little impact of the delayed CAR signifies minimal persistence in capital buffer methods over time, implying that banks may not significantly depend on prior year capital conditions in their current capital planning. The study highlights the complex nature of capital sufficiency, influenced by microeconomic factors such as size and leverage, as well as macroeconomic indices like the money supply. The findings substantiate the Capital Buffer Theory and furnish critical insights for regulators, bank executives, and policymakers seeking to bolster the resilience of the banking industry in South Africa.
The COVID-19 pandemic triggered a global economic crisis that significantly impacted the South African banking sector, already weakened by a pre-existing recession. While bank profitability and credit quality declined, stock market reactions appeared less severe, indicating a potential disconnect between fundamentals and investor behaviour. This study explores the influence of investor sentiment on credit risk, lending, and performance (ROA) of selected JSE-listed banks during the pandemic, incorporating behavioural finance perspectives. Panel regression analysis reveals that COVID-19 had a significant negative effect on stock, ROA and ROE, driven by heightened uncertainty and rising non-performing loans. Liquidity and capital positively influenced returns and ROE, reflecting investor confidence in resilient banks. Investor sentiment had a weakly positive impact on returns, but a significant negative effect on both ROA and ROE, suggesting that excessive optimism may have led to riskier lending practices and reduced profitability. Larger banks underperformed in terms of returns, likely due to operational complexity during the crisis. These findings highlight the critical role of behavioural factors in shaping financial outcomes during systemic shocks and provide new insights into emerging market banking dynamics under crisis conditions.
This study examined the effect of deposit diversification on the financial performance of Deposit-Taking Savings and Credit Cooperative Societies (DT-SACCOs) in Kenya and evaluated the moderating effect of corporate governance on this relationship. The study adopted a positivist research philosophy and a causal research design. The target population comprised 176 SASRA-licensed DT-SACCOs in Kenya, from which 122 SACCOs with complete financial records for the period 2015–2024 were selected using simple random sampling. Panel data techniques, including fixed-effects and random-effects regression models, were employed to estimate the direct and moderating effects, while hierarchical regression was used to test the moderation hypothesis. The findings revealed that non-withdrawable deposits significantly and positively influenced both surplus and dividend payout after introducing lags, whereas withdrawable deposits had no significant effect on financial performance. The results further established that corporate governance had a positive and significant direct effect on financial performance and significantly strengthened the relationship between deposit diversification and financial performance. The findings provide practical guidance for DT-SACCO managers and policymakers to strengthen stable deposit mobilization and corporate governance as mechanisms for enhancing financial sustainability and institutional performance.
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.
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.
This study examined the effect of deposit diversification on the financial performance of Deposit-Taking Savings and Credit Cooperative Societies (DT-SACCOs) in Kenya and evaluated the moderating effect of corporate governance on this relationship. The study adopted a positivist research philosophy and a causal research design. The target population comprised 176 SASRA-licensed DT-SACCOs in Kenya, from which 122 SACCOs with complete financial records for the period 2015–2024 were selected using simple random sampling. Panel data techniques, including fixed-effects and random-effects regression models, were employed to estimate the direct and moderating effects, while hierarchical regression was used to test the moderation hypothesis. The findings revealed that non-withdrawable deposits significantly and positively influenced both surplus and dividend payout after introducing lags, whereas withdrawable deposits had no significant effect on financial performance. The results further established that corporate governance had a positive and significant direct effect on financial performance and significantly strengthened the relationship between deposit diversification and financial performance. The findings provide practical guidance for DT-SACCO managers and policymakers to strengthen stable deposit mobilization and corporate governance as mechanisms for enhancing financial sustainability and institutional performance.
This paper examines how uninsured deposits influence credit union funding and whether private excess deposit insurance alters the stability, pricing, and lending capacity of uninsured deposits — deposits that exceed the federal deposit insurance limit. Using U.S. credit union Call Report data from 1995–2022, we exploit variation across institution size, insurance regime, and participation in optional private excess deposit insurance. We distinguish between pre-crisis (1995–2007) and post-crisis (2009–2022) periods surrounding the 2008 expansion of federal insurance limits. We document pronounced heterogeneity across the size distribution. For small credit unions, uninsured deposits are limited in scale and are associated with lower loan intensity. In contrast, uninsured deposits play a central funding role for large credit unions, which account for 94% of industry assets and 97% of uninsured deposits. For these institutions, uninsured deposits support lending and command higher funding costs — effects that are significantly moderated by excess deposit insurance, reducing funding costs by approximately 27 basis points during the pre-crisis period. Following 2008, excess insurance participation declines among large institutions but increases modestly among small firms. Overall, excess deposit insurance functions as a partial substitute for federal coverage, stabilizing uninsured funding without increasing delinquency rates — evidence against moral hazard.
This study explored the bank-specific and macroeconomic factors influencing capital adequacy in South African commercial banks. In this research, a balanced panel data set comprising 11 recapitalized banks was employed, spanning the period from 2008 to 2019. Employing panel regression techniques including OLS, Fixed Effects, Random Effects, and the Generalized Method of Moments (GMM), the analysis examines the influence of profitability (ROA), bank size, leverage, broad money supply, and the central bank’s monetary policy rate on the Capital Adequacy Ratio (CAR). The results indicate that profitability, bank size, leverage, and the broad money supply are critical determinants of capital sufficiency. Banks with increased profitability and increased exposure to the money supply typically demonstrate more robust capital positions. Larger bank size and increased leverage levels negatively affect capital adequacy ratios. The little impact of the delayed CAR signifies minimal persistence in capital buffer methods over time, implying that banks may not significantly depend on prior year capital conditions in their current capital planning. The study highlights the complex nature of capital sufficiency, influenced by microeconomic factors such as size and leverage, as well as macroeconomic indices like the money supply. The findings substantiate the Capital Buffer Theory and furnish critical insights for regulators, bank executives, and policymakers seeking to bolster the resilience of the banking industry in South Africa.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |