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: 90 / 93 publications (96.8%). 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 00:14 UTC — 21 Oct 2026 07:23 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.
86 / 93 with data · 7 missing or unmatched. Percentages use all 93 selected publications.
86 / 93 with data · 7 missing or unmatched. Percentages use all 93 selected publications.
93 / 93 with data · 0 missing or unmatched. Percentages use all 93 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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2015 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| 2020 | All selected publications | 13 | 13 | 13/13 | 13/13 |
| 2021 | All selected publications | 11 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| 2023 | All selected publications | 13 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| 2025 | All selected publications | 6 | 6 | 5/6 | 6/6 |
| 2026 | All selected publications | 4 | 4 | 2/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 20 | 6 | 6/6 | 6/6 |
| 2015 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 22 | 7 | 7/7 | 7/7 |
| 2017 | All selected publications | 11 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 29 | 10 | 10/10 | 10/10 |
| 2020 | All selected publications | 17 | 13 | 13/13 | 13/13 |
| 2021 | All selected publications | 36 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| 2023 | All selected publications | 28 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 6 | 7 | 7/7 | 7/7 |
| 2025 | All selected publications | 1 | 6 | 5/6 | 6/6 |
| 2026 | All selected publications | 1 | 4 | 2/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 46 | 6 | 6/6 | 6/6 |
| 2015 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2016 | All selected publications | 61 | 7 | 7/7 | 7/7 |
| 2017 | All selected publications | 23 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 10 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 56 | 10 | 10/10 | 10/10 |
| 2020 | All selected publications | 33 | 13 | 13/13 | 13/13 |
| 2021 | All selected publications | 73 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 14 | 10 | 10/10 | 10/10 |
| 2023 | All selected publications | 37 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 13 | 7 | 7/7 | 7/7 |
| 2025 | All selected publications | 1 | 6 | 5/6 | 6/6 |
| 2026 | All selected publications | 1 | 4 | 2/4 | 4/4 |
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 93 / 93 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): 2026-10-21T00:14:27.766849+00:00 — 2026-10-21T07:23:09.631720+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 | 4 | 93 | 93/93 |
| 2018 | All selected publications | 12 | 93 | 93/93 |
| 2019 | All selected publications | 20 | 93 | 93/93 |
| 2020 | All selected publications | 17 | 93 | 93/93 |
| 2021 | All selected publications | 42 | 93 | 93/93 |
| 2022 | All selected publications | 63 | 93 | 93/93 |
| 2023 | All selected publications | 47 | 93 | 93/93 |
| 2024 | All selected publications | 66 | 93 | 93/93 |
| 2025 | All selected publications | 63 | 93 | 93/93 |
| 2026 | All selected publications | 31 | 93 | 93/93 |
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 |
|---|---|
| 2013 | 1 |
| 2014 | 6 |
| 2015 | 2 |
| 2016 | 7 |
| 2017 | 1 |
| 2018 | 2 |
| 2019 | 10 |
| 2020 | 13 |
| 2021 | 11 |
| 2022 | 10 |
| 2023 | 13 |
| 2024 | 7 |
| 2025 | 6 |
| 2026 | 4 |
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 | 3 | 12 | 19 | 3/3 | 4.0 | 1 | 100.0 | 3/3 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 56 | 111 | 237 | 56/56 | 2.09 | 1 | 71.7 | 53/56 · 94.6% |
| International Journal of Research in Business and Social Science SSBFNET | 34 | 63 | 120 | 34/34 | 1.85 | 1.0 | 52.9 | 34/34 · 100.0% |
* Percentage among publications with a known citation count.
The main purpose of this study is to measure up to what extent the independent factors defined by capital adequacy ratio, non-performing loans ratio, cost-income ratio, liquidity ratio, and loans-to-deposits ratio impact the financial performance of sixteen commercial banks operating in the United Arab Emirates using panel data for the period of 2013-2019. The secondary data was collected from banks and examined by applying standard descriptive statistics and the random effect model for hypothesis testing. It is concluded from the regression outcomes that non-performing loans ratio and cost-income ratio have a significant negative impact on commercial banks profitability in the United Arab Emirates, while capital adequacy ratio, liquidity ratio, and loans -to-deposits ratio all have a very weak positive relationship on the return on assets but they are not determinants of bank’s profitability due to the insignificant statistical impact on it. It is therefore suggested that to enhance financial performance and minimize the risk of non-performing loans in the future, banks must watch very carefully the loans’ performance and analyze thoroughly the clients’ credit history and ability to pay back their debts prior to any approval of loan applications. Furthermore, banks should continuously improve their assets utilization, liquidity, and techniques of managing operating costs, improve the impact of capital adequacy, and the use of deposits for lending activities from a weak positive impact to a significant positive impact on their profitability. The researchers recommend that future studies on credit risk management influence on banks’ financial performance should consider more independent variables and longer periods of study such as twenty or thirty years to have more accuracy and generalized results.
The aim of the empirical study is to investigate credit risk determinants in banking sectors across three kinds of South Asian economies. An accumulated sample of 105 unbalanced panel data of financial firms over the period of 2000-2015, by applying General Method of Moment (GMM) estimation techniques one-step at the difference in order to identify factors influencing credit risk. This study is inspired by two broad categories of explanatory variables which are bank-specific and macroeconomic. Bank-specific factors influencing unsystematic risk, while macroeconomic factors promoting systematic risk. The study uses a proxy of non-performing loans for credit risk in banking sectors of Pakistan, India, and Bangladesh. The empirical results have been found aligned with theoretical arguments and literature as expected. In comparison, NPLs in Pakistan is greater than India and Bangladesh, while India has the lowest ratio of non-performing loans. The study documents that bank-specific factors (inefficiency, profitability, capital ratio and leverage) have a significant contribution towards credit risk. Further, the study also finds a significant impact of macroeconomic variables on non-performing loans. While, the result in the case of Bangladesh predicts contradictions that have no significant effect on non-performing loans at various levels. The overall results indicate that credit risk is not influenced by only external factors but also affect by internal factors like bad management and skimping etc.
This study examines the influence of liquidity on the profitability of Iraqi commercial banks. Five banks based in Iraq namely: North bank, Iraqi Islamic bank, Sumer bank, Dar Es-Salam bank and Babylon bank randomly selected and analyzed for the current study over the period 2005 to 2013. Moreover, annual reports of these banks have studied and the main ratios of profitability and liquidity were calculated. These reports are available at Iraqi Stock Exchange site. The variables that were identified as independent for liquidity were, loan deposit ratio, deposit asset ratio and cash deposit ratio, while return on assets as dependent variable for profitability. The Ordinary Least Square (OLS) model used to examine the impact of liquidity on profitability. The study observes that any increase in liquidity ratios as above mentioned will lead return on asset to increase as well. Depending on this study it could be better for Iraqi banks to keep a balance between liquidity and profitability.
The aim of our research is to investigate the relationship between risk management, corporate governance and performance in lending institutions. Mainly, this research seeks to examine the effect of risk management and some board’s features on financial performance. Empirical analyses are conducted from a sample of 17 Tunisian lending institutions over the period 2002-2011 using an OLS regression. The study shows that board size affect performance significantly. Most importantly, the existence of a risk committee within the institution has a negative and significant effect on performance.
In this study, we aimed to explain the influencing factors of interest rate risk in Turkish banking sector. Within this scope, 20 deposit banks in Turkey were evaluated. Furthermore, annual data for the periods between 2006 and 2015 was analyzed by using panel logit method. According to the results of this analysis, it was identified that 2 explanatory variables affect interest rate risk of Turkish banks. First of all, it was determined that banks, which have higher amount of deposits, are exposed to higher amount of interest rate risk. In addition to this situation, it was also defined that there is a negative relationship between the amount of capital and interest rate risk. As a result of this issue, it was recommended that Turkish banks should increase capital amount in order to manage interest rate risk more effectively.
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.
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 paper focuses on a classic policy trade-off by unraveling the role of financial deregulation in driving financial stability and exploring how the role of regulatory quality can affect this relationship. To this end, this study uses a balanced panel dataset of 73 countries across a period of ten years starting from 2014. The empirical specification utilizes a two-step System GMM approach, accounting for both endogeneity, unobserved heterogeneity issues, and persistence in financial stability. Specifically, financial stability is measured by non-performing loans (NPLs), which represent the level of risk exposure of national banking sectors. The findings reveal that financial freedom leads to higher level of financial instability, proving theoretical predictions of the excessive risk-taking behavior of lending institutions encouraged with financial deregulation. Furthermore, the interaction term between financial freedom and regulatory quality is statistically significant, suggesting that financial deregulation can be compensated by the quality of regulatory environment. The role of the GDP per capita variable used for stabilizing the findings is significant as it represents the resilience of more developed economies. The implications of the results are complex. In a more institutional context, this finding suggests that financial stability is not a direct function of financial freedom but is conditional on institutional capability. Hence, high regulatory quality can mitigate the instability caused by financial freedom, thereby enabling a balanced approach.
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 |