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: 10 / 10 publications (100.0%). 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 00:22 UTC — 21 Oct 2026 07:22 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.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 14 | 10 | 10/10 | 10/10 |
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 10 / 10 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): 2026-10-21T00:22:03.863736+00:00 — 2026-10-21T07:22:45.980505+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 | 10 | 10/10 |
| 2018 | All selected publications | 0 | 10 | 10/10 |
| 2019 | All selected publications | 0 | 10 | 10/10 |
| 2020 | All selected publications | 0 | 10 | 10/10 |
| 2021 | All selected publications | 0 | 10 | 10/10 |
| 2022 | All selected publications | 1 | 10 | 10/10 |
| 2023 | All selected publications | 1 | 10 | 10/10 |
| 2024 | All selected publications | 2 | 10 | 10/10 |
| 2025 | All selected publications | 6 | 10 | 10/10 |
| 2026 | All selected publications | 4 | 10 | 10/10 |
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 |
|---|---|
| 2022 | 10 |
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 Finance & Banking Studies SSBFNET | 3 | 1 | 2 | 3/3 | 0.33 | 0 | 33.3 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 7 | 9 | 12 | 7/7 | 1.29 | 1 | 85.7 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
This study examines the link between bank performance and bank stability in the context of African countries. Using the Augmented Mean Group (AMG) estimator and panel data from 16 selected African countries covering the period 2002–2019, this study considers whether the banking sector's performance influences the banking system's financial stability. The findings reveal a significant positive long-run relationship between ROA and financial stability. This was the case when the AMG estimator was employed and when the CCEMG was employed to check for robustness. Inflation was initially negative and insignificant but a highly significant determinant when a more robust method (CCEMG) was used. Economic growth has a negative relationship using both estimators but is insignificant, while trade openness and non-interest income had insignificant coefficients in both estimators. The granger causality results show a one-way causality established to bank stability in the case of bank performance and trade openness. In addition, there was a non-causal relationship between bank stability, non-interest income and inflation as against a double-track causation between bank stability and economic growth. African countries should strive to improve bank performance to enhance the stability of the sector.
This study examines the influence of macroeconomic factors, namely Inflation, Gross Domestic Production (G.D.P.) and changes in oil price and Bank-Specific Factors such as capital, asset size, liquidity risk, loan and deposit on bank profitability as measured by return on equity (R.O.E.) and net profit ratio (NPR) during the period of oil price decline, 2013-2017. The top 7 commercial banks were chosen as a sample of the study based on the availability of the data and the possible influence it can contribute to representing Oman's banking industry. The quantitative approach utilized appropriate statistical tools to analyze and interpret the secondary data gathered, including descriptive statistics, panel regression, Pearson correlation, and correlation matrix. Key findings of the study revealed no significant relationship between macroeconomic factors and the return on equity. There is also no significant relationship between macroeconomic factors and the net profit ratio. On the other hand, bank-specific factors significantly correlate return on equity and the net profit ratio. The study's findings contribute to the bank's management, economic policymakers, a research body, and academia in distinguishing the best indicator for a bank's profitability influenced by macroeconomic and bank-specific factors.
The paper’s purpose was to assess whether the effects on the regulatory capital of the ECL model in European banks differs among those that adopted IRB or standardized approaches to credit risk management. The empirical tests revealed that there was a significant reduction in the level of capita buffers of European banks when the IFRS 9 was first adopted, and that this reduction was more pronounced among banks using a standardized approach to credit risk than for those that relied on an IRB approach. Further testing confirmed the premise that there was an underestimation of capital requirements in the period prior to the adoption of the ECL. The study fills a gap in literature, by evaluating the difference in the impact of adopting the ECL model on the banking system, as a function of the credit risk management approach for capital purposes. The assessment of what happened in the European banking system can be used as a guidance to other jurisdictions still in transition to the ECL model.
The African farming sector suffers from insufficient finance. Climate changes and socio-political issues hold down the required production level while food on the continent is still inadequate, with more vulnerable people on the one side. On the other side, credit institutions need reasons and guarantees to raise their risk-taking level (financial benefits). Then, this study tries to conciliate those two sides with new shreds of evidence by demonstrating the short and long-run effects of agricultural production on bank sustainability in 40 Sub-Saharan African countries. The study used different agro-production factors (Food and Cereal production factors), bank stability proxies (Liquidity Ratio, NPLs, LLRs), and bank profitability proxies (ROA and ROE). The GMM, DFE, and FMOLS models were used for short (with the 2010-2019 dataset) and long-run analysis (with the 1970-2018 dataset). The results demonstrated that agricultural production increases bank stability and profitability but reduces bank risks. The study concludes that farming finance increases agro-production and stabilizes banks (win-win). Governments, via central banks, should encourage commercial banks to increase bank risk-taking levels to sustain their banking system, increase farming production, and improve food security.
This paper examined bank-specific performance indicators and macroeconomic factors affecting the short-term financing obligation of Nigerian banks from 2010 to 2019. The data for the study are sourced annually from the financial statements of the selected Deposit Money Banks and the Central Bank of Nigeria Statistical Bulletin. The panel unit root and co-integration tests are employed to ascertain the sustainability of the bank-specific performance indicators. The models for the industry were cast in a host of panel frameworks such that we estimated the static and dynamic panel models. The study observed that the capital adequacy ratio, which is the short-term financing obligation of Nigerian banks was elastic to bank profitability positively. In addition, interbank call rate, bank size, and oil price positively influence the capital adequacy ratio over time, whereas loan-to-deposit ratio, inflation and exchange rate exacerbate the capital adequacy ratio. Consequently, we canvass that Nigerian banks should reduce dividend payouts and increase retained profits as a buffer against exposed risks.
The African farming sector suffers from insufficient finance. Climate changes and socio-political issues hold down the required production level while food on the continent is still inadequate, with more vulnerable people on the one side. On the other side, credit institutions need reasons and guarantees to raise their risk-taking level (financial benefits). Then, this study tries to conciliate those two sides with new shreds of evidence by demonstrating the short and long-run effects of agricultural production on bank sustainability in 40 Sub-Saharan African countries. The study used different agro-production factors (Food and Cereal production factors), bank stability proxies (Liquidity Ratio, NPLs, LLRs), and bank profitability proxies (ROA and ROE). The GMM, DFE, and FMOLS models were used for short (with the 2010-2019 dataset) and long-run analysis (with the 1970-2018 dataset). The results demonstrated that agricultural production increases bank stability and profitability but reduces bank risks. The study concludes that farming finance increases agro-production and stabilizes banks (win-win). Governments, via central banks, should encourage commercial banks to increase bank risk-taking levels to sustain their banking system, increase farming production, and improve food security.
This study aims to examine the association between banks and firms in a loan. Our data set was pooled cross section data from 2014 to 2016, with long-term loans of firms listed in Indonesia Stock Exchange as a unit of analysis. We estimate our regression model using ordinary least square (OLS) estimator. The results revealed that lower-risk banks tend to associate with riskier but well-performing firms. Similarly, lower-capital banks tend to associate with riskier but well-performing firms. These results are quite contrary to previous studies conducted in developed countries. Lower risk banks have relationship with riskier and well-performing firms in condition that the amount of loan is small enough to be considered safe. Meanwhile, lower capital banks in this study, especially in Indonesia, may face the geographical problem which drives cost so high that makes banks charge higher interest to possibly riskier firms. This study makes contribution by providing evidence from a relative fragmented credit market. Future research on this topic is encouraged to look out more detail especially in the causality interpretation.
This study examines the link between bank performance and bank stability in the context of African countries. Using the Augmented Mean Group (AMG) estimator and panel data from 16 selected African countries covering the period 2002–2019, this study considers whether the banking sector's performance influences the banking system's financial stability. The findings reveal a significant positive long-run relationship between ROA and financial stability. This was the case when the AMG estimator was employed and when the CCEMG was employed to check for robustness. Inflation was initially negative and insignificant but a highly significant determinant when a more robust method (CCEMG) was used. Economic growth has a negative relationship using both estimators but is insignificant, while trade openness and non-interest income had insignificant coefficients in both estimators. The granger causality results show a one-way causality established to bank stability in the case of bank performance and trade openness. In addition, there was a non-causal relationship between bank stability, non-interest income and inflation as against a double-track causation between bank stability and economic growth. African countries should strive to improve bank performance to enhance the stability of the sector.
This paper aims to analyse the effects of financial statement indicators and off-balance sheet items affecting risk measures among Indian banks employing both panel data regression and a non-parametric decision tree approach. We explore the effects of bank size, leverage, exposure to contingent liabilities including off-balance sheet derivatives usage and macroeconomic factors on risk measures for banks. In this paper, it is also aimed to examine the effects of the major financial liberalization policy period in the domestic market in India that started in the mid-1990s and ended around 2004 as well as impacts of the 2008 global financial crisis on the risk measures of banks operating in India. As risk measures, we present a comparative analysis of liquidity, solvency, and interest rate risk measures of Indian banks across public (government) and private ownership categories. Main findings from our study demonstrate (i) significant impact of capital adequacy and the bank size on all the risk measures, (ii) contingent liabilities (including derivatives usage) at banks is observed to significantly impact the asset management measure of liquidity risk and the solvency risk of banks, (iii) GDP growth is observed to impact the asset management and liability management measure of liquidity risk, (iv) the global financial crisis is found to have a significant impact on the liquidity risk measures and interest rate risk, but a weak effect on solvency risk of Indian banks, (v) bank ownership category (government owned versus private sector banks) is observed to have a significant impact on all the risk measures, and finally (vi) financial liberalization reforms had a highly significant effect on the liquidity risk at banks.
This paper examined bank-specific performance indicators and macroeconomic factors affecting the short-term financing obligation of Nigerian banks from 2010 to 2019. The data for the study are sourced annually from the financial statements of the selected Deposit Money Banks and the Central Bank of Nigeria Statistical Bulletin. The panel unit root and co-integration tests are employed to ascertain the sustainability of the bank-specific performance indicators. The models for the industry were cast in a host of panel frameworks such that we estimated the static and dynamic panel models. The study observed that the capital adequacy ratio, which is the short-term financing obligation of Nigerian banks was elastic to bank profitability positively. In addition, interbank call rate, bank size, and oil price positively influence the capital adequacy ratio over time, whereas loan-to-deposit ratio, inflation and exchange rate exacerbate the capital adequacy ratio. Consequently, we canvass that Nigerian banks should reduce dividend payouts and increase retained profits as a buffer against exposed risks.
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 |