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: 7 / 7 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 07:22 UTC — 23 Oct 2026 13:08 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.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 |
|---|---|---|---|---|---|
| 2014 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 15 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
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 7 / 7 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): 2026-10-21T07:22:43.108325+00:00 — 2026-10-23T13:08:02.558315+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 0 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 1 | 7 | 7/7 |
| 2022 | All selected publications | 4 | 7 | 7/7 |
| 2023 | All selected publications | 4 | 7 | 7/7 |
| 2024 | All selected publications | 7 | 7 | 7/7 |
| 2025 | All selected publications | 11 | 7 | 7/7 |
| 2026 | All selected publications | 3 | 7 | 7/7 |
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 |
|---|---|
| 2014 | 1 |
| 2016 | 1 |
| 2019 | 1 |
| 2020 | 1 |
| 2022 | 1 |
| 2023 | 1 |
| 2025 | 1 |
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 | 11 | 18 | 2/2 | 5.5 | 5.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 2 | 4 | 2/2 | 1.0 | 1.0 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 3 | 8 | 3/3 | 1.0 | 1 | 100.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
Commercial banks accept deposits and lend money for investment and consumption. This study used five (5) first-tier banks in Nigeria as a case study to analyze the effects of credit risk management on the financial performance of commercial banks. The study examined fifteen (15) years' worth of panel data (from 2005 to 2019), taken from the audited financial reports of five first-tier listed banks. Deposit Money Banks (DMBs) are the only banks used, and they are all listed on the Nigerian Stock Exchange. Non-performing loans (NPL) and expected credit loss impairment provisions (ECL) were utilized in this study as indicators of credit risk management. At the same time, return on assets (ROA) was employed to measure financial performance.
Increasing trend in Non-performing loans (NPLs) adversely affected availability of credits to economic agents in all sectors of the economy thereby constraining financial intermediation and economic activities. The study examined the trend and growth rates of NPLs in the Nigerian banking system during the major banking policy reforms regimes namely: pre-consolidation (1979 – 2004) and post consolidation era (2005 – 2014). Time series data collected were analyzed using descriptive and regression analyses. Results indicated irregular fluctuations in NPLs’ trend in both periods. This result suggested prevalent high credit risk and corresponding reduction in lending capability of banks in the economy. Regression estimates of NPLs’ trend in the two regimes showed significant negative growth rates.This implies that, financial policies implemented in the country yielded positive impacts over time. NPLs assumed an exponential growth rate of -1.39% and -15.55% during the pre and post consolidated eras respectively. An average exponential growth rate of -5.2% was obtained during the entire period. Quadratic trend analysis revealed that, increase influence of time variable significantly reduced NPLs during pre- consolidation regime and the entire period considered. However, this influence was stagnated during post consolidation period. Based on the result, it is recommended that, prudent lending coupled with swift and orderly clean-up of banking system loan portfolios should be adopted to decelerate NPLs trend and growth rate in Nigeria. Time is an important element in designing and implementing any banking and macroeconomic policy.
This study examines the impacts of credit risk management on the growth of Nigerian banks. Specifically, the study focused mainly on the impacts of credit risk management among Deposit Money Banks in Nigeria. The study employed an ex-post facto research design, utilising secondary data from the financial information of 14 selected listed Deposit Money Banks from 2007 to 2022. The study population was defined as the total number of listed Deposit Money Banks, from which a sample of six banks was selected using a simple random sampling technique. The operationalisation of variables included (1) the use of natural logarithm for bank size, (2) a three-level scale for credit risk, and (3) alternative measurements for collateral management and credit scores. Data analysis involved the calculation of descriptive statistics, correlation analysis, variance inflation factors, and regression analysis. The research hypotheses are also validated to assess the significance of various factors in credit risk management. The findings revealed that credit scores significantly enhance the effectiveness of credit risk assessment, and collateral management did not significantly contribute to mitigating credit risk. The findings also revealed that default risk management significantly reduces the credit risk of Deposit Money Banks in Nigeria. These results highlight the intricate nature of credit risk management in the banking sector and emphasize the need for a multifaceted approach.
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 objective of this study is to examine the effect of bank lending on the growth of selected small and medium scale businesses in Nigeria. There are two basic research designs in social sciences, qualitative and quantitative orientation. However, the literature suggests a growing interest in a mixed approach (triangulation) following on from the argument that one is used to strengthen the other. Often, combining qualitative and quantitative methods, also known as the triangulation of methods, can capture a more holistic, complete, and contextual view of a phenomenon. The research is based on both qualitative and quantitative research designs. Three research questions were addressed. Data were collected from a purposive sample of 200 respondents drawn from a population of 400 respondents. A research developed questionnaire was used for the data collection. Data were analyzed using simple percentages and tables. The result of the study revealed that Lending to SMEs encourages self-employment thereby reducing the rate of unemployment and crime in Nigeria. It also boosts industrialization as well as improving the economic situation in the Country. In conclusion, bank lending influence positively the level of economic activities and the growth of SMEs in the country. A number of recommendations were made based on the findings prominent among them is the need for Government, Commercial bank, and Central bank of Nigeria to increase lending to small and medium scale business with a view to create more jobs, reduce crime and unemployment as well as boost industrialization in Nigeria.
This study examines the impacts of credit risk management on the growth of Nigerian banks. Specifically, the study focused mainly on the impacts of credit risk management among Deposit Money Banks in Nigeria. The study employed an ex-post facto research design, utilising secondary data from the financial information of 14 selected listed Deposit Money Banks from 2007 to 2022. The study population was defined as the total number of listed Deposit Money Banks, from which a sample of six banks was selected using a simple random sampling technique. The operationalisation of variables included (1) the use of natural logarithm for bank size, (2) a three-level scale for credit risk, and (3) alternative measurements for collateral management and credit scores. Data analysis involved the calculation of descriptive statistics, correlation analysis, variance inflation factors, and regression analysis. The research hypotheses are also validated to assess the significance of various factors in credit risk management. The findings revealed that credit scores significantly enhance the effectiveness of credit risk assessment, and collateral management did not significantly contribute to mitigating credit risk. The findings also revealed that default risk management significantly reduces the credit risk of Deposit Money Banks in Nigeria. These results highlight the intricate nature of credit risk management in the banking sector and emphasize the need for a multifaceted approach.
Commercial banks accept deposits and lend money for investment and consumption. This study used five (5) first-tier banks in Nigeria as a case study to analyze the effects of credit risk management on the financial performance of commercial banks. The study examined fifteen (15) years' worth of panel data (from 2005 to 2019), taken from the audited financial reports of five first-tier listed banks. Deposit Money Banks (DMBs) are the only banks used, and they are all listed on the Nigerian Stock Exchange. Non-performing loans (NPL) and expected credit loss impairment provisions (ECL) were utilized in this study as indicators of credit risk management. At the same time, return on assets (ROA) was employed to measure financial performance.
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 objective of this study is to examine the effect of bank lending on the growth of selected small and medium scale businesses in Nigeria. There are two basic research designs in social sciences, qualitative and quantitative orientation. However, the literature suggests a growing interest in a mixed approach (triangulation) following on from the argument that one is used to strengthen the other. Often, combining qualitative and quantitative methods, also known as the triangulation of methods, can capture a more holistic, complete, and contextual view of a phenomenon. The research is based on both qualitative and quantitative research designs. Three research questions were addressed. Data were collected from a purposive sample of 200 respondents drawn from a population of 400 respondents. A research developed questionnaire was used for the data collection. Data were analyzed using simple percentages and tables. The result of the study revealed that Lending to SMEs encourages self-employment thereby reducing the rate of unemployment and crime in Nigeria. It also boosts industrialization as well as improving the economic situation in the Country. In conclusion, bank lending influence positively the level of economic activities and the growth of SMEs in the country. A number of recommendations were made based on the findings prominent among them is the need for Government, Commercial bank, and Central bank of Nigeria to increase lending to small and medium scale business with a view to create more jobs, reduce crime and unemployment as well as boost industrialization in Nigeria.
The study examined the dynamic responses of profitability indexes to capital adequacy ratios of authorized internationalized deposit money banks in Nigeria. The data were sourced from the financial year books of the deposit money banks and analyzed with static and dynamic panel estimators. The static estimator shows that the banks have differences in managerial style, size and profitability. Also, it was revealed that return on asset and return on equity responded positively to asset size, efficiency of the use of asset and current ratio in the static models and they were highly significant. However, they were insignificant in the dynamic specifications except asset size that was significant in the return on asset model showing a weak dynamic response of profitability to capital adequacy ratios. Hence the study recommended that Banks should improve their share based as to increase the asset as this will improve profitability.
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 |