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: 2 / 2 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: 22 Oct 2026 01:39 UTC — 23 Oct 2026 05:24 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.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 0 | 2 | 2/2 | 2/2 |
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 2 / 2 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): 2026-10-22T01:39:59.924435+00:00 — 2026-10-23T05:24:24.124565+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 | 2 | 2/2 |
| 2018 | All selected publications | 0 | 2 | 2/2 |
| 2019 | All selected publications | 0 | 2 | 2/2 |
| 2020 | All selected publications | 0 | 2 | 2/2 |
| 2021 | All selected publications | 0 | 2 | 2/2 |
| 2022 | All selected publications | 0 | 2 | 2/2 |
| 2023 | All selected publications | 0 | 2 | 2/2 |
| 2024 | All selected publications | 0 | 2 | 2/2 |
| 2025 | All selected publications | 0 | 2 | 2/2 |
| 2026 | All selected publications | 0 | 2 | 2/2 |
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 |
|---|---|
| 2019 | 2 |
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 Research in Business and Social Science SSBFNET | 2 | 0 | 0 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Since independence in 2011 the Republic of South Sudan has witnessed growth in the financial systems and the overall economy. This has led to growth in the number of the financial institutions in the country. There is however minimal research on their overall performance. Hence the current research sought to determine the effect of ownership structure, bank stability and the financial performance of commercial banks in South Sudan. The population for the study was all the 29 commercial banks in South Sudan. Secondary data was collected for the period 2012-2017 from audited annual financial reports of individual banks and from the Central Bank of South Sudan reports while primary data was collected by use of a semi-structured questionnaire. The research utilized both descriptive and inferential statistical methods in the analysis. The statistical tests to be utilized in the study included t-tests, f-test, regression models and ANOVA models. The results of the study indicated there was a statistically significant moderating effect of ownership structure on the financial performance of commercial banks in South Sudan. The study recommends that the government should adopt better measures to safeguard public owned commercial banks to improve their efficiency and performance.
Despite increasing bank competitiveness within the country for the past half-decade there has been scant literature examining their stability in the face of the numerous internal factors and economic shocks. Hence the current research aims to determine if bank stability has any effect on commercial bank’s fiscal performance in South Sudan. The study was guided by the CAMEL model metrics (ROA and ROE) in measuring stability and its influence on the monetary performance of commercial banks. SPSS 23 was used to carry out subsequent descriptive and inferential statistical analysis. The study was primarily grounded on the CAMEL model. The correlation tests indicated that asset quality had a strong positive effect on monetary performance of commercial banks p= .784; a strong positive effect of management efficiency p= .758 and liquidity p= .620.
Since independence in 2011 the Republic of South Sudan has witnessed growth in the financial systems and the overall economy. This has led to growth in the number of the financial institutions in the country. There is however minimal research on their overall performance. Hence the current research sought to determine the effect of ownership structure, bank stability and the financial performance of commercial banks in South Sudan. The population for the study was all the 29 commercial banks in South Sudan. Secondary data was collected for the period 2012-2017 from audited annual financial reports of individual banks and from the Central Bank of South Sudan reports while primary data was collected by use of a semi-structured questionnaire. The research utilized both descriptive and inferential statistical methods in the analysis. The statistical tests to be utilized in the study included t-tests, f-test, regression models and ANOVA models. The results of the study indicated there was a statistically significant moderating effect of ownership structure on the financial performance of commercial banks in South Sudan. The study recommends that the government should adopt better measures to safeguard public owned commercial banks to improve their efficiency and performance.
Despite increasing bank competitiveness within the country for the past half-decade there has been scant literature examining their stability in the face of the numerous internal factors and economic shocks. Hence the current research aims to determine if bank stability has any effect on commercial bank’s fiscal performance in South Sudan. The study was guided by the CAMEL model metrics (ROA and ROE) in measuring stability and its influence on the monetary performance of commercial banks. SPSS 23 was used to carry out subsequent descriptive and inferential statistical analysis. The study was primarily grounded on the CAMEL model. The correlation tests indicated that asset quality had a strong positive effect on monetary performance of commercial banks p= .784; a strong positive effect of management efficiency p= .758 and liquidity p= .620.
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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |