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: 4 / 4 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 01:26 UTC — 22 Oct 2026 02:06 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2016 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 7 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 22 | 4 | 4/4 | 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 4 / 4 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): 2026-10-22T01:26:03.866796+00:00 — 2026-10-22T02:06:04.114530+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 | 1 | 4 | 4/4 |
| 2018 | All selected publications | 3 | 4 | 4/4 |
| 2019 | All selected publications | 3 | 4 | 4/4 |
| 2020 | All selected publications | 4 | 4 | 4/4 |
| 2021 | All selected publications | 3 | 4 | 4/4 |
| 2022 | All selected publications | 2 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 2 | 4 | 4/4 |
| 2025 | All selected publications | 1 | 4 | 4/4 |
| 2026 | All selected publications | 0 | 4 | 4/4 |
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 |
|---|---|
| 2016 | 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 Finance & Banking Studies SSBFNET | 2 | 3 | 16 | 2/2 | 1.5 | 1.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 4 | 6 | 2/2 | 2.0 | 2.0 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
This paper analyzes the total factor productivity developments in the Middle East banking, by drawing on the experience of Jordanian banks at the start of the new millennium. In order to control for the effects of different specifications of banking technology on the results, this study estimates the productivity and efficiency growth scores under two alternative approaches, production and intermediation models. On average, under the former model, we found 79% technical efficiency and 3.2% productivity growth, while under the later model we found 92% technical efficiency and 3.3% productivity growth for the sector. One implication is that the Jordanian banks can obtain considerable resource savings if they can catch up with the best practice banks. Among the organizational forms operating in this emerging market, we found that commercial banks generally outperform both investment and Islamic banks in terms of efficiency and total factor productivity growth.
By drawing on Ukrainian experience, this paper analyzes the anatomy of bank efficiency in a transitional economy. Acknowledging the vast disparities in the business technology of different size banks, in this comprehensive study, we innovatively estimate group-specific (distinct) frontiers for small, medium, and large size banks. The results from separate frontiers reveal that Ukrainian banks record 38% technical inefficiency, 26% pure technical inefficiency, and 17% scale inefficiency on average. Apparently, banks in transition waste about the two fifths of their factor inputs during the production of financial services. The cardinal source of sub-performance in transitional banks seems to be managerial inefficiencies. We also found that banks operating in areas with more political influence and more developed infrastructure outperform the banks operating in politically and economically weaker regions. The results also indicate that larger banks, enjoying public trust in a risky business climate, dominate smaller banks in all forms of efficiency. However, such bias for size causes large banks to suffer from decreasing returns to scale and small banks from idle capacity. Consequently, the policies promoting consolidation between small and large banks may alleviate the excess (idle) capacity for large (small) banks in a transitional economy.
<p>The proactively evolved banking regulations in the Indian Banking sector under the authorative directive of the Reserve bank of India (RBI) has often brought about a change in the business strategy, capital structure and operations of the banks in the Indian banking sector. During these events of continuous change and adoption of Basel norms, we analyse the efficiency of the Indian banking sector with using Data Envelopment Analysis across three economic eras andacross the different ownership structures. The determinants of efficiency are selected on the basis of intermediation approach. We also attempt to identify whether the inefficiency arises from managerial incompetence or improper size and resource allocation. From our analysis, we identify the main cause of inefficiency in the Indian Banking sector to be arising out of improper size allocation.</p>
The precondition of the increase in the efficiency of the banks depends on their ability to compete. Through the banking sector with high competitive power, economic dynamism is promoted, and economic stability is ensured. The alteration in macroeconomic conditions affects the performance of the banking sector and financial stability. This study was used the malmquist productivity index to analyze the efficiency of 19 commercial banks operating in Turkey during the period of 1990 - 2012 for intermediation and profit approach. Banks have experienced productivity loss according to both approaches in times of crisis. The efficiency of intermediation function in the banking sector have increased owing to the regulations made ??under the restructuring program of the Turkish banking sector and the disinflation process. The regression analysis results reveals that the impact of credit / deposit ratio, ROA, ROE and inflation rate is positive on bank’s total factor productivity. As ROE increases, banks' total factor productivity has decreased under the intermediation approach. Increase in GDP has led to increase in bank’s technical efficiency for intermediation and profit approach.
The precondition of the increase in the efficiency of the banks depends on their ability to compete. Through the banking sector with high competitive power, economic dynamism is promoted, and economic stability is ensured. The alteration in macroeconomic conditions affects the performance of the banking sector and financial stability. This study was used the malmquist productivity index to analyze the efficiency of 19 commercial banks operating in Turkey during the period of 1990 - 2012 for intermediation and profit approach. Banks have experienced productivity loss according to both approaches in times of crisis. The efficiency of intermediation function in the banking sector have increased owing to the regulations made ??under the restructuring program of the Turkish banking sector and the disinflation process. The regression analysis results reveals that the impact of credit / deposit ratio, ROA, ROE and inflation rate is positive on bank’s total factor productivity. As ROE increases, banks' total factor productivity has decreased under the intermediation approach. Increase in GDP has led to increase in bank’s technical efficiency for intermediation and profit approach.
By drawing on Ukrainian experience, this paper analyzes the anatomy of bank efficiency in a transitional economy. Acknowledging the vast disparities in the business technology of different size banks, in this comprehensive study, we innovatively estimate group-specific (distinct) frontiers for small, medium, and large size banks. The results from separate frontiers reveal that Ukrainian banks record 38% technical inefficiency, 26% pure technical inefficiency, and 17% scale inefficiency on average. Apparently, banks in transition waste about the two fifths of their factor inputs during the production of financial services. The cardinal source of sub-performance in transitional banks seems to be managerial inefficiencies. We also found that banks operating in areas with more political influence and more developed infrastructure outperform the banks operating in politically and economically weaker regions. The results also indicate that larger banks, enjoying public trust in a risky business climate, dominate smaller banks in all forms of efficiency. However, such bias for size causes large banks to suffer from decreasing returns to scale and small banks from idle capacity. Consequently, the policies promoting consolidation between small and large banks may alleviate the excess (idle) capacity for large (small) banks in a transitional economy.
This paper analyzes the total factor productivity developments in the Middle East banking, by drawing on the experience of Jordanian banks at the start of the new millennium. In order to control for the effects of different specifications of banking technology on the results, this study estimates the productivity and efficiency growth scores under two alternative approaches, production and intermediation models. On average, under the former model, we found 79% technical efficiency and 3.2% productivity growth, while under the later model we found 92% technical efficiency and 3.3% productivity growth for the sector. One implication is that the Jordanian banks can obtain considerable resource savings if they can catch up with the best practice banks. Among the organizational forms operating in this emerging market, we found that commercial banks generally outperform both investment and Islamic banks in terms of efficiency and total factor productivity growth.
<p>The proactively evolved banking regulations in the Indian Banking sector under the authorative directive of the Reserve bank of India (RBI) has often brought about a change in the business strategy, capital structure and operations of the banks in the Indian banking sector. During these events of continuous change and adoption of Basel norms, we analyse the efficiency of the Indian banking sector with using Data Envelopment Analysis across three economic eras andacross the different ownership structures. The determinants of efficiency are selected on the basis of intermediation approach. We also attempt to identify whether the inefficiency arises from managerial incompetence or improper size and resource allocation. From our analysis, we identify the main cause of inefficiency in the Indian Banking sector to be arising out of improper size allocation.</p>
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 |