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.
Top 5 in the selected collection · Ranked by OpenAlex lifetime citations. Only articles with at least one known citation are included; source totals are never combined.
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 ↓No data available.
0/4 records with dataNo data available.
0/4 records with dataNo data available.
0/4 records with dataIndependent 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, 00:21 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: Not available — Not available. 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.
0 / 4 with data · 4 missing or unmatched. Percentages use all 4 selected publications.
No verified institutions data for this selection.
0 / 4 with data · 4 missing or unmatched. Percentages use all 4 selected publications.
No verified countries data for this selection.
0 / 4 with data · 4 missing or unmatched. Percentages use all 4 selected publications.
No verified primary topics data for this selection.
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 |
|---|---|---|---|---|---|
| 2018 | All selected publications | 4 | 4 | 4/4 | 0/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 3 | 4 | 4/4 | 0/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | — | 4 | 4/4 | 0/4 |
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 0 / 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.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | — | 4 | 0/4 |
| 2018 | All selected publications | — | 4 | 0/4 |
| 2019 | All selected publications | — | 4 | 0/4 |
| 2020 | All selected publications | — | 4 | 0/4 |
| 2021 | All selected publications | — | 4 | 0/4 |
| 2022 | All selected publications | — | 4 | 0/4 |
| 2023 | All selected publications | — | 4 | 0/4 |
| 2024 | All selected publications | — | 4 | 0/4 |
| 2025 | All selected publications | — | 4 | 0/4 |
| 2026 | All selected publications | — | 4 | 0/4 |
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 |
|---|---|
| 2018 | 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 | 4 | 3 | — | 0/4 | 0.75 | 1.0 | 75.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
<p><em>The success of SMEs is determined by the business capital and able to give value added to the business more productively. Various financing pattern schemes for SMEs have been provided in various regions and all economic sectors. However, the development of SMEs credit is still concentrated in several regions in Indonesia</em><em> t</em><em>his can lead to inequality in the growth of SMEs</em><em>. </em><em>This study aims to analyze the convergence of absolute beta and conditional beta in the Provinces in Indonesia and calculate the half-time or time required to achieve steady-state conditions of the SME credit convergence process. Convergence test used is beta conditional convergence and absolute convergence with the monthly time period during 2017.1 until 2017.7. The determinant of SMEs convergence of credit in Indonesia is a number of third-party funds. The model used is dynamic panel data regression and the estimation method used is Arellano-Bond Generalized Method of Moment (AB-GMM).</em></p><p><em>The results of the study show that during the study period, there has been a convergence credit process in Indonesia for both absolute and conditional convergence models. The conditional beta-convergence model provides a smaller beta value than the absolute model. The speed of credit growth convergence between provinces in Indonesia with half-time of 6,94 months for the absolute model and the half-time of 6,96 months for the conditional model. </em><em></em></p>
<p>The purpose of this article is to examine the impact of selected internal and external factors on a bank’s profitability. The research investigates the impact of operational size, liquidity, risk appetite, management efficiency, product diversification, concentration, GDP growth and inflation change on the profitability of sample of 4179 European commercial banks for the period between 2011 and 2015. The input data were obtained from the Orbis Focus and the World Bank databases. The determinants were used to construct two models with ROAA and ROAE as a proxies and regression analysis using between groups panel approach was conducted. It has been found that growing economy impacts banks’ profitability positively. The liquidity has been found to impact profitability positively, but statistically significant results were obtained only with the ROAA model. It has been robustly confirmed that management efficiency, product diversification, market concentration and inflation result in decreased profitability. The operational size has been found to be negatively linked to changes in net results but was confirmed only with ROAA model. Similarly, statistically significant results with regard to liquidity were found only for ROAA model and the correlation was positive. The strong negative impact of market concentration on profitability is an interesting finding allowing for further exploration of reasons for this unexpected vector of correlation.</p>
<p><em>This paper observes the impact of working capital management on profitability of industrial sector in Iraq. Four companies based in Iraq namely: Iraqi Date processing, Iraqi carton manufactories, Baghdad soft drinks and Iraqi for tufted carpets randomly selected and analyzed for the present study over the period 2007 to 2016. Annual reports of these companies have been studied and significant ratios calculated. The variables that were identified as independent for working capital were, current ratio and quick ratio, while return on equity ROE as dependent variable for profitability. The Ordinary Least Square (OLS) model used to examine the impact of working capital management on profitability. Results indicate that ROE is positively related with working capital variables.</em></p>
<p><em>Worldwide, Small and medium-size enterprises (SMEs) exhibit inimitable financial needs. While SMEs remain fundamental to economic growth, their mortality rate in Kenya approaches 90% by the second year, mainly owing to lack of credit. However, scholarly endeavors exploring the impact of alternative finance (AF) on managerial competency - efficiency nexus for manufacturing SMEs have received little attention in Kenya. To resolve this conundrum, a thorough study to investigate how AF impacts managerial competency - efficiency nexus is necessary. The study used a cross-sectional research design, employing both qualitative and quantitative research approaches. The target population was 171 SMEs registered with Kenya Association of Manufacturers. The accessible population was 136 SMEs owners/managers. A semi-structured questionnaire was used to collect primary and secondary data. Data envelopment analysis was used to measure efficiency, multiple regression modeling used to analyze the direct relationships while hierarchical moderated multiple regression analysis employed to test moderation. Partial Least Squares Structural Equation Modeling was used to test robustness of our results. The findings of this study demonstrate that managerial competency positively influences efficiency (β = 0.150, t-value =10.246, P&lt;0.05), and that alternative finance does moderate managerial competency relationships with efficiency (R-Square change of 21.7%).We suggest trainings for manufacturing SME owners/managers in Kenya on the pivotal role of alternative finance to facilitate SMEs achieve higher efficiencies and accelerate economic growth.</em></p>
<p><em>Worldwide, Small and medium-size enterprises (SMEs) exhibit inimitable financial needs. While SMEs remain fundamental to economic growth, their mortality rate in Kenya approaches 90% by the second year, mainly owing to lack of credit. However, scholarly endeavors exploring the impact of alternative finance (AF) on managerial competency - efficiency nexus for manufacturing SMEs have received little attention in Kenya. To resolve this conundrum, a thorough study to investigate how AF impacts managerial competency - efficiency nexus is necessary. The study used a cross-sectional research design, employing both qualitative and quantitative research approaches. The target population was 171 SMEs registered with Kenya Association of Manufacturers. The accessible population was 136 SMEs owners/managers. A semi-structured questionnaire was used to collect primary and secondary data. Data envelopment analysis was used to measure efficiency, multiple regression modeling used to analyze the direct relationships while hierarchical moderated multiple regression analysis employed to test moderation. Partial Least Squares Structural Equation Modeling was used to test robustness of our results. The findings of this study demonstrate that managerial competency positively influences efficiency (β = 0.150, t-value =10.246, P&lt;0.05), and that alternative finance does moderate managerial competency relationships with efficiency (R-Square change of 21.7%).We suggest trainings for manufacturing SME owners/managers in Kenya on the pivotal role of alternative finance to facilitate SMEs achieve higher efficiencies and accelerate economic growth.</em></p>
<p><em>The success of SMEs is determined by the business capital and able to give value added to the business more productively. Various financing pattern schemes for SMEs have been provided in various regions and all economic sectors. However, the development of SMEs credit is still concentrated in several regions in Indonesia</em><em> t</em><em>his can lead to inequality in the growth of SMEs</em><em>. </em><em>This study aims to analyze the convergence of absolute beta and conditional beta in the Provinces in Indonesia and calculate the half-time or time required to achieve steady-state conditions of the SME credit convergence process. Convergence test used is beta conditional convergence and absolute convergence with the monthly time period during 2017.1 until 2017.7. The determinant of SMEs convergence of credit in Indonesia is a number of third-party funds. The model used is dynamic panel data regression and the estimation method used is Arellano-Bond Generalized Method of Moment (AB-GMM).</em></p><p><em>The results of the study show that during the study period, there has been a convergence credit process in Indonesia for both absolute and conditional convergence models. The conditional beta-convergence model provides a smaller beta value than the absolute model. The speed of credit growth convergence between provinces in Indonesia with half-time of 6,94 months for the absolute model and the half-time of 6,96 months for the conditional model. </em><em></em></p>
<p>The purpose of this article is to examine the impact of selected internal and external factors on a bank’s profitability. The research investigates the impact of operational size, liquidity, risk appetite, management efficiency, product diversification, concentration, GDP growth and inflation change on the profitability of sample of 4179 European commercial banks for the period between 2011 and 2015. The input data were obtained from the Orbis Focus and the World Bank databases. The determinants were used to construct two models with ROAA and ROAE as a proxies and regression analysis using between groups panel approach was conducted. It has been found that growing economy impacts banks’ profitability positively. The liquidity has been found to impact profitability positively, but statistically significant results were obtained only with the ROAA model. It has been robustly confirmed that management efficiency, product diversification, market concentration and inflation result in decreased profitability. The operational size has been found to be negatively linked to changes in net results but was confirmed only with ROAA model. Similarly, statistically significant results with regard to liquidity were found only for ROAA model and the correlation was positive. The strong negative impact of market concentration on profitability is an interesting finding allowing for further exploration of reasons for this unexpected vector of correlation.</p>
<p><em>This paper observes the impact of working capital management on profitability of industrial sector in Iraq. Four companies based in Iraq namely: Iraqi Date processing, Iraqi carton manufactories, Baghdad soft drinks and Iraqi for tufted carpets randomly selected and analyzed for the present study over the period 2007 to 2016. Annual reports of these companies have been studied and significant ratios calculated. The variables that were identified as independent for working capital were, current ratio and quick ratio, while return on equity ROE as dependent variable for profitability. The Ordinary Least Square (OLS) model used to examine the impact of working capital management on profitability. Results indicate that ROE is positively related with working capital variables.</em></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 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |
| ojs-rest | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:14 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 00:22 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |