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: 3 / 3 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 02:02 UTC — 23 Oct 2026 11:51 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.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 1 | 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 3 / 3 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): 2026-10-22T02:02:31.942174+00:00 — 2026-10-23T11:51:20.229174+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 | 3 | 3/3 |
| 2018 | All selected publications | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 0 | 3 | 3/3 |
| 2021 | All selected publications | 0 | 3 | 3/3 |
| 2022 | All selected publications | 1 | 3 | 3/3 |
| 2023 | All selected publications | 0 | 3 | 3/3 |
| 2024 | All selected publications | 1 | 3 | 3/3 |
| 2025 | All selected publications | 1 | 3 | 3/3 |
| 2026 | All selected publications | 2 | 3 | 3/3 |
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 |
|---|---|
| 2021 | 1 |
| 2023 | 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 Finance & Banking Studies SSBFNET | 2 | 1 | 1 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 4 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
Banks are a high-risk industry, which is regulated by the government through the Financial Services Authority (FSA), so bank management must be very careful in managing banks so that risks can be controlled. The purpose of this study was to examine the effect of bank risk and third party funds on bank performance. Bank performance is measured by return on assets (ROA), while bank risk consists of operating risk which is measured by operating expenses to operating income ratio (EIR), liquidity risk is measured by loan to deposit ratio (LDR), capital risk is measured by capital adequacy ratio (CAR), and credit risk is measured by non-performing loans (NPL), and third party funds (TPF) are measured by the natural log of total credit. The research population consisted of 46 banks listed on the Indonesia Stock Exchange with a sample of 24 banks taken using a purposive sampling technique. The data collection period is four years with quarterly data (2019-2022). To test the hypothesis used panel data regression. After testing the model with the Chow-test and Hausman-test, the best regression model is the fixed effect model. The results of research using the fixed effect model show that operating risk (EIR) has a significant and negative effect on bank performance, while liquidity risk (LDR) has a significant positive effect on bank performance. Meanwhile, the capital adequacy ratio (CAR), non-performing loans (NPL), and third party funds (TPF) have no effect on bank performance.
The Covid-19 pandemic has hit the world since the end of 2019 and has damaged the world economy, including Indonesia. Banking as a financial institution that provides funding to companies is also affected. Because the pandemic has reduced the company's performance, and this decline in performance has had an impact on banking. The aim of this research is to test whether the Covid-19 pandemic has an impact on the relationship between risk factors and bank performance. Bank performance is measured by profitability which consists of return on assets (ROA) and return on equity (ROE), while bank risk in this study consists of credit risk, liquidity risk, capital, operational risk and the Covid-19 pandemic. The population in this research is the Regional Development Banks (BPD) in Indonesia totaling 34 banks with a sample of 30 banks. The observation period was 4 years with quarterly data so that 320 observation data were collected. Hypothesis testing uses panel data regression, and to select the best regression model, the model will be tested using the Chow-test, Hausman-test, and Lagrange Multiplier test. After the model test was carried out, the fixed effect model was selected as the best model. The research results show that credit risk and operational risk have a significant and negative influence on all profitability, both ROA and ROE. Meanwhile, liquidity risk (LDR) has no effect on both types of profitability, while capital has an effect on ROE but has no effect on ROA. Another interesting result is that the Covid-19 pandemic has no impact on the influence of risk on bank performance.
This study aims to examine and analyze the influence of interest rates, exchange rates and capital structure on profitability in state-owned and private banking go public in Indonesia. This research is quantitative research based on the study of empirical rational principles. Collecting data using secondary data with purposive sampling technique, the sample consists of Commercial Banks Business Group (BUKU IV) with core capital > Rp 30 trillion. The data analysis technique used panel data regression analysis using EVIEWS version 11 software. The results showed that the interest rate had a positive and significant effect on banking profitability; Exchange Rate has a negative and significant effect on Banking Profitability; Capital Structure has a positive and significant effect on Banking Profitability; Interest Rate, Exchange Rate, and Capital Structure simultaneously have a positive and significant effect on Banking Profitability
The Covid-19 pandemic has hit the world since the end of 2019 and has damaged the world economy, including Indonesia. Banking as a financial institution that provides funding to companies is also affected. Because the pandemic has reduced the company's performance, and this decline in performance has had an impact on banking. The aim of this research is to test whether the Covid-19 pandemic has an impact on the relationship between risk factors and bank performance. Bank performance is measured by profitability which consists of return on assets (ROA) and return on equity (ROE), while bank risk in this study consists of credit risk, liquidity risk, capital, operational risk and the Covid-19 pandemic. The population in this research is the Regional Development Banks (BPD) in Indonesia totaling 34 banks with a sample of 30 banks. The observation period was 4 years with quarterly data so that 320 observation data were collected. Hypothesis testing uses panel data regression, and to select the best regression model, the model will be tested using the Chow-test, Hausman-test, and Lagrange Multiplier test. After the model test was carried out, the fixed effect model was selected as the best model. The research results show that credit risk and operational risk have a significant and negative influence on all profitability, both ROA and ROE. Meanwhile, liquidity risk (LDR) has no effect on both types of profitability, while capital has an effect on ROE but has no effect on ROA. Another interesting result is that the Covid-19 pandemic has no impact on the influence of risk on bank performance.
Banks are a high-risk industry, which is regulated by the government through the Financial Services Authority (FSA), so bank management must be very careful in managing banks so that risks can be controlled. The purpose of this study was to examine the effect of bank risk and third party funds on bank performance. Bank performance is measured by return on assets (ROA), while bank risk consists of operating risk which is measured by operating expenses to operating income ratio (EIR), liquidity risk is measured by loan to deposit ratio (LDR), capital risk is measured by capital adequacy ratio (CAR), and credit risk is measured by non-performing loans (NPL), and third party funds (TPF) are measured by the natural log of total credit. The research population consisted of 46 banks listed on the Indonesia Stock Exchange with a sample of 24 banks taken using a purposive sampling technique. The data collection period is four years with quarterly data (2019-2022). To test the hypothesis used panel data regression. After testing the model with the Chow-test and Hausman-test, the best regression model is the fixed effect model. The results of research using the fixed effect model show that operating risk (EIR) has a significant and negative effect on bank performance, while liquidity risk (LDR) has a significant positive effect on bank performance. Meanwhile, the capital adequacy ratio (CAR), non-performing loans (NPL), and third party funds (TPF) have no effect on bank performance.
This study aims to examine and analyze the influence of interest rates, exchange rates and capital structure on profitability in state-owned and private banking go public in Indonesia. This research is quantitative research based on the study of empirical rational principles. Collecting data using secondary data with purposive sampling technique, the sample consists of Commercial Banks Business Group (BUKU IV) with core capital > Rp 30 trillion. The data analysis technique used panel data regression analysis using EVIEWS version 11 software. The results showed that the interest rate had a positive and significant effect on banking profitability; Exchange Rate has a negative and significant effect on Banking Profitability; Capital Structure has a positive and significant effect on Banking Profitability; Interest Rate, Exchange Rate, and Capital Structure simultaneously have a positive and significant effect on Banking 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 |