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: 21 Oct 2026 07:22 UTC — 22 Oct 2026 01:27 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 | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 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 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): 2026-10-21T07:22:53.429420+00:00 — 2026-10-22T01:27:02.126252+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 | 0 | 3 | 3/3 |
| 2023 | All selected publications | 1 | 3 | 3/3 |
| 2024 | All selected publications | 2 | 3 | 3/3 |
| 2025 | All selected publications | 2 | 3 | 3/3 |
| 2026 | All selected publications | 4 | 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 |
| 2024 | 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 Finance & Banking Studies SSBFNET | 1 | 2 | 2 | 1/1 | 2.0 | 2 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 6 | 7 | 2/2 | 3.0 | 3.0 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
This research aims to analyze the impact of green credit distribution by banks on bank performance and identify factors that can influence green credit. The study utilizes data from 46 banks in Indonesia during the 2018-2022 period, by using the panel data regression method. The findings indicate (i) that green credit does not have a significant influence on credit risk, as measured by the NPL (Non-performing Loan). The distribution of more green credit allocations does not result in a decrease in bank credit risk. Additionally, sustainable business borrowers do not exhibit better debt repayment performance compared to the non-sustainable business category. (ii) In terms of bank profitability, green credit does not impact ROE (Return on Equity) and NIM (Net Interest Margin), but it does have a negative effect on ROA (Return on Assets). Banks that allocate a significant portion of their credit distribution to green initiatives tend to experience a decline in their profits. (iii) Bank size has a positive impact on the allocation of green credit, with larger banks dedicating a greater portion to the distribution of green credit. Larger banks possess more capital and extensive networks, making them better equipped to address potential risks compared to smaller banks. (iv) Meanwhile, government ownership and good corporate governance in banks do not influence the proportion of green credit distribution. The author recommends that the government make corrections to existing green financing programs, to cultivate a green credit ecosystem in Indonesia. One concrete step that can be taken is to support government-owned banks in becoming pioneers in the distribution of green credit in Indonesia.
This study analyzes the effect of sustainable investment awareness and risk perception on students' interest in green finance instruments, with financial literacy as a mediating variable. A quantitative approach was used, involving 180 student respondents in the Special Region of Yogyakarta, who were selected through a purposive sampling technique using an online questionnaire via Google Forms. Data analysis was conducted using the SEM-PLS method through SmartPLS version 4.1.1.2. The results showed that sustainable investment awareness, risk perception, and financial literacy positively and significantly affect student investment interest in green finance. In addition, financial literacy acts as a significant mediator in the relationship between sustainable investment awareness and risk perception on interest in investing in green finance. This study contributes to developing literature on sustainable investment behavior among the younger generation, especially university students, by integrating financial literacy variables as a mediating mechanism. The findings expand the understanding of how psychological factors and financial knowledge influence investment decisions in sustainability.
This study aims to examine Blue Bonds as a guarantee issued by the issuer (government and companies) as alternative financing. Compared to ordinary bonds that are issued only to meet the issuer's funding needs, the transaction results in Blue Bonds will be used to support marine protection, fisheries governance, waste and water pollution management, and the restoration of marine ecosystems. In this study, the author uses the method literature review sourced from journals, books, reports from related ministries, international financial institutions such as the World Bank, and news from national and international media. The results of this study indicate that by issuing Blue Bonds, the government and companies will get more funds from bond investors. Investors will receive a return in the form of a coupon (fixed interest rate) from the issuer and pay according to schedule and the initial principal investment. Not only that, the government and companies will get a good reputation among investors and actively contribute to Indonesia's maritime development.
This study analyzes the effect of sustainable investment awareness and risk perception on students' interest in green finance instruments, with financial literacy as a mediating variable. A quantitative approach was used, involving 180 student respondents in the Special Region of Yogyakarta, who were selected through a purposive sampling technique using an online questionnaire via Google Forms. Data analysis was conducted using the SEM-PLS method through SmartPLS version 4.1.1.2. The results showed that sustainable investment awareness, risk perception, and financial literacy positively and significantly affect student investment interest in green finance. In addition, financial literacy acts as a significant mediator in the relationship between sustainable investment awareness and risk perception on interest in investing in green finance. This study contributes to developing literature on sustainable investment behavior among the younger generation, especially university students, by integrating financial literacy variables as a mediating mechanism. The findings expand the understanding of how psychological factors and financial knowledge influence investment decisions in sustainability.
This research aims to analyze the impact of green credit distribution by banks on bank performance and identify factors that can influence green credit. The study utilizes data from 46 banks in Indonesia during the 2018-2022 period, by using the panel data regression method. The findings indicate (i) that green credit does not have a significant influence on credit risk, as measured by the NPL (Non-performing Loan). The distribution of more green credit allocations does not result in a decrease in bank credit risk. Additionally, sustainable business borrowers do not exhibit better debt repayment performance compared to the non-sustainable business category. (ii) In terms of bank profitability, green credit does not impact ROE (Return on Equity) and NIM (Net Interest Margin), but it does have a negative effect on ROA (Return on Assets). Banks that allocate a significant portion of their credit distribution to green initiatives tend to experience a decline in their profits. (iii) Bank size has a positive impact on the allocation of green credit, with larger banks dedicating a greater portion to the distribution of green credit. Larger banks possess more capital and extensive networks, making them better equipped to address potential risks compared to smaller banks. (iv) Meanwhile, government ownership and good corporate governance in banks do not influence the proportion of green credit distribution. The author recommends that the government make corrections to existing green financing programs, to cultivate a green credit ecosystem in Indonesia. One concrete step that can be taken is to support government-owned banks in becoming pioneers in the distribution of green credit in Indonesia.
This study aims to examine Blue Bonds as a guarantee issued by the issuer (government and companies) as alternative financing. Compared to ordinary bonds that are issued only to meet the issuer's funding needs, the transaction results in Blue Bonds will be used to support marine protection, fisheries governance, waste and water pollution management, and the restoration of marine ecosystems. In this study, the author uses the method literature review sourced from journals, books, reports from related ministries, international financial institutions such as the World Bank, and news from national and international media. The results of this study indicate that by issuing Blue Bonds, the government and companies will get more funds from bond investors. Investors will receive a return in the form of a coupon (fixed interest rate) from the issuer and pay according to schedule and the initial principal investment. Not only that, the government and companies will get a good reputation among investors and actively contribute to Indonesia's maritime development.
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 |