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: 5 / 5 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 — 23 Oct 2026 10:31 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | 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 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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 5 / 5 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 — 2026-10-23T10:31:06.297258+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 0 | 5 | 5/5 |
| 2023 | All selected publications | 1 | 5 | 5/5 |
| 2024 | All selected publications | 2 | 5 | 5/5 |
| 2025 | All selected publications | 5 | 5 | 5/5 |
| 2026 | All selected publications | 3 | 5 | 5/5 |
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 |
| 2022 | 1 |
| 2024 | 2 |
| 2026 | 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 Research in Business and Social Science SSBFNET | 5 | 9 | 11 | 5/5 | 1.8 | 2 | 60.0 | 5/5 · 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.
As extreme weather events continue to impact every continent and the world moves towards establishing a lower-carbon economy, the banking industry is expected to incorporate climate risk into their risk management practices. Climate change poses significant risks to bank loan portfolios through increased physical and transition risks. This study systematically analysed the literature to identify effective strategies for managing these risks. Our findings reveal that climate-related events can lead to substantial loan defaults and credit losses. To mitigate these impacts, banks can integrate climate risk into their risk management frameworks, adopt sustainable lending practices, and diversify their portfolios. Some banks have already implemented measures to mitigate climate risk through insurance policies, while others are incorporating sustainability criteria into their lending practices, such as financing green projects. By proactively addressing climate risks, banks can protect their portfolios, enhance financial resilience and contribute to a low-carbon economy.
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.
Green bonds are typically used for environmental protection projects. This paper explores the differences between general bonds and green bonds in Taiwan, as well as the impact of inflation. The findings are as follows: First, because green bonds support environmentally sustainable development projects, which require a longer time to realize their environmental benefits, they require longer repayment periods. Second, most green bonds have lower coupon rates than general bonds, indicating that investors are willing to accept lower interest income for the sake of environmental sustainability. Third, because green bonds invest in environmental protection projects with lower returns, investors also demand higher risk premiums due to relatively higher recovery risks. Finally, after inflation occurs, the increase in green bond coupon rates is less than that of general bonds. Inflation may have different effects on the dividend yields of individual companies, but there is no significant difference for the overall industry.
The Paris Agreement has highlighted the worldwide significance of adaptation. Many investors are considering the effects of climate change and resource scarcity when making decisions. Even while the whole amount of the environmental harm caused by climate change is yet unknown, recent scientific evidence is more frightening, and many governments are taking substantial measures to avert a calamity. The financial innovations and mechanisms created to ease the transition to a low-carbon economy will have far-reaching effects on markets, firms, intermediaries, and investors. Although economists have been working on the subject for decades, financial-economics professionals have only recently become interested in climate change. There has been a growing body of empirical and theoretical contributions in recent years that analyse the influence of climate risks on investment decisions for firms, financial intermediaries, and national governments, as well as the pricing and hedging of climate change risks. This study seeks to establish the role of multilateral climate change financing in the developing world vis-à-vis challenges and opportunities for Africa. Five determinants of the multilateral climate fund were established and they are namely; Reduction of Greenhouse gas emissions, Enabling Environments, Poverty and development linkages, Private investment and Public climate finance.
Green bonds are typically used for environmental protection projects. This paper explores the differences between general bonds and green bonds in Taiwan, as well as the impact of inflation. The findings are as follows: First, because green bonds support environmentally sustainable development projects, which require a longer time to realize their environmental benefits, they require longer repayment periods. Second, most green bonds have lower coupon rates than general bonds, indicating that investors are willing to accept lower interest income for the sake of environmental sustainability. Third, because green bonds invest in environmental protection projects with lower returns, investors also demand higher risk premiums due to relatively higher recovery risks. Finally, after inflation occurs, the increase in green bond coupon rates is less than that of general bonds. Inflation may have different effects on the dividend yields of individual companies, but there is no significant difference for the overall industry.
As extreme weather events continue to impact every continent and the world moves towards establishing a lower-carbon economy, the banking industry is expected to incorporate climate risk into their risk management practices. Climate change poses significant risks to bank loan portfolios through increased physical and transition risks. This study systematically analysed the literature to identify effective strategies for managing these risks. Our findings reveal that climate-related events can lead to substantial loan defaults and credit losses. To mitigate these impacts, banks can integrate climate risk into their risk management frameworks, adopt sustainable lending practices, and diversify their portfolios. Some banks have already implemented measures to mitigate climate risk through insurance policies, while others are incorporating sustainability criteria into their lending practices, such as financing green projects. By proactively addressing climate risks, banks can protect their portfolios, enhance financial resilience and contribute to a low-carbon economy.
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.
The Paris Agreement has highlighted the worldwide significance of adaptation. Many investors are considering the effects of climate change and resource scarcity when making decisions. Even while the whole amount of the environmental harm caused by climate change is yet unknown, recent scientific evidence is more frightening, and many governments are taking substantial measures to avert a calamity. The financial innovations and mechanisms created to ease the transition to a low-carbon economy will have far-reaching effects on markets, firms, intermediaries, and investors. Although economists have been working on the subject for decades, financial-economics professionals have only recently become interested in climate change. There has been a growing body of empirical and theoretical contributions in recent years that analyse the influence of climate risks on investment decisions for firms, financial intermediaries, and national governments, as well as the pricing and hedging of climate change risks. This study seeks to establish the role of multilateral climate change financing in the developing world vis-à-vis challenges and opportunities for Africa. Five determinants of the multilateral climate fund were established and they are namely; Reduction of Greenhouse gas emissions, Enabling Environments, Poverty and development linkages, Private investment and Public climate finance.
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 19:55 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 |