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.
2020 · Rommy Pramudya · Rommy Pramudya
2023 · Rejaul Karim · Md. Mustaqim Roshid · Farjana Bashar Shamme
2018 · Marcin Korytowski
2017 · Oguzhan Cepni · Ibrahim Ethem Guney
2016 · Doaa Mohamed Salman · Eyad M. Atya
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: 86 / 86 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: 22 Oct 2026 00:25 UTC — 27 Oct 2026 21:54 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.
63 / 86 with data · 23 missing or unmatched. Percentages use all 86 selected publications.
63 / 86 with data · 23 missing or unmatched. Percentages use all 86 selected publications.
86 / 86 with data · 0 missing or unmatched. Percentages use all 86 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 |
|---|---|---|---|---|---|
| 2012 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2013 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2014 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2015 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| 2016 | All selected publications | 17 | 17 | 17/17 | 17/17 |
| 2017 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2018 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2020 | All selected publications | 11 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 11 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2023 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2013 | All selected publications | 16 | 6 | 6/6 | 6/6 |
| 2014 | All selected publications | 22 | 5 | 5/5 | 5/5 |
| 2015 | All selected publications | 23 | 7 | 7/7 | 7/7 |
| 2016 | All selected publications | 55 | 17 | 17/17 | 17/17 |
| 2017 | All selected publications | 32 | 6 | 6/6 | 6/6 |
| 2018 | All selected publications | 18 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | 20 | 6 | 6/6 | 6/6 |
| 2020 | All selected publications | 55 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 55 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 23 | 5 | 5/5 | 5/5 |
| 2023 | All selected publications | 44 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 21 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 25 | 2 | 2/2 | 2/2 |
| 2013 | All selected publications | 47 | 6 | 6/6 | 6/6 |
| 2014 | All selected publications | 41 | 5 | 5/5 | 5/5 |
| 2015 | All selected publications | 69 | 7 | 7/7 | 7/7 |
| 2016 | All selected publications | 168 | 17 | 17/17 | 17/17 |
| 2017 | All selected publications | 78 | 6 | 6/6 | 6/6 |
| 2018 | All selected publications | 35 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | 45 | 6 | 6/6 | 6/6 |
| 2020 | All selected publications | 127 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 98 | 11 | 11/11 | 11/11 |
| 2022 | All selected publications | 49 | 5 | 5/5 | 5/5 |
| 2023 | All selected publications | 54 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 22 | 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 86 / 86 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): 2026-10-22T00:25:55.178620+00:00 — 2026-10-27T21:54:45.232849+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 | 21 | 86 | 86/86 |
| 2018 | All selected publications | 31 | 86 | 86/86 |
| 2019 | All selected publications | 52 | 86 | 86/86 |
| 2020 | All selected publications | 60 | 86 | 86/86 |
| 2021 | All selected publications | 87 | 86 | 86/86 |
| 2022 | All selected publications | 110 | 86 | 86/86 |
| 2023 | All selected publications | 140 | 86 | 86/86 |
| 2024 | All selected publications | 147 | 86 | 86/86 |
| 2025 | All selected publications | 102 | 86 | 86/86 |
| 2026 | All selected publications | 49 | 86 | 86/86 |
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 |
|---|---|
| 2012 | 2 |
| 2013 | 6 |
| 2014 | 5 |
| 2015 | 7 |
| 2016 | 17 |
| 2017 | 6 |
| 2018 | 3 |
| 2019 | 6 |
| 2020 | 11 |
| 2021 | 11 |
| 2022 | 5 |
| 2023 | 5 |
| 2024 | 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 | 86 | 392 | 858 | 86/86 | 4.56 | 4.0 | 95.3 | 86/86 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to investigate the association between non-performing loans (NPLs) and the profitability of banks in Bangladesh. The data of twenty-five listed banks for the twelve years spanning from 2010 to 2021 have been analyzed to achieve the research objective. through the use of the ordinary least square (OLS) regression model, we found that the NPL has a negative significant impact on the profitability determined by the return on asset (ROA). In addition, the study revealed that the bank size, which is represented by banks’ total assets, is also inversely related to the profitability of the sample banks used in this research. The study concludes that the stakeholders, particularly the management of the banks, as well as the regulators, should be more cautious about NPLs and should try to lessen the level of NPLs because it can bring devastating results both on the microeconomic as well as on macroeconomic metrics of a developing country like Bangladesh.
Bu çal??man?n amac?, Türkiye’de hayat d??? sigortac?l?k sektöründe aktif karl?l??? ile firmaya özgü faktörler aras?ndaki ili?kiyi tespit ederek aktif kârl?l???n?n etkinlikten mi yoksa yo?unla?madan m? kaynakland???n? belirlemektir. Bu amaçla, Türk sigorta sektöründe faaliyet gösteren 36 hayat d??? sigorta ?irketi aras?nda 2015 y?l? verilerine göre pazar?n toplam %83.38’ini olu?turan 15 sigorta ?irketinin 2010-2015 dönemine ait mali verileri ile performans ili?kisine yönelik Period SUR panel veri analizi yap?lm??t?r. Analiz sonuçlar?na göre, aktif büyüklü?ü, likidite ve pazar pay? de?i?kenleri ile aktif karl?l??? aras?nda pozitif ve istatistiki olarak anlaml? bir ili?ki tespit edilmi?ken kald?raç, hasar/prim oran? ve firma ya?? de?i?kenleri aras?nda ise negatif ve istatistiki olarak anlaml? bir ili?ki tespit edilmi?tir. Analiz dönemi boyunca Herfindahl–Hirschman Endeksi de?erleri 1.500’ün alt?nda oldu?u için Türkiye’de hayat d??? sigortac?l?k sektörünün yo?un olmayan bir piyasa görünümünde oldu?u tespit edilmi?tir. Bu nedenle, hayat d??? sigortac?l?k sektöründe aktif kârl?l??? yo?unla?madan daha ziyade faaliyetlerdeki etkinlikten kaynaklanmaktad?r.
Financial inclusion, especially the adoption of fintech, has emerged as a crucial avenue for removing the financial access divides in developing countries, including Bangladesh. Following the comprehensive analysis, this article intends to outline Bangladesh's recent experiences with fintech-based financial inclusion, identify the short-comings and hence make policy suggestions. Being a descriptive research, cross-sectional and observational research approaches are applied for the explanatory analysis of secondary data. Results suggest an urban-rural gap in the implementation of digital financial services, with urban areas consistently having higher rates of fully online branches and a greater number of financial machines. Despite this, the sharp rise in the issuance of active cards is a positive sign suggesting an expansion of consumer base and an adoption of electronic modes of payment. Moreover, inter-bank electronic fund transfers and online banking have experienced increasing uptake, revealing a progressing trend towards digital transactions within the banking industry. Additionally, the study identifies a speedy growth in the number of mobile financial services accounts in both urban and rural areas. This study adds to the exchange of ideas regarding financial inclusion by carrying out a detailed study of Bangladesh's digital financial transformation, exemplifying the accomplishments, obstacles, and future research directions. It highlights the need for targeted policies and ongoing research efforts to build inclusive financial systems to serve the entire society’s interest. Nevertheless, the observations will have both theoretical and practical significance, contributing towards building capability in harnessing technology for sustainability, community uplifting, and shaping a brighter future.
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. 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.
The purpose of this study is to determine which indicators are more capable of showing more accurate sell and buy signals on the LQ45 index by using the oscillator indicator Moving Average Divergent Convergent (MACD), Bollinger Band, and Relative Strength Index (RSI). The results in this study indicate that the sell signal can be captured well by the Bollinger band and MACD indicators, but it cannot be captured properly by the RSI, the volume can be small or heading and are in the side ways, while the MACD plays a too slow role in capturing the signal buy compared to Bollinger bands and RSI. The use of a single indicator will never show a buy and sell signal that is really accurate, this is based on the results of research that shows the difference in timeliness in Bollinger, RSI and also MACD so that the combination of several types of indicators will be better compared to using single indicators. Although in statistics there are no significant differences, there are only differences in increment and improvement in the placement of existing values, but in this case, the order of this value is crucial for traders because it requires very high accuracy to determine the right decision in daily transactions.
Financial inclusion, especially the adoption of fintech, has emerged as a crucial avenue for removing the financial access divides in developing countries, including Bangladesh. Following the comprehensive analysis, this article intends to outline Bangladesh's recent experiences with fintech-based financial inclusion, identify the short-comings and hence make policy suggestions. Being a descriptive research, cross-sectional and observational research approaches are applied for the explanatory analysis of secondary data. Results suggest an urban-rural gap in the implementation of digital financial services, with urban areas consistently having higher rates of fully online branches and a greater number of financial machines. Despite this, the sharp rise in the issuance of active cards is a positive sign suggesting an expansion of consumer base and an adoption of electronic modes of payment. Moreover, inter-bank electronic fund transfers and online banking have experienced increasing uptake, revealing a progressing trend towards digital transactions within the banking industry. Additionally, the study identifies a speedy growth in the number of mobile financial services accounts in both urban and rural areas. This study adds to the exchange of ideas regarding financial inclusion by carrying out a detailed study of Bangladesh's digital financial transformation, exemplifying the accomplishments, obstacles, and future research directions. It highlights the need for targeted policies and ongoing research efforts to build inclusive financial systems to serve the entire society’s interest. Nevertheless, the observations will have both theoretical and practical significance, contributing towards building capability in harnessing technology for sustainability, community uplifting, and shaping a brighter future.
This paper aims to examine the financial performance of Bangladeshi listed commercial banks. The study analyzed the financial performances of banks categorized into three generations—first, second, and third—based on their year of commencement of operations in the country. The data of a total of 24 banks, 8 from each generation, listed in the Dhaka Stock Exchange (DSE), has been collected from audited financial statements for the time period of 13 years, from 2010 to 2022. Data has been analyzed using different ratios of profitability, liquidity, capital adequacy, operational efficiency, and credit risk. The ANOVA test also has been used to make a comparison of profitability—the return on assets (ROA), and return on equity (ROE) of the banks of different generations. According to the results, the average profitability ratios in terms of ROA, and ROE of the second-generation banks showed their credibility than banks of other generations; while first generation banks kept higher liquidity, and capital adequacy with higher credit risk than the banks of other generations. The first-generation banks also showed a lower cost-expense ratio, and a higher efficiency in terms of operation, than the banks in the second and third generations. The research also discovered that the profitability of banks of different generations significantly varies from one another.
In the past decade, Southeast Asia has seen the development of financial inclusion, as evidenced by the growth of the penetration, availability, and usage dimensions of financial inclusion. This study analyses the impact financial inclusion has on economic growth, represented by GDP per capita growth, and unemployment using data from Indonesia, Malaysia, Thailand, the Philippines, and Cambodia. The authors employed panel data regression with fixed effect and random effect models to analyse the data. The results show that the number of commercial bank branches and outstanding loans statistically significantly affect GDP per capita growth, while the number of saving/deposit accounts does not. All three variables are shown to have a statistically significant impact on unemployment.
This study aims to enhance credit risk identification, improve loan borrower review efficiency, and increase default prediction accuracy rate using data mining and machine learning techniques. The study also employs deep learning to develop a consumer loan default prediction model that minimizes credit risks and ensures consistent development. The researchers collected data from a survey of 1000 participants, stratified into local and foreign banks, and selected the top 11 banks based on turnover and customer volume. To construct the machine learning model, Keras, a neural network library that runs on TensorFlow, was utilized. The model predicts loan applicant default likelihood. The study's practical implications demonstrate a noteworthy success rate of customer default prediction, which can significantly benefit banks. The model was evaluated on a test set of 250 records and achieved a test set accuracy of 95.2%, correctly predicting the default state of 238 out of 250 respondents.
The banking system’s role as an intermediary between depositors and borrowers makes its stability a crucial element of the economy. Individual bank stability impacts the stability of the financial sector and, consequently, the real sector and economic growth. This study is a detailed investigation of bank stability scores for the Turkish banking sector. Turkey experienced a major banking crisis from 2000 to 2001. However, with an improved regulatory environment and structural reforms, its resilience to shocks increased significantly in subsequent years. The present study contributes to the literature in three areas. First, it applies eight variations of the Z-score to the Turkish banking sector to test the importance of time and risk variation. Second, it investigates the impact on stability scores of several factors–the implementation of new capital regulations and Basel III liquidity rules, the Turkish lira crisis and the effects of COVID-19). Finally, it measures the contribution to systemic risk of each Turkish bank using the leave-one-out (LOO) Z-score method; this is the first study to use this method to analyse the contribution of different bank types to the overall stability of the sector.
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 |