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: 19 / 23 publications (82.6%). 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 01:08 UTC — 27 Oct 2026 19:06 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.
23 / 23 with data · 0 missing or unmatched. Percentages use all 23 selected publications.
23 / 23 with data · 0 missing or unmatched. Percentages use all 23 selected publications.
23 / 23 with data · 0 missing or unmatched. Percentages use all 23 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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 7 | 7 | 6/7 | 7/7 |
| 2026 | All selected publications | 3 | 3 | 0/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 15 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 16 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 22 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 2 | 7 | 6/7 | 7/7 |
| 2026 | All selected publications | — | 3 | 0/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 22 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 20 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 23 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 2 | 7 | 6/7 | 7/7 |
| 2026 | All selected publications | 0 | 3 | 0/3 | 3/3 |
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 23 / 23 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): 2026-10-22T01:08:09.452513+00:00 — 2026-10-27T19:06:14.330626+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 | 1 | 23 | 23/23 |
| 2018 | All selected publications | 3 | 23 | 23/23 |
| 2019 | All selected publications | 0 | 23 | 23/23 |
| 2020 | All selected publications | 3 | 23 | 23/23 |
| 2021 | All selected publications | 9 | 23 | 23/23 |
| 2022 | All selected publications | 4 | 23 | 23/23 |
| 2023 | All selected publications | 13 | 23 | 23/23 |
| 2024 | All selected publications | 22 | 23 | 23/23 |
| 2025 | All selected publications | 25 | 23 | 23/23 |
| 2026 | All selected publications | 13 | 23 | 23/23 |
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 |
|---|---|
| 2013 | 1 |
| 2014 | 1 |
| 2016 | 1 |
| 2020 | 1 |
| 2021 | 3 |
| 2023 | 2 |
| 2024 | 4 |
| 2025 | 7 |
| 2026 | 3 |
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 | 23 | 65 | 96 | 23/23 | 3.42 | 1 | 68.4 | 19/23 · 82.6% |
* 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.
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.
This research paper intends to evaluate an idea about bankers’ perceptions on green banking by getting a candid opinion from conventional banks’ bankers in Bangladesh based on a quality survey questionnaire covers relevant areas like benefits of green banking, superior officials who serve green banking services, taken eco-friendly initiatives, getting support from proper authorities, safeguarding environment pollution and rewards for adopting green banking. Considering the highest mean score of items in each group, this paper insights about green banking is environment-friendly banking, managers and officers are resourceful, emphasizes on recycling of left-over materials, keeping the environment pollution free, and performs to reduce resource wastages. This paper also finds that support from the government should be getting heightened priority to enhance its performance and area. So it can be easily presumed that green banking already put a great impact on a great portion of the banking industry in Bangladesh so far.
Bank profitability plays a significant role in the growth and development of an emerging economy. The purpose of the study was to examine the impact of bank characteristics, industry concentration and macroeconomics variables on commercial bank profitability in Bangladesh from 2007-2017. Bank profitability is proxied by return on assets (ROA), return on equity (ROE) and net interest margin (NIM). The study is based on secondary data and Hausman test has been performed using STATA software in favor of fixed effect modeling. Panel regressions shows that cost efficiency has significant negative impact on ROA and NIM. The positive impact of loan to deposit ratio with ROA suggests that efficient fund management including investment and assessed expenditure should be emphasized. Bank size has significant negative impact on all the measures of profitability, which indicates that monopolistic competition will reduce banking profit. Credit risk has significant positive impacts on ROE. Industry concentration measured by CR3 is positively related with ROE and has significant negative relation with bank profitability (ROA). Among macroeconomic variables inflation has significant positive and bank spread has significant negative impact on ROE. The coefficients of all the macroeconomic variables have been found to be significantly related to bank profitability while measured by NIM. Our study recommends further research with other explanatory variables such as, corporate governance, corporate social responsibility (CSR) and deposit insurance to accelerate the model and construct the econometric model by using structural equation modeling, mediation effect modeling etc.
Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.
Digital expansion is conceived as a firm-level consequence after adoption, capturing both the breadth and depth of digital tools usage in operational and customer-facing business operations. The study investigates five readiness dimensions based on survey data of 388 small firms: capital adequacy, technological infrastructure, digital literacy, preference adaptation, and marketing investment. The results suggest that capital adequacy and digital literacy are positively and significantly related to digital expansion whereas technological infrastructure, preference adaptation and marketing investment are not statistically significant in the estimated model. Coefficient-comparison tests also imply that the important internal readiness variables are more strongly related to digital expansion than the market-oriented readiness variables. This study contributes to the literature on digital transformation in small firms by showing that, in a resource-constrained emerging-economy environment, internal financial and capability-related conditions are more strongly associated with digital expansion than market-facing readiness. The results have substantial implications for Bangladesh suggesting that digital financial support should be coupled with digital literacy development and targeted capability-building for small companies.
This study aims to assess and rank all thanas in Bangladesh according to their performance in financial inclusion. It employed a composite index for that purpose, using three proxies of financial inclusion: deposit per account, advance per account, and advance deposit ratio. Cross-sectional data obtained from the Scheduled Banks Statistics of Bangladesh Bank are utilized to rank 615 thanas in Bangladesh. It categorizes 615 thanas into three classifications: high, medium, and poor financial inclusion. There are large differences in the availability and utilization of financial services among thanas. Thanas have a low level of integration into the formal financial system, as indicated by the average financial inclusion index of 0.068 and a maximum of 0.628. The rate of financial inclusion is continuously lower in rural, remote, and hilly regions compared to economically active and urban areas. Kotwali in Chattogram, Dhaka, etc., is a higher-ranked thana that demonstrates stronger financial inclusion, with higher per-account values and greater reliance on credit. By comparison, the lower-ranked thanas such as Ramgati, Char Shasivuson, Madan etc. are characterized by a low level of financial integration, poor institutionalization as well as extensive use of informal finance. The paper concludes that the present policy actions have failed to create broad financial inclusion improvements. It proposes multi-dimensional interventions, which are focused to tackle the urban-rural divide. This study will provide the policy makers with useful information to determine the actual situation by determining the highly included and excluded thanas in Bangladesh. Eventually, it will help the interested parties to develop thana or area-based measures to secure financial inclusiveness of all that result to promoting comprehensive and sustainable economic development. The study is also unique because it is likely to be the first initiative that has attempted the study at micro level i.e. thana based analysis of financial inclusion in Bangladesh.
The research investigates how goal contagion impacts the acceptance of digital technologies and also explores the moderating effect of COVID-19 and survival instinct within the interconnection between goal contagion and the acceptance of digital technologies. The research has undertaken partial least squares structural equation modeling to identify the direct as well as moderating effects based on a sample of 250 individuals across diverse firms in Bangladesh. The research also involved the Importance-Performance Map Analysis approach (IPMA) to explore key areas of importance and performance, thus providing a holistic understanding of key factors impacting the acceptance of digital technologies. Then, an ANN model analysis was used to determine how important the components determined by the PLS-SEM study were in terms of relative influence. The study revealed that others’ behavior and situational context have a significant impact on goal contagion. The outcome also showed that goal contagion has a significant impact on the acceptance of digital technologies; besides, survival instinct and COVID-19 have a statistically significant moderating effect between goal contagion and the acceptance of digital technologies. The IPMA findings showed that COVID-19 and goal contagion are the most important factors for the acceptance of digital technologies. The ANN findings revealed that situational context is the most contributing construct for goal contagion. The findings also demonstrated that COVID-19 and goal contagion are the most influential constructs for the acceptance of digital technologies. The findings of this research contribute significantly to the relevant knowledge by promoting a theoretical framework for comprehending the factors that influence the acceptance of digital technologies. Furthermore, this research illustrates valuable insights for companies that are planning to make strategic decisions regarding their digital technologies.
Employee promotion in State-Owned Commercial Bank (SOCB) and Private Commercial Bank (PCB) depends on Key Determining Factors (KDF). The study aims to identify these factors. The objective is to compare the impact of KDF on employee promotion between SOCB and PCB. The study finds that Education, Qualifications, Job performance and Skills do not impact promotion in SOCB, whereas Experiences, Tenures, Work ethics and Dependability determine employee promotion in PCB. Social relationships and interpersonal relationships both influence employee promotion at PCB. Bias and Favouritism exist from a certain level in SOCB, whereas the study unveils a strong presence of Bias and Favouritism in PCB. There is no presence of Age, Gender and Ethnicity in employee promotion in SOCB, while PCB experienced a mixed influence of Age, Gender and Ethnicity on employee promotion. While there is no influence of Union Status, Firm Size on employee promotion in PCB, an indirect influence on employee promotion has been observed in this study. Luck and External factors both influence employee promotion in SOCB and PCB. Seniority is maintained up to a certain level in SOCB, after that, both merit and seniority is considered whereas performance plays a pivotal role in employee promotion in PCB.
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 |