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: 10 / 10 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 01:24 UTC — 27 Oct 2026 19:04 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.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 37 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 66 | 10 | 10/10 | 10/10 |
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 10 / 10 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): 2026-10-22T01:24:51.971008+00:00 — 2026-10-27T19:04:03.923750+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 | 10 | 10/10 |
| 2018 | All selected publications | 0 | 10 | 10/10 |
| 2019 | All selected publications | 0 | 10 | 10/10 |
| 2020 | All selected publications | 0 | 10 | 10/10 |
| 2021 | All selected publications | 6 | 10 | 10/10 |
| 2022 | All selected publications | 15 | 10 | 10/10 |
| 2023 | All selected publications | 16 | 10 | 10/10 |
| 2024 | All selected publications | 17 | 10 | 10/10 |
| 2025 | All selected publications | 8 | 10 | 10/10 |
| 2026 | All selected publications | 4 | 10 | 10/10 |
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 | 10 |
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 | 3 | 15 | 22 | 3/3 | 5.0 | 7 | 66.7 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 7 | 22 | 44 | 7/7 | 3.14 | 2 | 85.7 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
The study was motivated by the need to highlight the roles played by social media marketing on consumers' purchase intention during the COVID-19 pandemic. Since it was a quantitative study, hypotheses were tested to generate findings. We used IBM SPSS 25.0 software to analyze using reliability statistics, descriptive statistics, and IBM SPSS Amos 26.0 software was used to do confirmatory factor analysis for the purpose of developing hypothesis, and SEM used for trying to fit the model. The primary data was mustered by personal interview in an online survey method through a structured questionnaire with five-point Likert scales from 240 Bangladeshi online consumers. These findings publicized that social media marketing (Facebook, Instagram, and YouTube) a significant stimulus on consumers purchase intention during COVID-19, and all factors except discount or coupon offer and brand awareness had an epoch-making and constructive connection with consumers’ purchase intention during the coronavirus malady (COVID-19) epidemic in Bangladesh.
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.
In this study, we review the literature to find how the financial development of a country attracts foreign direct investments for a sustainable real sector development of the country. The area is least focused on literature. Thus we don’t limit our search and review to any time or database or journal category. We find the theoretical logic and empirical evidence so far available in the literature. Our review finds that the development of the financial sector of a country is one of the most important attractors of FDIs. Theoretically, financial sector development works as a symbol of trust and goodness to the new potential investors and a good resource allocation channel for the existing investors. However, very few researchers find that FDIs are more prone to countries with a low developed financial system which may happen due to the presence of risk-taker foreign investors and risk-averse domestic entrepreneurs.
As the inclination to FDI shifts from developed to developing economies, investors are flocking to emerging markets, particularly to the Next-11 nations, which render additional growth and investment opportunities. Meanwhile, these countries have become popular FDI destinations; the goal of this study is to look at the major factors that make these countries appealing to FDI destinations. As a result, this research examines the factors that influenced FDI inflows into these nations from 1995 to 2019. Market size, trade openness, natural resource availability, economic stability, and infrastructure facilities are among the potential explanatory factors identified in this research. On the panel data set, which includes data from 11 nations, a fixed-effect model is used. The data show that market size, trade openness, natural resource availability, and economic stability are all possible predictors of FDI inflows to these nations, whereas infrastructure appears to be a minor one.
This study investigates the impact of some variables such as total revenue, total assets, total liabilities, total deposits, total unclassified loans, total classified loans, standard loans, special mention account loans, sub-standard loans, doubtful loans, and bad and loss loans on profit before tax. Unbalanced Panel Data were collected from the website of 45Commercial Bank of Bangladesh from the year 2010 to 2018. Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least square (2SLS), Generalized Methods of Moments (GMM) methods are used in this study. This research found that total revenue had a significant positive relationship with profit before tax in all the models except DK and GMM models. Total unclassified loans had a significant positive relationship and total liabilities had a significant negative relationship with profit before tax in all the models. Special mention account loans had a significant positive relationship with profit before tax in OLS and DK models and total classified loans had a significant positive relationship with profit before tax in GMM model.
It has been widely acknowledged that female workers account for 80% of the Ready Made Garments (RMG) industry’s workforce in Bangladesh but a number of studies estimated different male to female workers’ ratios ranging from 35: 65 to 55:45. To contribute to such debate, this paper leverage the data of the ‘Mapped in Bangladesh’ (MiB) project. While the objective of the MiB project is to enable transparency and accountability in the RMG sector by providing the industry stakeholders accurate, updated and authentic factory data collected through the factory census method and published in a digital map; this paper aims to shed light on the male to female ratio of workers employed in the RMG factories of Bangladesh is not 20:80, but it is 42:58 according to the findings from MiB data. Presenting such data, the study seeks to discuss how factory issues can influence the gender composition of RMG Workers. These issues such as factory locations, factory type, factory size and production sections are important to understand the challenges of future research addressing the gender composition of RMG workers in Bangladesh.
As the inclination to FDI shifts from developed to developing economies, investors are flocking to emerging markets, particularly to the Next-11 nations, which render additional growth and investment opportunities. Meanwhile, these countries have become popular FDI destinations; the goal of this study is to look at the major factors that make these countries appealing to FDI destinations. As a result, this research examines the factors that influenced FDI inflows into these nations from 1995 to 2019. Market size, trade openness, natural resource availability, economic stability, and infrastructure facilities are among the potential explanatory factors identified in this research. On the panel data set, which includes data from 11 nations, a fixed-effect model is used. The data show that market size, trade openness, natural resource availability, and economic stability are all possible predictors of FDI inflows to these nations, whereas infrastructure appears to be a minor one.
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.
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.
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 |