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: 27 / 27 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 07:23 UTC — 22 Oct 2026 12:05 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.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 selected publications.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 selected publications.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 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 | 1 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | 6 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 11 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 0 | 3 | 3/3 | 3/3 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | 14 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 15 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 12 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 7 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | 22 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 21 | 3 | 3/3 | 3/3 |
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 11 | 3 | 3/3 | 3/3 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 3 | 4 | 4/4 | 4/4 |
| 2020 | All selected publications | 21 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 27 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 17 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 9 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 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 27 / 27 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): 2026-10-21T07:23:01.304603+00:00 — 2026-10-22T12:05:25.294678+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 | 27 | 27/27 |
| 2018 | All selected publications | 3 | 27 | 27/27 |
| 2019 | All selected publications | 5 | 27 | 27/27 |
| 2020 | All selected publications | 13 | 27 | 27/27 |
| 2021 | All selected publications | 7 | 27 | 27/27 |
| 2022 | All selected publications | 14 | 27 | 27/27 |
| 2023 | All selected publications | 22 | 27 | 27/27 |
| 2024 | All selected publications | 22 | 27 | 27/27 |
| 2025 | All selected publications | 23 | 27 | 27/27 |
| 2026 | All selected publications | 12 | 27 | 27/27 |
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 | 1 |
| 2013 | 2 |
| 2014 | 3 |
| 2015 | 1 |
| 2016 | 3 |
| 2019 | 4 |
| 2020 | 1 |
| 2021 | 3 |
| 2022 | 4 |
| 2024 | 3 |
| 2025 | 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 |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 1 | 0 | 1 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 2 | 9 | 11 | 2/2 | 4.5 | 4.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 12 | 18 | 55 | 12/12 | 1.5 | 0.0 | 41.7 | 12/12 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 12 | 41 | 67 | 12/12 | 3.42 | 1.0 | 66.7 | 12/12 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to evaluate the effect of rapid changes in financial technologies and their impact on the financial services industry of India. A descriptive study has been made on the implementation of financial technologies in modern-day financial services Industries. An intensive literature review has been done from the existing most recent available journals, newspaper articles, government websites, and magazines. We have discussed the effects of the financial technologies on the existing financial system of India, the threats and challenges faced by the regulators in regulating the novel disruptive technologies. We have also discussed potential threats, challenges and future prospects of upcoming technologies in the mutual funds industry in India. Based on the literature review, it is found that financial technologies (FinTech) have a positive and important effect on the financial services industry of India. The AUM (Asset Under Management) has seen a tremendous jump in the recent past. It has also increased the customer experience with better access to the back office, even from remote places. In addition, the paper has also discussed the challenges faced by the regulators, who are yet to fully understand the implication of the fast-changing technological environment around us. Finally, this article contributes to the knowledge building and understanding of financial technologies and its impact on the financial industry, challenges, and future prospects.
Human capital is a significant element in the attainment of sustained competitive advantage and economic survival of organizations. The study explored whether human capital mediates the nexus of human resource management practices and organizational performance. A field study was conducted among 11 internationally and 4 indigenously owned banks. The hypothesized relationships were supported by the data. The results show that the association between selective staffing with the levels of human capital was significant. The results also show that the levels of human capital influenced organizational performance significantly. The results further show that human capital mediated the nexus of HRM practices and organizational performance. The generalizability of the results obtained may be constrained since the present study focused on the banking industry. The study suggests the creation and maintenance of valuable human capital promote competitiveness and sustained competitive advantage. The study contributes to the extant literature by empirically evidencing that human capital mediated the nexus of HRM practice and organizational performance.
The automotive industry is standing on the edge of the digital era. Digitization is the motivating force behind this change and is influencing every aspect of consumer behavior. Forces behind this digital transformation are the new technological possibilities which range from comprehensive connectivity, 3D printing, and the social network of virtual solutions as well. The impact of digitization can already be seen in today’s world and also in the automotive industry of India. Digitization will play an imperative role in the upcoming years such as artificial intelligence. This paper is primarily concerned with the recent trends of digitization and it also tries to measure the impact of digitization on the automobile supply chain between automobile manufacturers and suppliers. It is discussed the thrust on the potentialities of digitalization in the automobile industry of India and its impact on the overall performance of the industry. The study concluded that digitization has a significant impact on the automotive industry of India. Today, all the business practices become digitalized and foreign players use advanced technology in their products as compared to the national automotive players. The selling of automotive products is increased after the adoption of more advanced technology. It upgrades the quality of products and its service after sale which ultimately leads to the customer and brand loyalty used by the consumers.
The link between stock market development and economic activity has always been the subject of considerable debate in the field of economics and it raises empirical question whether stock market development influences economic activity or whether it is a consequence of increased economic activity. This study attempts to investigate the direction of causality between stock market development and economic growth in the Indian context. Using the cointegration and causality tests for the period June 1991 to June 2013, the study confirms a well defined long-run equilibrium relationship between the stock market development indicators and economic growth in India. The empirical results show bidirectional causality between market capitalisation and economic growth and unidirectional causality from turnover ratio to economic growth in the long-run and short-run. By and large, it can be inferred that the stock market development indicators viz. market capitalisation and turnover ratio have a positive influence on economic growth in India.
The problem of NPA is not limited to only Indian public sector banks, but it prevails in the entire banking industry. Major portion of bad debts in Indian Banks arose out of lending to the priority sector at the dictates of politicians and bureaucrats. If only banks had monitored their loans effectively, the bad debt problem could have been contained if not eliminated. The present study has been designed to illustrate the necessity and the nature of the non-performing assets in Indian Bank, Tamil Nadu. Finding out Non Performing Assets –NPA- under the Priority sector lending in Indian Bank and Compare with Public Sector Banks and making appropriate suggestions to avoid future NPAs and to manage existing NPAs in Indian Bank are the other major objectives of this study. The scope of this study covers on the basis: (i) measuring for the banks to avoid future NPAs & to reduce existing NPAs, (ii) guiding for the government in creating & implementing new strategies to control NPAs, (iii) selecting appropriate techniques suited to manage the NPAs and develop a time bound action plan to arrest the growth of NPAs.
This study investigates the relationship between corporate governance and firm performance in the Bangladeshi insurance sector, focusing on variables like board independence, female directors, audit committee size, leverage, and firm age. Using a sample of 42 insurance firms from 2017 to 2021, regression analysis is employed to assess these relationships. The findings show that board independence positively impacts performance, while audit committee size, leverage, and firm age have negative effects. Female directors exhibit a marginal but weak positive influence. This research contributes to the literature by providing empirical evidence from a developing economy, where limited studies exist. It also offers insights into governance practices in emerging markets. The implications suggest that policymakers and corporate leaders in Bangladesh should prioritize enhancing board independence, managing leverage, and promoting gender diversity to improve performance. Future research could explore causal relationships and extend the analysis to other sectors or emerging markets, considering cultural and regulatory factors.
The banking sector is a linchpin of economic growth and development, with its prosperity heavily influenced by various factors of the economy. The cooperative model of banking to achieve both of personal and community development goals has been chosen as an instrument for fostering high and stable financial growth. As a key metric for assessing the financial health and profitability of banks, including cooperative banks, NPAs plays a crucial role in evaluating their stability and resilience. Notably the Indian Banking system, now, compares with the global benchmarks, reflecting commendable Return on Assets (ROA), Return on Equity (ROE) and Credit risk (NPAs). The purpose of this article is an attempt to analyze the trends of NPAs (Gross NPAs and Net NPAs) of selected Urban Cooperative Banks (UCBs) and assessing the profitability using ROA and ROE over the period of 2016-2022 by employing the linear trend analysis and multiple regression model. Secondary sources provided the information gathered for the study. The study indicates that the trend of NPAs is fluctuating over time with low minimal correlation. GNPAs and NNPAs have a significant impact on ROA for the selected UCBs- Nagarik Samabay Bank (NSB) and Gauhati Cooperative Urban Bank (GCUB). However, during the period 2020-2022, GNPA sand NNPAs did not exhibit significant influence on ROE for Gauhati Cooperative Urban Bank. Hence, the dynamism of NPA and their impact on profitability on banking sector will reflect the growth of financial sector of the economy.
This paper investigates the factors that form bank risks in Bangladeshi state-owned banks. As a representation of bank risk, non-performing loans have been considered the dependent variable for this study. The relevant data have been extracted from six state-owned banks in Bangladesh from 2013 to 2022. The final dataset consists of 60 firm-year observations. The ordinary least square (OLS) regression with robust standard errors model is utilized to find the relationship of bank risks with determinants like asset size, efficiency, liquidity, profitability, leverage ratio, capital adequacy ratio, and loan to asset ratio. The findings say that bank size and loan-to-asset ratio have a highly significant positive relationship with bank risk, whereas profitability, capital adequacy ratio, and bank efficiency have a significant negative association with bank risk. On the other hand, leverage and liquidity are negatively and positively correlated with no statistical significance. To check the study's robustness, another proxy of bank risk, loan loss provision has been used and the results are almost similar. State-owned banks operate in every economy with a different mindset than the general commercial banks. Hence, policymakers should take necessary initiatives based on this study to bring down the high bank risks in state-owned banks in Bangladesh.
The novelty and advancement of technology have explored new avenues in the education sectors. Now e-learning has blended with face-to-face learning to increase its effectiveness. An integrated model is being proposed in this study to measure the continuance usage intention of students adopting e-learning services. With the constructs of ECM (confirmation, perceived usefulness), perceived ease of use and perceived self-efficacy proposed to measure their effect on satisfaction. Besides, to explore the impact of quality features on satisfaction and continuance intention, three major determinants of D&M’s ISS model such as system quality, service quality and information quality included in this study. 410 responses collected to do quantitative analysis. The PLS-SEM analysis showed that perceived ease of use has the strongest effect on perceived usefulness, followed by perceived self-efficacy on perceived ease of use and satisfaction with continuance intention.The study reveals that challenges in developing countries are unique and drives the learners differently than developed countries. The growing e-learning industry requires widespread research from national and institutional perspectives for holistic development in the Bangladesh education market.
This paper examines the consequences of banks’ performance on bank risk. The paper forms a theoretical model and delivers empirical evidence to identify that banks suffer in performance as the loans become bad. Using panel data from a sample of five (05) South-Asian emerging economies from 2011 to 2019, we have found that the banks are highly influenced by the development of non-performing loans (NPLs). We have primarily used Return on Asset (ROA) followed by Return on Equity (ROE) as a substitution to the performance of the banks and NPL as the proxy of bank risk. Simultaneous regression applying 3sls finds that Non-Performing Loan (NPL) hinders banks' growth, negatively affecting their profitability.
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 |