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: 8 / 8 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 01:23 UTC — 23 Oct 2026 11:28 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.
6 / 8 with data · 2 missing or unmatched. Percentages use all 8 selected publications.
6 / 8 with data · 2 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 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 | 0 | 0 | 0/0 | 0/0 |
| 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 | 3 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 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 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 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 | 3 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | 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 8 / 8 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): 2026-10-22T01:23:37.021778+00:00 — 2026-10-23T11:28:25.279816+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 | 8 | 8/8 |
| 2018 | All selected publications | 0 | 8 | 8/8 |
| 2019 | All selected publications | 2 | 8 | 8/8 |
| 2020 | All selected publications | 2 | 8 | 8/8 |
| 2021 | All selected publications | 0 | 8 | 8/8 |
| 2022 | All selected publications | 1 | 8 | 8/8 |
| 2023 | All selected publications | 1 | 8 | 8/8 |
| 2024 | All selected publications | 1 | 8 | 8/8 |
| 2025 | All selected publications | 0 | 8 | 8/8 |
| 2026 | All selected publications | 0 | 8 | 8/8 |
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 |
| 2016 | 1 |
| 2019 | 3 |
| 2021 | 1 |
| 2023 | 1 |
| 2025 | 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 0 | 1 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 6 | 0 | 5 | 6/6 | 0.0 | 0.0 | 0.0 | 6/6 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 1 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
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 exploration aims to test and dissect factors that impact bank fiscal performance and their impact on shareholder tips. The variables used are E-Banking, credit handed as an independent variable, and ROE as a dependent variable. This exploration also looks at the influence of ROE on shareholder tips proxied by the DPR. This exploration was conducted in all BPDs in Sumatra, there are 8 BPDs registered with the OJK during the 2019 – 2022 period. The exploration system used was descriptive exploration with a quantitative exploration approach. Data recycling analysis uses multiple and simple retrogression analyses. The exploration results show that E-Banking and the credit handed have a significant influence on ROE, both concertedly and collectively. Meanwhile, fiscal performance (ROE) also influences shareholder tips (DPR).
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.
The demonetisation footstep by the Government of India twisted complicated influences in the economy. Complete sectors of the economy had faced and produced mixed sensation results over the decision of demonetisation. India’s financial services struggled with demonetisation; on the other hand demonetisation affects utmost over the banking sector because it is substantial influenced services to transform money circulation in an Indian economy. Eradicating components of currency notes from circulation in an economy is demonetisation. It is as the processes of components of money are denied the status of legal tender. Consequently, ceased currency notes will not be account as valid currency in an economy. The term ‘demonetization’ is an instrument to shrink Inflation, Black Money, Corruption and terror funding, this step discourages a cash dependent economy in India. Government of India drive towards demonetisation has given a strong push to the popularity of digital banking and made helps with the alternative arrangements of e-banking and e –wallet to trade and commerce. Exploring the demonetisation emergence in an economy and impact on banking services ecosystem dynamics, this study take an abductive approach anchored in over 4 years of case study data regarding. The present study foremost intention is to be analysing the demonetisation impact over banking loans and advances. In this regard the present study is to be examining the pre demonetisation and post demonetisation period.
The banks in India have over 67,000 branches located across the country. All these are classified into two major categories, nonscheduled banks and scheduled banks. Scheduled banks includes commercial banks and the co-operative banks. The public sector banks are accountable for more than 78 percent of total banking industry in India. Even though private sector banks came later into the market, due to their customer servicing and easy banking features they are also competing equally with already existing public sector banks. so it is very essential to analyze how their financial performance is influenced by number of factors which willfurther suggest them where they need to concentrate more. in this article we have analyzed the correlation between return on total assets and other financial variables of selected private and public banks in India.
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 exploration aims to test and dissect factors that impact bank fiscal performance and their impact on shareholder tips. The variables used are E-Banking, credit handed as an independent variable, and ROE as a dependent variable. This exploration also looks at the influence of ROE on shareholder tips proxied by the DPR. This exploration was conducted in all BPDs in Sumatra, there are 8 BPDs registered with the OJK during the 2019 – 2022 period. The exploration system used was descriptive exploration with a quantitative exploration approach. Data recycling analysis uses multiple and simple retrogression analyses. The exploration results show that E-Banking and the credit handed have a significant influence on ROE, both concertedly and collectively. Meanwhile, fiscal performance (ROE) also influences shareholder tips (DPR).
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.
Clients’ non-performing loan is one of the problems faced by a Bank. The differences in character, culture, and people’s socio-economy influence a Bank, through its collectors, to solve the problem of this non-performing loan. The objective of this research was to find out social interaction done by Bank X in solving the non-performing loans of non-performing clients. The research used a qualitative method. The data were gathered by conducting interviews with nine informants – five clients, one collector, and three managers of Bank X in the area of Medan. The result of the research showed that in solving non-performing loan, Bank X did social interaction approach by conducting cooperation in achieving Agreement between collectors and clients, accommodation by understanding clients’ socio-cultural character in order to adjust to clients and to decrease the tension, and contravention by disgracing clients in front of their neighbors.
The introduction of the New Economic Policy (NEP) in 1991 by the Government of India (GoI) made it very clear that the viability of commercial banks is conditioned on their ability to make profits. In a globalized world, the whims and fancies of business cycles govern the fate of banks and a recessionary phase hampers the bank’s ability to pile on the profits thereby increasing their stock of non-performing assets. India, recently, is placed in a very bizarre situation, — some of the renowned banks are reporting huge losses but there is a very limited impact on stock markets. Strategically, the government, however, has taken corrective measures to arrest the growth of non-performing assets (NPAs) of banks. This paper builds upon a time series model capturing the position of NPAs of banks in India (excluding foreign banks operating in India). Empirically, there is a uni-directional causal relationship running from NPAs of banks to growth. Theoretically, what we can conclude is that imposing strict lending norms on banks actually manifests itself into a deeper recession, lowers growth and in turn aggravates the NPA problem further.
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 |