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: 7 / 7 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 00:49 UTC — 21 Oct 2026 07:22 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.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 6 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 4 | 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 7 / 7 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): 2026-10-21T00:49:31.829712+00:00 — 2026-10-21T07:22:56.388351+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 0 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 0 | 7 | 7/7 |
| 2022 | All selected publications | 2 | 7 | 7/7 |
| 2023 | All selected publications | 3 | 7 | 7/7 |
| 2024 | All selected publications | 3 | 7 | 7/7 |
| 2025 | All selected publications | 4 | 7 | 7/7 |
| 2026 | All selected publications | 1 | 7 | 7/7 |
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 |
|---|---|
| 2019 | 1 |
| 2022 | 3 |
| 2023 | 1 |
| 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 Research in Business and Social Science SSBFNET | 7 | 8 | 13 | 7/7 | 1.14 | 1 | 85.7 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
The main goal of this study is to evaluate customer perceptions of the competitiveness of Absa Bank in South Africa. To achieve this objective, the study is divided into two sections, which were designed as the main research questions. The first question aimed to determine customer perceptions of the level of bank competition in South Africa, while the second question focused on customer perceptions of Absa's competitiveness within the South African banking sector. It was revealed through an Absa Bank communication that Barclays Bank (UK), the major shareholder, was withdrawing from Barclays Africa Group aka Absa Bank due to ongoing uncertainties in the African market. This departure has resulted in mixed reactions from the market, with customers expressing skepticism about the potential impact on the bank's performance. The study was conducted at the Durban Central branch, which serves approximately 150,000 customers. A sample of 400 walk-in customers at the branch was selected using a non-probability convenience sampling technique. Out of the 400 questionnaires distributed, 13 were discarded due to incomplete responses. This resulted in 387 questionnaires being returned. The collected data was analysed using the latest computerized Statistical Package for Social Sciences (SPSS) version 24.0. The findings of the study indicate that competition does exist within the banking sector, with banks employing pricing strategies to compete for customers. Most customers perceive Absa Bank as being competitive in the market. As a recommendation, it is suggested that branch management regularly conduct customer surveys to engage customers and identify areas for improvement that can be incorporated into the branch operations.
This paper analyses the effect of the treasury single account (TSA) on the financial performance of commercial banks in Tanzania over the period 2015-2020. The selected commercial banks include NMB Plc, CRDB Plc, EXIM Bank, NBC and DCB in Tanzania’s banking sector. The study employs a descriptive research design and the CAMEL Rating Analysis approach. The findings show that all the selected commercial banks have maintained a strong position on their composite rating system before and after the TSA implementation. They are sound in the aspects of capital adequacy, management quality, earning capacity and liquidity conditions.
Commercial banks in Kenya operate in quite dynamic financial market environment and continue to experience stiff competition in the provision of financial services. The liberation of the financial markets has resulted into an upsurge in the number of institutions providing financial products and services, threatening the future of Kenyan commercial banks. This study aimed at determining the effect of strategic alliances on competitive advantage of commercial banks in Kenya. The objectives were to determine effect of joint ventures, equity alliances, and joint research and development on the competitiveness of Kenyan banks. The following theories informed this research; Resource Based View theory, competitive theory, and resource dependence theory. Causal research design was adopted where all the 42 Kenyan commercial banks formed the target population. Census survey sampling design was applied and semi-structured questionnaire used. Reliability and validity results were used to improve the research instrument prior to the actual data collection. Data was analyzed using descriptive and inferential statistics. Study found that joint venture (?=0.435, p=0.000) equity alliances (?=0.227, p=0.018), and joint research and development (?=0.0.612, p=0.000) had positive significant effects on competitive advantage. With a coefficient of determination (R-square) of 68.9% and overall p-value of 0.000, the study concluded strategic alliances have a statistical significant effect on competitive advantage. The study recommends that managements of commercial banks should fast-truck implementation of such alliances to for improved competitiveness.
Bank Indonesia Regulation No.13/1/PBI/2011 requires banks to regularly conduct a self-assessment using the RBBR (Risk-based Bank Rating) risk approach at the individual and consolidated levels. This health assessment is called RGEC (Risk Profile, Good Corporate Governance, Earnings, and Capital). This research aims to determine the effect of bank soundness with Risk Profile, Good Corporate Governance, Earning and Capital on Firm Value at Conventional Banks listed on the Indonesian Stock Exchange for the period 2019 to 2021. The sampling technique used in this study is purposive sampling. The sample criteria are conventional banking companies registered and publish complete annual financial statements that do not merge during 2019–2021. This study used 40 samples based on predetermined criteria. Analysis of the data in this study using Microsoft Excel 2019 and hypothesis testing using panel data regression analysis with the EViews version 12.0 program with a significance level of 5%. The results of this study are (1) Risk Profile using Non-Performing Loan does not affect firm value, (2) Good Corporate Governance has a positive effect on firm value, (3) Earning using Return on Assets has no effect on firm value, (4) Capital using Capital Adequacy Ratio has a positive effect on firm value. The implications of this research for banks are to increase company value; conventional banks can pay attention to the Risk Profile, Good Corporate Governance, Earnings, and Capital (RGEC) to improve their performance and for investors to be a reflection of good information to invest. The limitations of this study are that some banking companies do not publish complete financial statements, and research variables, namely profile risk and earning, do not support the theory, so they require further research.
The primary purpose of this research study is to reflect on financial anomalies, especially bank scams in Bangladesh. This study is an empirical approach developed through a well-structured Likert-scaled questionnaire to indicate different human behaviors, psychologies, and emotions that considerably impact financial incongruities in Bangladesh. The proposed model supported the structural equation model (SEM) and used SPSS Amos (Version 24) to build an attitudinal and behavioral model that reflects the complex relationships segment of this paper. Results show people try to rationalize irrational, unethical, and impertinent things and issues to achieve self-gain. Furthermore, corporations are treated as an entity for which they cannot be punished. Apart from this, human natures like greediness, dissatisfaction with what people have, societal status, possession and position, competition with peer groups for luxury, and tendency to imitate bad things are also responsible for bank scams in the Bangladeshi economy. Last but not least bad loan and default culture developed in the banking industry of Bangladesh only lacks execution laws, rules, and regulations.
Commercial banks in Kenya operate in quite dynamic financial market environment and continue to experience stiff competition in the provision of financial services. The liberation of the financial markets has resulted into an upsurge in the number of institutions providing financial products and services, threatening the future of Kenyan commercial banks. This study aimed at determining the effect of strategic alliances on competitive advantage of commercial banks in Kenya. The objectives were to determine effect of joint ventures, equity alliances, and joint research and development on the competitiveness of Kenyan banks. The following theories informed this research; Resource Based View theory, competitive theory, and resource dependence theory. Causal research design was adopted where all the 42 Kenyan commercial banks formed the target population. Census survey sampling design was applied and semi-structured questionnaire used. Reliability and validity results were used to improve the research instrument prior to the actual data collection. Data was analyzed using descriptive and inferential statistics. Study found that joint venture (?=0.435, p=0.000) equity alliances (?=0.227, p=0.018), and joint research and development (?=0.0.612, p=0.000) had positive significant effects on competitive advantage. With a coefficient of determination (R-square) of 68.9% and overall p-value of 0.000, the study concluded strategic alliances have a statistical significant effect on competitive advantage. The study recommends that managements of commercial banks should fast-truck implementation of such alliances to for improved competitiveness.
The main goal of this study is to evaluate customer perceptions of the competitiveness of Absa Bank in South Africa. To achieve this objective, the study is divided into two sections, which were designed as the main research questions. The first question aimed to determine customer perceptions of the level of bank competition in South Africa, while the second question focused on customer perceptions of Absa's competitiveness within the South African banking sector. It was revealed through an Absa Bank communication that Barclays Bank (UK), the major shareholder, was withdrawing from Barclays Africa Group aka Absa Bank due to ongoing uncertainties in the African market. This departure has resulted in mixed reactions from the market, with customers expressing skepticism about the potential impact on the bank's performance. The study was conducted at the Durban Central branch, which serves approximately 150,000 customers. A sample of 400 walk-in customers at the branch was selected using a non-probability convenience sampling technique. Out of the 400 questionnaires distributed, 13 were discarded due to incomplete responses. This resulted in 387 questionnaires being returned. The collected data was analysed using the latest computerized Statistical Package for Social Sciences (SPSS) version 24.0. The findings of the study indicate that competition does exist within the banking sector, with banks employing pricing strategies to compete for customers. Most customers perceive Absa Bank as being competitive in the market. As a recommendation, it is suggested that branch management regularly conduct customer surveys to engage customers and identify areas for improvement that can be incorporated into the branch operations.
Bank Indonesia Regulation No.13/1/PBI/2011 requires banks to regularly conduct a self-assessment using the RBBR (Risk-based Bank Rating) risk approach at the individual and consolidated levels. This health assessment is called RGEC (Risk Profile, Good Corporate Governance, Earnings, and Capital). This research aims to determine the effect of bank soundness with Risk Profile, Good Corporate Governance, Earning and Capital on Firm Value at Conventional Banks listed on the Indonesian Stock Exchange for the period 2019 to 2021. The sampling technique used in this study is purposive sampling. The sample criteria are conventional banking companies registered and publish complete annual financial statements that do not merge during 2019–2021. This study used 40 samples based on predetermined criteria. Analysis of the data in this study using Microsoft Excel 2019 and hypothesis testing using panel data regression analysis with the EViews version 12.0 program with a significance level of 5%. The results of this study are (1) Risk Profile using Non-Performing Loan does not affect firm value, (2) Good Corporate Governance has a positive effect on firm value, (3) Earning using Return on Assets has no effect on firm value, (4) Capital using Capital Adequacy Ratio has a positive effect on firm value. The implications of this research for banks are to increase company value; conventional banks can pay attention to the Risk Profile, Good Corporate Governance, Earnings, and Capital (RGEC) to improve their performance and for investors to be a reflection of good information to invest. The limitations of this study are that some banking companies do not publish complete financial statements, and research variables, namely profile risk and earning, do not support the theory, so they require further research.
The primary purpose of this research study is to reflect on financial anomalies, especially bank scams in Bangladesh. This study is an empirical approach developed through a well-structured Likert-scaled questionnaire to indicate different human behaviors, psychologies, and emotions that considerably impact financial incongruities in Bangladesh. The proposed model supported the structural equation model (SEM) and used SPSS Amos (Version 24) to build an attitudinal and behavioral model that reflects the complex relationships segment of this paper. Results show people try to rationalize irrational, unethical, and impertinent things and issues to achieve self-gain. Furthermore, corporations are treated as an entity for which they cannot be punished. Apart from this, human natures like greediness, dissatisfaction with what people have, societal status, possession and position, competition with peer groups for luxury, and tendency to imitate bad things are also responsible for bank scams in the Bangladeshi economy. Last but not least bad loan and default culture developed in the banking industry of Bangladesh only lacks execution laws, rules, and regulations.
Previous studies analyzing the relationship between the performance of rural banks and the COVID-19 pandemic are very limited in number. This study aims to find out how the impact of the COVID-19 pandemic on the performance of rural banks in Indonesia. This study uses panel regression data to examine the effect of the COVID-19 pandemic on the capital adequacy ratio (CAR) from the capital aspect, non-performing loan (NPL) from the asset quality aspect, return on assets (ROA) from the earning aspect, and cash ratio (CR) from the aspect of liquidity. Our findings explain that the COVID-19 pandemic has a positive effect on CAR and NPL, a negative effect on ROA, and no effect on CR.
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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |