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.
Top 5 in the selected collection · Ranked by Crossref lifetime citations. Only articles with at least one known citation are included; source totals are never combined.
2019 · Nexhat Kryeziu · Esat Ali Durguti
2019 · Muhammad Waqas · Nudrat Fatima · Aryan Khan
2019 · Evans machero Ochego · Job Omagwa · Stephen Muathe
2019 · Wesal M. Aldarabseh
2019 · Filiz Mızrak · Serhat Yüksel
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: 35 / 35 publications (100.0%). 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 01:09 UTC — 28 Oct 2026 21:42 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.
29 / 35 with data · 6 missing or unmatched. Percentages use all 35 selected publications.
29 / 35 with data · 6 missing or unmatched. Percentages use all 35 selected publications.
35 / 35 with data · 0 missing or unmatched. Percentages use all 35 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 | 35 | 35 | 35/35 | 35/35 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 96 | 35 | 35/35 | 35/35 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 180 | 35 | 35/35 | 35/35 |
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 35 / 35 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): 2026-10-22T01:09:05.441476+00:00 — 2026-10-28T21:42:07.217887+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 | 35 | 35/35 |
| 2018 | All selected publications | 2 | 35 | 35/35 |
| 2019 | All selected publications | 7 | 35 | 35/35 |
| 2020 | All selected publications | 21 | 35 | 35/35 |
| 2021 | All selected publications | 28 | 35 | 35/35 |
| 2022 | All selected publications | 36 | 35 | 35/35 |
| 2023 | All selected publications | 33 | 35 | 35/35 |
| 2024 | All selected publications | 28 | 35 | 35/35 |
| 2025 | All selected publications | 18 | 35 | 35/35 |
| 2026 | All selected publications | 6 | 35 | 35/35 |
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 ↗
Records with full publication dates only. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2019-02 | 4 |
| 2019-05 | 5 |
| 2019-07 | 11 |
| 2019-08 | 7 |
| 2019-09 | 6 |
| 2019-10 | 1 |
| 2019-12 | 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 Finance & Banking Studies SSBFNET | 35 | 96 | 180 | 35/35 | 2.74 | 1 | 62.9 | 35/35 · 100.0% |
* Percentage among publications with a known citation count.
The main purpose of this study is to investigate inflation rate and its impact on the growth rate or to GDP growth for Eurozone countries, using panel data for the period 1997-2017, on an annual basis with a total of 257 observations. For conducting the study, and achieving results, a multiple linear regression model with the least squares regression is used. Moreover, multiple linear regression analysis has been applied in order to investigate whether Inflation rate, as an independent variable, has any significant impact on economic growth. Consequently, in order to test the data used in the model we have applied diagnostic tests, such as Durbin-Watson test to analyze the correlation of serial correlation, as well as the Breusch-Pagan test for heteroskedasticity. The tests’ results give us strong indications that the model has no relation between of serial correlation and there is no heteroskedasticity either. The study conducted shows results generated from the model, and according to the econometric results indicate that Inflation rate has positive impact on the economic growth rate for euro area.
The aim of the empirical study is to investigate credit risk determinants in banking sectors across three kinds of South Asian economies. An accumulated sample of 105 unbalanced panel data of financial firms over the period of 2000-2015, by applying General Method of Moment (GMM) estimation techniques one-step at the difference in order to identify factors influencing credit risk. This study is inspired by two broad categories of explanatory variables which are bank-specific and macroeconomic. Bank-specific factors influencing unsystematic risk, while macroeconomic factors promoting systematic risk. The study uses a proxy of non-performing loans for credit risk in banking sectors of Pakistan, India, and Bangladesh. The empirical results have been found aligned with theoretical arguments and literature as expected. In comparison, NPLs in Pakistan is greater than India and Bangladesh, while India has the lowest ratio of non-performing loans. The study documents that bank-specific factors (inefficiency, profitability, capital ratio and leverage) have a significant contribution towards credit risk. Further, the study also finds a significant impact of macroeconomic variables on non-performing loans. While, the result in the case of Bangladesh predicts contradictions that have no significant effect on non-performing loans at various levels. The overall results indicate that credit risk is not influenced by only external factors but also affect by internal factors like bad management and skimping etc.
Firm value is dependent on corporate which leads to increased value. High valued firms attract more investors. Towards firm value protection, minimum capital requirements were raised by the Central Bank of Kenya from 250 million to 1 billion shillings on commercial banks to cushion bank shareholders value. Despite the increased oversight and regulatory efforts on corporate governance to protect and enhance firm value, some commercial banks have recorded low firm value. Hence, this study sought to investigate the mediating effect of financial performance on the relationship between corporate governance and firm value of commercial banks in Kenya. The study was anchored on Agency Theory. Explanatory research design was adopted. Target population was forty four Kenyan commercial banks, where a census was conducted. Secondary data was collected from published financial statements and bank websites for the period 2009 to 2018. STATA version 13.0 was used for data analysis. Descriptive and inferential statistics specifically panel regression was used in data analysis. The study findings established that there is a statistically significant effect between financial performance and firm value of commercial banks in Kenya. Therefore, the study concluded that firms with good financial performance have high firm value. And as such, these calls for the management of the commercial banks improve financial performance which will go a long way in improving firm value. There is also need for Central bank of Kenya, Capital Markets Authority and Nairobi Securities Exchange to emphasis on corporate governance and short term goals to enable achievement of long term goals .
Islamic finance is a growing industry with global distribution in all continents including Europe and America. The aim of the current study was to examine how popular is Islamic finance in the USA during the period 2014-2019 using Google Trends. In addition, the interest in Islamic finance across different US states was also investigated. Using “Islamic finance” and “Islamic bank” as search terms in Goggle Trends, the trend curve showed decreases in search volumes, suggesting a decline in the popularity of Islamic finance in the USA with years. Search volumes were detected in seven out of 50 states, suggesting low interest in Islamic finance in the majority of US states. The order of the popularity in the seven states was: Virginia > New York > New Jersey > Illinois > Texas > California > Pennsylvania > Georgia > Florida > Massachusetts. Longitudinal survey studies are needed to confirm the present findings.
The purpose of this study is to determine major indicators of the Greek crisis that started in 2009 and the effects of which can still be observed. In this regard, 8 independent variables were applied so as to fulfill the objective. Besides, the annual data between the years 1984 and 2016 was analyzed with Probit model. As a consequence of this study, it was concluded that inflation and gross savings are the leading meters of Greek crisis based on probit method. On the other hand, according to the MARS results, 3 different variables are identified as the indicators of the debt crisis in Greece. It is concluded that there is a negative relation between financial crisis with saving ratio and current account balance. Additionally, it is also identified that high unemployment ratio leads to financial crisis. While comparisng the results of these two approaches, it is concluded that MARS is much more successful than the probit method to predict the debt crisis in Greece. It is strongly recommended that saving ratio should be increased in Greece. For this purpose, governments should take some actions in order to increase this ratio more than 15.5%. Within this framework, media channels can be used by the government to tell the people about the importance of the savings to have sustainable economic development.
Firm value is dependent on corporate which leads to increased value. High valued firms attract more investors. Towards firm value protection, minimum capital requirements were raised by the Central Bank of Kenya from 250 million to 1 billion shillings on commercial banks to cushion bank shareholders value. Despite the increased oversight and regulatory efforts on corporate governance to protect and enhance firm value, some commercial banks have recorded low firm value. Hence, this study sought to investigate the mediating effect of financial performance on the relationship between corporate governance and firm value of commercial banks in Kenya. The study was anchored on Agency Theory. Explanatory research design was adopted. Target population was forty four Kenyan commercial banks, where a census was conducted. Secondary data was collected from published financial statements and bank websites for the period 2009 to 2018. STATA version 13.0 was used for data analysis. Descriptive and inferential statistics specifically panel regression was used in data analysis. The study findings established that there is a statistically significant effect between financial performance and firm value of commercial banks in Kenya. Therefore, the study concluded that firms with good financial performance have high firm value. And as such, these calls for the management of the commercial banks improve financial performance which will go a long way in improving firm value. There is also need for Central bank of Kenya, Capital Markets Authority and Nairobi Securities Exchange to emphasis on corporate governance and short term goals to enable achievement of long term goals .
The object of this study is to explore the effect of cultural distance on both the long run and short run performance of cross border mergers and acquisitions undertaken by Indian acquiring firms. We utilize buy and hold returns (BHAR), cumulative abnormal returns (CAR) and cross-sectional regression analysis in our study. Adopting the traditional Hofstede measure of cultural distance and other pertinent variables, commonly used to measure cultural differences, we document a negative and statistically significant influence of cultural distance on Indian cross-border M&As and corroborate some of other findings reported in prior research. Also, we find that the BHAR is nevertheless higher when the acquisitions are friendly, paid for 100% cash, and the acquiring firm is large, older and belongs to a business group. The inclusion of the variable ‘business group’ along with industry relatedness and acquirer size provides valuable insights into the Indian cross border acquisition landscape, wherein business groups dominate to a great extent.
The main aim of this study was to empirically assess the main microeconomic factors that affect a bank's performance. The objectives were to ascertain if there is a relationship between the performance variables with the microeconomic variables, determine those that are significant and their impact on the performance of banks in Zimbabwe. An econometric model was built from balanced panel data and the Arellano-Bond estimation procedure was employed. The empirical analysis was carried out on a sample of 17 banks that were operational in the years 2010 to 2017 in Zimbabwe. Return on Assets (ROA), Return on Equity (ROE) and Net Interest Margin (NIM) were used as the performance indicators in the analysis. The results indicate the main microeconomic factors to be those attributed to growth, credit risk, capitalisation, managerial efficiency, liquidity and diversification in the Zimbabwean financial institutions. Performance in these institutions is generally good as measured by positive persistent profits, that is, ROA, ROE and NIM. These returns reflect the extent to which these institutions are resilient to the economic crisis.
Purpose: Using panel data approach in Pakistani banking sector for 7 year time period from 2010 to 2016, the aim behind this study was to examine the bank specific, industry specific and macroeconomic determinants of bank profitability Research Design: Quantitative research design has been employed with OLS, random effect model and fixed effect model, moreover regression and correlation analysis has been used in this study Findings: Rise in NPLs ratio, Loan loss provision, inflation and exchange rate reduces the profitability of banks while increase in market power, bank size, capital adequacy enhance the profitability Practical Implication: The deleterious impact of different indicators on profitability of banks shows that distressed banking sector can cause hindrance in not only growth of financial sector but can also cause the poor growth of economy. Outcomes of the study emphasis on the need of clear-out of NPLs to keep financial sector sound as NPLs cause high loan loss provision which effect the capitalization of banks that ultimately effect the economic growth of financial as well as other sectors of economy. Banking supervisory agencies should pay attention towards banking monitory policies and banks macroeconomic policies Originality/value: This study examine the impact of all three types of indicator (Bank specific, industry specific and macroeconomic) on banks profitability by employing latest data from 2010 to 2016 in which major reforms were held in banking industry of Pakistan because there exist rare studies with all three types of variables with latest figures
The contemporary economy has changed dramatically and moved from the industrial age to the information age, pushing businesses to embark into a predominantly intangible economy. Thus, and in addition to solid and liquid value, there is a gaseous value which is the intangible capital. This exploratory study of 14 Lebanese companies analyzed with the “Tropes” software focuses on the constituent elements of intangible capital, its place within these companies and its contribution to the creation of value. This work concludes a first proposal for the classification of the components of intangible capital.
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 |