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: 476 / 476 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: 21 Oct 2026 00:21 UTC — 22 Oct 2026 10:53 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.
360 / 476 with data · 116 missing or unmatched. Percentages use all 476 selected publications.
360 / 476 with data · 116 missing or unmatched. Percentages use all 476 selected publications.
472 / 476 with data · 4 missing or unmatched. Percentages use all 476 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 | 6 | 6 | 6/6 | 6/6 |
| 2013 | All selected publications | 29 | 29 | 29/29 | 29/29 |
| 2014 | All selected publications | 26 | 26 | 26/26 | 26/26 |
| 2015 | All selected publications | 15 | 15 | 15/15 | 15/15 |
| 2016 | All selected publications | 72 | 72 | 72/72 | 72/72 |
| 2017 | All selected publications | 20 | 20 | 20/20 | 20/20 |
| 2018 | All selected publications | 20 | 20 | 20/20 | 16/20 |
| 2019 | All selected publications | 35 | 35 | 35/35 | 35/35 |
| 2020 | All selected publications | 41 | 41 | 41/41 | 41/41 |
| 2021 | All selected publications | 44 | 44 | 44/44 | 44/44 |
| 2022 | All selected publications | 41 | 41 | 41/41 | 41/41 |
| 2023 | All selected publications | 33 | 33 | 33/33 | 33/33 |
| 2024 | All selected publications | 32 | 32 | 32/32 | 32/32 |
| 2025 | All selected publications | 62 | 62 | 62/62 | 62/62 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 25 | 6 | 6/6 | 6/6 |
| 2013 | All selected publications | 56 | 29 | 29/29 | 29/29 |
| 2014 | All selected publications | 53 | 26 | 26/26 | 26/26 |
| 2015 | All selected publications | 55 | 15 | 15/15 | 15/15 |
| 2016 | All selected publications | 100 | 72 | 72/72 | 72/72 |
| 2017 | All selected publications | 86 | 20 | 20/20 | 20/20 |
| 2018 | All selected publications | 26 | 20 | 20/20 | 16/20 |
| 2019 | All selected publications | 96 | 35 | 35/35 | 35/35 |
| 2020 | All selected publications | 169 | 41 | 41/41 | 41/41 |
| 2021 | All selected publications | 82 | 44 | 44/44 | 44/44 |
| 2022 | All selected publications | 52 | 41 | 41/41 | 41/41 |
| 2023 | All selected publications | 62 | 33 | 33/33 | 33/33 |
| 2024 | All selected publications | 44 | 32 | 32/32 | 32/32 |
| 2025 | All selected publications | 31 | 62 | 62/62 | 62/62 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 62 | 6 | 6/6 | 6/6 |
| 2013 | All selected publications | 139 | 29 | 29/29 | 29/29 |
| 2014 | All selected publications | 109 | 26 | 26/26 | 26/26 |
| 2015 | All selected publications | 167 | 15 | 15/15 | 15/15 |
| 2016 | All selected publications | 330 | 72 | 72/72 | 72/72 |
| 2017 | All selected publications | 206 | 20 | 20/20 | 20/20 |
| 2018 | All selected publications | 58 | 20 | 20/20 | 16/20 |
| 2019 | All selected publications | 180 | 35 | 35/35 | 35/35 |
| 2020 | All selected publications | 348 | 41 | 41/41 | 41/41 |
| 2021 | All selected publications | 193 | 44 | 44/44 | 44/44 |
| 2022 | All selected publications | 111 | 41 | 41/41 | 41/41 |
| 2023 | All selected publications | 84 | 33 | 33/33 | 33/33 |
| 2024 | All selected publications | 49 | 32 | 32/32 | 32/32 |
| 2025 | All selected publications | 32 | 62 | 62/62 | 62/62 |
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 472 / 476 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): 2026-10-21T00:21:59.435320+00:00 — 2026-10-22T10:53:58.577106+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 | 56 | 476 | 472/476 |
| 2018 | All selected publications | 89 | 476 | 472/476 |
| 2019 | All selected publications | 121 | 476 | 472/476 |
| 2020 | All selected publications | 155 | 476 | 472/476 |
| 2021 | All selected publications | 219 | 476 | 472/476 |
| 2022 | All selected publications | 255 | 476 | 472/476 |
| 2023 | All selected publications | 343 | 476 | 472/476 |
| 2024 | All selected publications | 327 | 476 | 472/476 |
| 2025 | All selected publications | 244 | 476 | 472/476 |
| 2026 | All selected publications | 133 | 476 | 472/476 |
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 | 6 |
| 2013 | 29 |
| 2014 | 26 |
| 2015 | 15 |
| 2016 | 72 |
| 2017 | 20 |
| 2018 | 20 |
| 2019 | 35 |
| 2020 | 41 |
| 2021 | 44 |
| 2022 | 41 |
| 2023 | 33 |
| 2024 | 32 |
| 2025 | 62 |
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 | 476 | 937 | 2068 | 472/476 | 1.97 | 1.0 | 56.3 | 476/476 · 100.0% |
* Percentage among publications with a known citation count.
As an industry that has an important role for other industrial sectors, the plastic and packaging industry is the supply chain for consumer products. Behind the high industrial growth and the potential is still large, there are problems with plastic waste, consumption power, and changes in people's lifestyles that can affect the growth of the plastic and packaging industry. This study aims to determine how much impact the NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) on Profit Growth in the plastic and packaging industry sub-sector companies listed in IDX (Indonesia Stock Exchange) for the period 2014 to 2018. The method used in this study is a quantitative descriptive. The sampling technique used was purposive sampling in order to obtain a sample of 11 companies from a population of 12 companies. In the study the method of data analysis used the multiple linear regression analysis techniques by processing data using Eviews 8, because the data is not normally distributed, it uses the log transformation method. The results showed that simultaneously NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) had a significant effect on profit growth. And partially NPM (Net Profit Margin) has a significant effect on profit growth, while GPM (Gross Profit Margin) and TAT (Total Assets Turnover) have no significant effect on profit growth.
The study examines the bank-specific and macroeconomic determinants of banks profitability in Nigeria analyzing audited financial reports of selected sixteen (16) commercial banks over the period of 2010 to 2015 making up to 96 observations. The study identified that existing studies are sketchy in developing economies even though many studies have emerge in developed economies. The bank profitability is measured by return on assets and return on equity as function of bank-specific and macroeconomic determinants. Using the balanced panel data set, the empirical results of the study shows that capital adequacy and liquidity have a positive and significant effect on bank profitability. However, efficiency ratio have a negative and significant effect on bank profitability. With regards to macroeconomic variable, GDP growth also have a positive and significant impact on banks profitability. The empirical results of the study suggested that banks can improve their profitability through increasing capital and liquidity, decreasing operating cost with conscious effort to maintain transparency in their operations. In addition, a good economic environment for financial institutions foster increase in bank profitability. Hence, the study recommends that further studies can expand the scope while extending to other industries as well.
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.
This paper demonstrates the relationship between CAMELS ratios and credit ratings of deposit banks in Turkey. Annual data was used for the period between 2004 and 2014 in this study. Moreover, 20 deposit banks of Turkey were analyzed and 21 different ratios of CAMELS components were used. In addition to that, credit ratings of these banks were provided from Moody’s corporation or annual activity reports of the banks. After that, we created multi nominal logistic regression analysis in order to illustrate the relationship. The major finding in this study is that three components (Asset Quality, Management Quality, and Sensitivity to Market Risk) of CAMELS have effects on credit ratings whereas the ratios related to Capital Adequacy and Earnings are not effective. As a result, it was recommended that Turkish deposit banks should concentrate on the percentage of fixed assets and interest income to have a better rating. Moreover, having high market share with respect to total assets and lower interest expense are also other important points for this purpose. On the other hand, Turkish deposit banks should control the proportion of financial assets and increase the amount of FX liquid assets to prevent credit ratings to decrease. Additionally, market share of banks for loans should not reach at high level for this objective.
Increase in losses borne by banks as a result of inadequate operational risk management practices and the adverse impact on banks’ financial performance has been a major concern to bank management and regulators. This study analysed the impact of operational risk management practices on the financial performance of commercial banks in Nigeria. 10-years (2008 - 2017) secondary data extracted from audited financial statements of selected commercial banks in Nigeria was used for the study. The data was analysed using the Linear Multiple Regression Model. The results showed that there is a positive relationship between operational risk management and the financial performance of banks. The findings revealed that sound operational risk management practices impact positively on the financial performance of banks. We, therefore, recommend that banks’ management should deploy adequate resources towards understanding operational risk to ensure sound operational risk management and improved financial performance of banks.
The Options Based Portfolio Insurance (OBPI) should avoid losses and capture gains, by the cost of a “premium”, but in practice the premium cost can be too high to capture gains in the different market conditions. Based on this premise, the objective of this study is to analyze an optimized alternative to Options Based Portfolio Insurance, assuming that the probability of an Extreme Negative Event varies with time, and therefore the insurance floor should not be maintained at any cost. To achieve the objective, data were crossed between the rollover date and a fixed insurance cost on equity, using historical data from 678,546 trades carried out in the US market, which resulted in 3,700 portfolios. Data analysis was performed using descriptive and econometric statistics with simple linear regressions. The results demonstrated that the insured floor varied with the volatility implied in option prices, indicating the possibility of obtaining better return-risk ratio and lower drawdown when compared to the unprotected portfolio, showing a positive correlation between insurance cost and return-risk ratio for low costs and a negative correlation for higher costs. Furthermore, it can be indirectly inferred that the explanation for the results comes from the perception of risk by the market not representing the real risk. As with the stabilization and possible recovery of prices that occur after a significant drop, market confidence is not restored to the same proportion. That’s why volatility remains at high levels, consequently, raising the insurance cost, even with lower probabilities of Extreme Negative Events.
The current research aims to examine the accounting of digital assets by linking accounting measurement theory to financial disclosure requirements, in light of the challenges related to the absence of specialized international accounting standards for digital assets. The research was divided into two parts: theoretical and applied. The theoretical part included a review of the literature related to accounting measurement (historical cost, fair value, and impairment model) and financial disclosure requirements according to International Financial Reporting Standards (IAS/IFRS) and American standards (FASB, AICPA, and SEC). The applied part used a questionnaire and administered to a sample of financial report users, including academics and professionals, to obtain their opinions on the adequacy of current measurement models, financial disclosure requirements, and shortcomings in international standards. It also explored the possibility of formulating an integrated framework for measuring and disclosing digital assets. The results of the analysis of the questionnaire showed that fair value measurement is more appropriate for the nature of digital assets than traditional models, with the need to enhance disclosure of risks associated with price volatility, liquidity, and operational risks. It also showed that the absence of a specific accounting standard for digital assets leads to poor comparability and increased variation in accounting practices across economic entities. Based on the survey results, an integrated theoretical framework for accounting for digital assets was proposed. This framework includes principles of recognition, measurement, and disclosure, and contributes to achieving the objectives of financial reporting in accordance with the International Accounting Standards Board (IASB) conceptual framework, ensuring relevance, accurate representation, comparability, clarity, and timeliness. The study concluded that developing a specialized accounting framework for digital assets represents a strategic necessity to ensure the reliability and transparency of financial reporting and enhance user confidence, given the rapid growth in the adoption of digital assets within global economic activities.
This study examines the prospective integration of blockchain technologies to enhance operational transparency in the Iraqi banking sector. Despite the absence of actual blockchain deployment, the research adopts a foresight-driven, empirical approach combining literature analysis with survey data from 82 banking professionals. Results from statistical tests (including ANOVA and t-tests) reveal a generally low level of institutional awareness but a strong perceived potential for transparency improvement—especially when paired with a phased implementation model. Moreover, technological infrastructure and management attitudes were found to significantly mediate the adoption process. The study concludes with practical recommendations tailored to Iraq’s institutional realities and proposes a scalable roadmap for gradual blockchain adoption. These insights contribute to bridging the gap between technological potential and institutional readiness in developing economies.
This research aims to demonstrate the role of financial statements (balance sheet) in reporting the risks faced by government units and the extent of the risks within these units, in addition to demonstrating the steps through which risks can be managed in these units, whether they are governmental or private economic units. Financial risks are one of the problems facing economic units, whether private or governmental. In turn, decision-makers, both internal and external, work to measure the financial risks facing these units. Therefore, the research problem is as follows, Do financial position statement contribute to reporting financial risks in governmental units (Baghdad Municipality)? In order to achieve the research objectives, the financial position statement of the Baghdad Municipality Department (a government unit) was used, and a set of indicators was used to reach a judgment on the presence or absence of risks, as well as the level of risks facing this unit. It was found that there is a possibility of knowing the risks through the financial position statement, in addition to discovering that the level of risks facing this unit (Baghdad Municipality) is considered high.
This is a study about the financing of large group health insurance in the United States. Almost 8 in 10 covered employees in private large firms are enrolled in self-insured (or self-funded) health plans in contrast to only 20 percent of employees in small firms. More than half of all large standard (non-supplemental) health plans are self-insured although their number is decreasing. Considering their significantly greater risk of exposure and transaction costs, the question for scholarly investigation is why (and how) do private large firms self-fund employer-sponsored health insurance? Using plan-level data from health plan administrator filings of Forms 5500 and Summary Annual Reports (2014-2022) with the U.S. Department of Labor, six variables are examined in this study relative to large group self-insurance: industry/sectoral distribution, plan size/enrollment, plan administration, benefits coverage, plan assets and investments, and statutory compliance. Findings suggest that industry/sectoral and enrollee distributions of large health plans are not widely dispersed while their assets and investments and statutory exemptions offer comparative advantages. These plans have also increasingly relied on stop-loss insurance, third-party administration, supplemental health benefits, and less major medical plans to mitigate actuarial risks that involve considerable financial exposure to fluctuating claims costs, potential for catastrophic claims, and cash flow unpredictability. The intertwining theoretical and practical implications of large group self-insurance in healthcare finance and risk management are addressed by way of conclusion.
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 |