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: 4 / 4 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 11:30 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 22 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 31 | 4 | 4/4 | 4/4 |
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 4 / 4 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): 2026-10-22T01:23:21.345920+00:00 — 2026-10-23T11:30:10.418771+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 3 | 4 | 4/4 |
| 2022 | All selected publications | 2 | 4 | 4/4 |
| 2023 | All selected publications | 13 | 4 | 4/4 |
| 2024 | All selected publications | 5 | 4 | 4/4 |
| 2025 | All selected publications | 8 | 4 | 4/4 |
| 2026 | All selected publications | 0 | 4 | 4/4 |
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 |
|---|---|
| 2021-01 | 1 |
| 2021-02 | 1 |
| 2021-05 | 1 |
| 2021-06 | 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 | 1 | 1 | 4 | 1/1 | 1.0 | 1 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 21 | 27 | 3/3 | 7.0 | 4 | 100.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
In this paper, we investigate the definition of Fintech and measure the extent of the impact of Fintech variables on the Cybersecurity as the dependent variable. The hypotheses developed by the authors which are based on research through the statistical results of the research variables and as all correlation coefficients were a positive relationship and at the level of significance 0.01 which made the authors accept the correlation hypotheses, and for the results of the influence factor between the research variables it also had a positive effect when the level of 0.05 for all sections of the independent variable, as we have also noticed that the influence of the independent variable of financial technology when linked to all of its sections with Cybersecurity. We find the influence of the influence coefficient significantly increased to 0.908, which explains that there is a complementarity between the sections of the independent variable.
Online education has been introduced as a tool in the learning process in the majority of international universities worldwide. The term “e-learning” is defined as “any learning that involves using the internet or intranet. In this research, we tried the check the impact of online learning upon the students of Lebanese French University Erbil, Kurdistan region Iraq. The Objectives of the study are multi-folded. Firstly, to evaluate the influence of online learning upon the performance of students and secondly, to test the motivation of online learning towards the students. For this purpose, a detailed questionnaire was developed in order to get the response of the students. The questionnaire was built up and distributed to almost eighty respondents in which we got back a perfect response in complete shape only fifty. Graph analysis has been used in order to present the response of the respondent. Mix response was recorded in which slightly negative response was in high portion. Furthermore, results showed that 60 % of respondents answered they are not happy with the online learning process and they want to have a traditional learning process that is on campus. Similarly, in each question, an extraordinary negative response toward online learning is recorded such as 76 % respondents said that they are not satisfied with this implementation of online learning. Also, they are facing hurdles and 58 % of people showed their response one of the big challenges toward online learning is a poor internet connection. 60% claimed that the instructor is not helping them to understand this whole process as a tool of online learning. The possible reason that was claimed from respondents are following: (i)This online process is first time they are interacting with,(ii) Lack of training of such online tools for the online learning process, (iii) once any student is facing trouble while this online process less support is available from the department and technical staff of the university
This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.
The purpose of this article to identify the hidden economy and money laundering operations and expose the backgrounds, social and banking them, and clarify the relationship between them. Also clarifying the position of the banking system from money laundering practices through the procedures followed, Furthermore to address the size of this issue and the methods used in laundering the money, since money laundering is a phenomena that all world states suffer from because of its negative impacts on social, economic and political aspects in any state. The spread of such phenomena can be attributed to various reasons that may be subjective of procedural, among them the fail of national legislation or the absence of cooperation between the concerned. Due to the impact of such phenomena international, regional and local efforts were exerted to fight this phenomena through international agreements, Purpose to achieve the objectives of the research has been formulated a main hypothesis as follows: The procedures followed and the laws in force in the field of money laundering are still limited to reviewing this phenomenon and besieging and addressing it. The study will employ the analytical method to test its hypotheses. It will be divided into three chapters in its theoretical and practical aspects, money laundering operations and ways of confronting them through the banking system. The first chapter deals with the theoretical framework of the study, which includes three subjects. Money laundering, the second chapter includes the role of the banking system in the face of money laundering, and the third was devoted to presenting the practical side of the role of the banking system in the face of money laundering. The practical side has collected the required liabilities from within the banking system in the province. Finally, conclusions and proposals for the study were reached. It concoded to us Money laundering is an integral part of the hidden economy and appears in the illegal part of it, as it hides the sources of illicit funds and turns them into legitimate sources. And the hidden economy, and without these operations, money would not be able to return to the apparent economy.
The purpose of this article to identify the hidden economy and money laundering operations and expose the backgrounds, social and banking them, and clarify the relationship between them. Also clarifying the position of the banking system from money laundering practices through the procedures followed, Furthermore to address the size of this issue and the methods used in laundering the money, since money laundering is a phenomena that all world states suffer from because of its negative impacts on social, economic and political aspects in any state. The spread of such phenomena can be attributed to various reasons that may be subjective of procedural, among them the fail of national legislation or the absence of cooperation between the concerned. Due to the impact of such phenomena international, regional and local efforts were exerted to fight this phenomena through international agreements, Purpose to achieve the objectives of the research has been formulated a main hypothesis as follows: The procedures followed and the laws in force in the field of money laundering are still limited to reviewing this phenomenon and besieging and addressing it. The study will employ the analytical method to test its hypotheses. It will be divided into three chapters in its theoretical and practical aspects, money laundering operations and ways of confronting them through the banking system. The first chapter deals with the theoretical framework of the study, which includes three subjects. Money laundering, the second chapter includes the role of the banking system in the face of money laundering, and the third was devoted to presenting the practical side of the role of the banking system in the face of money laundering. The practical side has collected the required liabilities from within the banking system in the province. Finally, conclusions and proposals for the study were reached. It concoded to us Money laundering is an integral part of the hidden economy and appears in the illegal part of it, as it hides the sources of illicit funds and turns them into legitimate sources. And the hidden economy, and without these operations, money would not be able to return to the apparent economy.
Online education has been introduced as a tool in the learning process in the majority of international universities worldwide. The term “e-learning” is defined as “any learning that involves using the internet or intranet. In this research, we tried the check the impact of online learning upon the students of Lebanese French University Erbil, Kurdistan region Iraq. The Objectives of the study are multi-folded. Firstly, to evaluate the influence of online learning upon the performance of students and secondly, to test the motivation of online learning towards the students. For this purpose, a detailed questionnaire was developed in order to get the response of the students. The questionnaire was built up and distributed to almost eighty respondents in which we got back a perfect response in complete shape only fifty. Graph analysis has been used in order to present the response of the respondent. Mix response was recorded in which slightly negative response was in high portion. Furthermore, results showed that 60 % of respondents answered they are not happy with the online learning process and they want to have a traditional learning process that is on campus. Similarly, in each question, an extraordinary negative response toward online learning is recorded such as 76 % respondents said that they are not satisfied with this implementation of online learning. Also, they are facing hurdles and 58 % of people showed their response one of the big challenges toward online learning is a poor internet connection. 60% claimed that the instructor is not helping them to understand this whole process as a tool of online learning. The possible reason that was claimed from respondents are following: (i)This online process is first time they are interacting with,(ii) Lack of training of such online tools for the online learning process, (iii) once any student is facing trouble while this online process less support is available from the department and technical staff of the university
This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.
In this paper, we investigate the definition of Fintech and measure the extent of the impact of Fintech variables on the Cybersecurity as the dependent variable. The hypotheses developed by the authors which are based on research through the statistical results of the research variables and as all correlation coefficients were a positive relationship and at the level of significance 0.01 which made the authors accept the correlation hypotheses, and for the results of the influence factor between the research variables it also had a positive effect when the level of 0.05 for all sections of the independent variable, as we have also noticed that the influence of the independent variable of financial technology when linked to all of its sections with Cybersecurity. We find the influence of the influence coefficient significantly increased to 0.908, which explains that there is a complementarity between the sections of the independent variable.
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 |