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: 1 / 1 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 01:44 UTC — 22 Oct 2026 01:44 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.
1 / 1 with data · 0 missing or unmatched. Percentages use all 1 selected publications.
1 / 1 with data · 0 missing or unmatched. Percentages use all 1 selected publications.
1 / 1 with data · 0 missing or unmatched. Percentages use all 1 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 |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 7 | 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 1 / 1 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): 2026-10-22T01:44:38.673323+00:00 — 2026-10-22T01:44:38.673323+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 | 1 | 1/1 |
| 2018 | All selected publications | 0 | 1 | 1/1 |
| 2019 | All selected publications | 0 | 1 | 1/1 |
| 2020 | All selected publications | 0 | 1 | 1/1 |
| 2021 | All selected publications | 0 | 1 | 1/1 |
| 2022 | All selected publications | 0 | 1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 |
| 2024 | All selected publications | 4 | 1 | 1/1 |
| 2025 | All selected publications | 1 | 1 | 1/1 |
| 2026 | All selected publications | 1 | 1 | 1/1 |
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 |
|---|---|
| 2023 | 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 | 6 | 7 | 1/1 | 6.0 | 6 | 100.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
E-commerce is gaining popularity due to its importance for both merchants and consumers, particularly in light of the COVID-19 pandemic, which restricts mass movement and gathering, as well as the high costs associated with traveling to different markets. Despite mounting evidence demonstrating the importance of internet in retails business, little is known about the potential mechanisms that increase consumer purchasing intentions when using online shopping platforms. In today's high customer sensitivity to service quality, successful entrepreneurs have recently thrived under competitive pressures. Online transactions are more difficult because buyers and sellers do not know each other, yet they must provide financial information to intermediaries. Thus, it is now clear that increasing customer trust is a viable strategy for driving e-business success today. Considering this, a new model demonstrating a potential mechanism that increases customers' trust in intermediaries and thus leads to their online purchasing intentions was developed. This innovative model connects website quality to the online purchasing intentions of the customers, using trust in intermediaries as a mediator and moderating the effect of perceived usefulness. To prove or disprove the assumptions highlighted in this study, a cross-sectional research design was used with data from 568 clients of nine domestic e-commerce platforms operating in Rwanda. To investigate the relationship between the variables hypothesized in this study, a variety of methods and tools were used. To assess the potential effect of each variable in this model, we used CFA in SEM-Amos, mean and standard deviation in SPSS, and Hayes macro process. The overall results obtained using the various techniques specified supported the current hypothesized model. We believe that the current study provided an innovative and useful mechanism as one of the potential solutions for today's merging online businesses.
E-commerce is gaining popularity due to its importance for both merchants and consumers, particularly in light of the COVID-19 pandemic, which restricts mass movement and gathering, as well as the high costs associated with traveling to different markets. Despite mounting evidence demonstrating the importance of internet in retails business, little is known about the potential mechanisms that increase consumer purchasing intentions when using online shopping platforms. In today's high customer sensitivity to service quality, successful entrepreneurs have recently thrived under competitive pressures. Online transactions are more difficult because buyers and sellers do not know each other, yet they must provide financial information to intermediaries. Thus, it is now clear that increasing customer trust is a viable strategy for driving e-business success today. Considering this, a new model demonstrating a potential mechanism that increases customers' trust in intermediaries and thus leads to their online purchasing intentions was developed. This innovative model connects website quality to the online purchasing intentions of the customers, using trust in intermediaries as a mediator and moderating the effect of perceived usefulness. To prove or disprove the assumptions highlighted in this study, a cross-sectional research design was used with data from 568 clients of nine domestic e-commerce platforms operating in Rwanda. To investigate the relationship between the variables hypothesized in this study, a variety of methods and tools were used. To assess the potential effect of each variable in this model, we used CFA in SEM-Amos, mean and standard deviation in SPSS, and Hayes macro process. The overall results obtained using the various techniques specified supported the current hypothesized model. We believe that the current study provided an innovative and useful mechanism as one of the potential solutions for today's merging online businesses.
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 |