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: 2 / 2 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 01:22 UTC — 22 Oct 2026 01:31 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 / 2 with data · 1 missing or unmatched. Percentages use all 2 selected publications.
1 / 2 with data · 1 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 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 | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 8 | 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 2 / 2 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): 2026-10-22T01:22:28.573024+00:00 — 2026-10-22T01:31:57.823324+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 | 2 | 2/2 |
| 2018 | All selected publications | 0 | 2 | 2/2 |
| 2019 | All selected publications | 0 | 2 | 2/2 |
| 2020 | All selected publications | 0 | 2 | 2/2 |
| 2021 | All selected publications | 0 | 2 | 2/2 |
| 2022 | All selected publications | 1 | 2 | 2/2 |
| 2023 | All selected publications | 4 | 2 | 2/2 |
| 2024 | All selected publications | 2 | 2 | 2/2 |
| 2025 | All selected publications | 1 | 2 | 2/2 |
| 2026 | All selected publications | 0 | 2 | 2/2 |
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 |
|---|---|
| 2021 | 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 | 2 | 3 | 8 | 2/2 | 1.5 | 1.5 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to examine the problem of the effect of e-brand experience on e-brand loyalty that mediated by e-brand love and e-brand trust (a study of go-pay users in the Go-Jek application in Malang). This research used one independent variable that is e-brand experience, the variable e-brand trust and e-brand love as a mediating variable, and the variable e-brand loyalty as the dependent variable. This research uses non-probability purposive sampling. The population in this research was all Go-Pay users in the Go-Jek application in Malang City. The sample is 130 respondents based on the specified criteria. Analysis of research data using SEM PLS. Based on the analysis conducted in this research show that e-brand experience did not have a significant effect on e-brand loyalty directly, whereas if it mediated by e-brand trust and e-brand love so the relationship between e-brand experience and e-brand loyalty becomes significant.
The paper determines the black consumers’ perceptions towards luxury brands in South Africa. The purchase of luxury brands has been on the rise locally and internationally. Global brands have been investing in SA by expanding to the region. The demand for luxury brands has also increased over the past decades. In SA, the middle-class group has also increased, particularly the black middle class which increased the market for luxury brands. To achieve the objectives of the study, a survey was conducted among black consumers in Thohoyandou, Venda, South Africa. Data were collected by two fieldworkers who intercepted shoppers visiting a regional mall in the area. Data were analyzed using SPSS 25. The descriptives, factor analysis, and ANOVA were analyzed to achieve the objectives of the study. The findings of the study reveal that black consumers are more influenced by the rarity and uniqueness of the brands followed by the financial and functional values of the brands. Black consumers’ perceptions towards luxury brands were found to differ across age and income groups but did not differ across gender and education levels. Organizations targeting black consumers must design brands that are rare and unique and ensure that brands deliver the financial and functional values desired by black consumers
The paper determines the black consumers’ perceptions towards luxury brands in South Africa. The purchase of luxury brands has been on the rise locally and internationally. Global brands have been investing in SA by expanding to the region. The demand for luxury brands has also increased over the past decades. In SA, the middle-class group has also increased, particularly the black middle class which increased the market for luxury brands. To achieve the objectives of the study, a survey was conducted among black consumers in Thohoyandou, Venda, South Africa. Data were collected by two fieldworkers who intercepted shoppers visiting a regional mall in the area. Data were analyzed using SPSS 25. The descriptives, factor analysis, and ANOVA were analyzed to achieve the objectives of the study. The findings of the study reveal that black consumers are more influenced by the rarity and uniqueness of the brands followed by the financial and functional values of the brands. Black consumers’ perceptions towards luxury brands were found to differ across age and income groups but did not differ across gender and education levels. Organizations targeting black consumers must design brands that are rare and unique and ensure that brands deliver the financial and functional values desired by black consumers
This study aims to examine the problem of the effect of e-brand experience on e-brand loyalty that mediated by e-brand love and e-brand trust (a study of go-pay users in the Go-Jek application in Malang). This research used one independent variable that is e-brand experience, the variable e-brand trust and e-brand love as a mediating variable, and the variable e-brand loyalty as the dependent variable. This research uses non-probability purposive sampling. The population in this research was all Go-Pay users in the Go-Jek application in Malang City. The sample is 130 respondents based on the specified criteria. Analysis of research data using SEM PLS. Based on the analysis conducted in this research show that e-brand experience did not have a significant effect on e-brand loyalty directly, whereas if it mediated by e-brand trust and e-brand love so the relationship between e-brand experience and e-brand loyalty becomes significant.
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 |