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: 21 Oct 2026 07:22 UTC — 23 Oct 2026 07:31 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.
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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 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 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): 2026-10-21T07:22:55.656755+00:00 — 2026-10-23T07:31:47.693096+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 | 0 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 0 | 4 | 4/4 |
| 2025 | All selected publications | 0 | 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 ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2013 | 1 |
| 2020 | 1 |
| 2022 | 1 |
| 2024 | 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 Research in Business and Social Science SSBFNET | 4 | 0 | 0 | 4/4 | 0.0 | 0.0 | 0.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
The Covid-19 pandemic significantly affected the global fashion industry, causing several changes that intensified competition between fashion retailers and brands, making it more challenging to establish or increase clothing brand awareness. Gender plays a crucial role in consumers’ perceptions and decision-making, highlighting the importance of understanding the role of gender in effectively establishing and increasing clothing brand awareness. The objective of the study was to determine whether differences exist in the creation of clothing brand awareness of Generation Y male and female students. This study followed a descriptive research design. A self-administered questionnaire was distributed to students for voluntary completion. A total of 625 completed questionnaires were analysed by performing frequency analysis, descriptive statistics, internal consistency reliability, correlation analysis and regression analysis. After establishing the reliability of the measurement instrument, and confirming significant statistical relationships between all the constructs, multiple linear regression analysis was performed. The findings of the regression analysis revealed that for Generation Y male students, product, store image and advertising of clothing brands significantly influence their awareness of a brand; while for Generation Y female students, the price and advertising of clothing brands significantly influence their awareness of clothing brands. This study contributes to the literature relating to gender studies and brand awareness, and provides practical recommendations for clothing brands and retailers to more effectively establish or strengthen clothing brand awareness among Generation Y male and female consumers, respectively.
The aim of this study was to determine the nexus between brand consciousness and psychological antecedents of consumer decision-making styles of Generation Y consumers in Botswana. Brand Consciousness refers to the degree to which people use brand names to make purchase decisions. The study employed quantitative and causal research. E-questionnaire was employed to collect data from 400 generation Y consumers, of which 320 were successfully selected and tested through purposeful sampling. The study results revealed that there is a positive relationship between brand consciousness and psychological antecedents of consumer decision-making styles and also the research findings indicated that millennial consumers in Botswana identify themselves as independent decision-makers that do not rely on external influence when making their purchasing decisions. The study results also indicated that most Batswana millennials are more cognitive innovators than sensory innovators. It is recommended that retailers must be encouraged to add excitement to shopping amenities to attract and retain millennial sensory innovators. Tangible evidence on future research is also required on the actual effects of modern smart e-shopping on generational transformation from Gen X, and Y to Z.
The concept of prejudice has become increasingly important to scientific thinking about relations between groups. Yet, despite extensive research, little is known about how prejudice affects consumer buying behavior, especially regarding activities that involve purchasing products and services thereby crossing to suppliers from the dominant community. The purpose of this study is twofold: to examine the influence of both positive and negative prejudices on cross-shopping intention in the context of an ethnic minority-majority group relationship; and, to investigate the moderating influence of intercultural-related factors (i.e. online contact, social interaction, and acculturation) on the relationship between negative prejudice and cross-shopping intention. A sample consisting of 202 respondents was obtained from across ethnic-minority consumers (the Israeli Arabs) who routinely interact online and offline with individuals from the majority population (Israeli Jews). The conceptual framework and hypothesis are tested using the partial least squares analyses (PLS). The study results provide a better understanding of the conflicting effects of positive and negative prejudice on cross-shopping intention. Additionally, results shed light on the moderating role of intercultural factors on the relationship between negative prejudice and cross-shopping intention. Implications are identified together with consideration of the study limitations and avenues for future research.
The study aims to examine brand management model in Iran's professional Football League (2011-2012) with emphasis on brand image. The study was descriptive-survey one. A sample of Iranian professional football league fans (N=911) responded 4 items questionnaire. A structural equation model (SEM) test with maximum likelihood estimation was performed to test the relationships among the research variables. The analyses of data showed three dimensions of brand image influenced on fan’s brand loyalty of which the attitude was the most important. Benefits and attributes were placed in the second and third rank respectively. According to Results, brand image play a pivotal role between Iranian fans brand loyalty. Create an attractive and desirable brand image in the fans mind increases brand loyalty. And due to, revenue and profits increase through ticket sales and products of club and also attract more sponsors.
The Covid-19 pandemic significantly affected the global fashion industry, causing several changes that intensified competition between fashion retailers and brands, making it more challenging to establish or increase clothing brand awareness. Gender plays a crucial role in consumers’ perceptions and decision-making, highlighting the importance of understanding the role of gender in effectively establishing and increasing clothing brand awareness. The objective of the study was to determine whether differences exist in the creation of clothing brand awareness of Generation Y male and female students. This study followed a descriptive research design. A self-administered questionnaire was distributed to students for voluntary completion. A total of 625 completed questionnaires were analysed by performing frequency analysis, descriptive statistics, internal consistency reliability, correlation analysis and regression analysis. After establishing the reliability of the measurement instrument, and confirming significant statistical relationships between all the constructs, multiple linear regression analysis was performed. The findings of the regression analysis revealed that for Generation Y male students, product, store image and advertising of clothing brands significantly influence their awareness of a brand; while for Generation Y female students, the price and advertising of clothing brands significantly influence their awareness of clothing brands. This study contributes to the literature relating to gender studies and brand awareness, and provides practical recommendations for clothing brands and retailers to more effectively establish or strengthen clothing brand awareness among Generation Y male and female consumers, respectively.
The aim of this study was to determine the nexus between brand consciousness and psychological antecedents of consumer decision-making styles of Generation Y consumers in Botswana. Brand Consciousness refers to the degree to which people use brand names to make purchase decisions. The study employed quantitative and causal research. E-questionnaire was employed to collect data from 400 generation Y consumers, of which 320 were successfully selected and tested through purposeful sampling. The study results revealed that there is a positive relationship between brand consciousness and psychological antecedents of consumer decision-making styles and also the research findings indicated that millennial consumers in Botswana identify themselves as independent decision-makers that do not rely on external influence when making their purchasing decisions. The study results also indicated that most Batswana millennials are more cognitive innovators than sensory innovators. It is recommended that retailers must be encouraged to add excitement to shopping amenities to attract and retain millennial sensory innovators. Tangible evidence on future research is also required on the actual effects of modern smart e-shopping on generational transformation from Gen X, and Y to Z.
The concept of prejudice has become increasingly important to scientific thinking about relations between groups. Yet, despite extensive research, little is known about how prejudice affects consumer buying behavior, especially regarding activities that involve purchasing products and services thereby crossing to suppliers from the dominant community. The purpose of this study is twofold: to examine the influence of both positive and negative prejudices on cross-shopping intention in the context of an ethnic minority-majority group relationship; and, to investigate the moderating influence of intercultural-related factors (i.e. online contact, social interaction, and acculturation) on the relationship between negative prejudice and cross-shopping intention. A sample consisting of 202 respondents was obtained from across ethnic-minority consumers (the Israeli Arabs) who routinely interact online and offline with individuals from the majority population (Israeli Jews). The conceptual framework and hypothesis are tested using the partial least squares analyses (PLS). The study results provide a better understanding of the conflicting effects of positive and negative prejudice on cross-shopping intention. Additionally, results shed light on the moderating role of intercultural factors on the relationship between negative prejudice and cross-shopping intention. Implications are identified together with consideration of the study limitations and avenues for future research.
The study aims to examine brand management model in Iran's professional Football League (2011-2012) with emphasis on brand image. The study was descriptive-survey one. A sample of Iranian professional football league fans (N=911) responded 4 items questionnaire. A structural equation model (SEM) test with maximum likelihood estimation was performed to test the relationships among the research variables. The analyses of data showed three dimensions of brand image influenced on fan’s brand loyalty of which the attitude was the most important. Benefits and attributes were placed in the second and third rank respectively. According to Results, brand image play a pivotal role between Iranian fans brand loyalty. Create an attractive and desirable brand image in the fans mind increases brand loyalty. And due to, revenue and profits increase through ticket sales and products of club and also attract more sponsors.
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 |