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: 7 / 7 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 — 22 Oct 2026 02:32 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.
6 / 7 with data · 1 missing or unmatched. Percentages use all 7 selected publications.
6 / 7 with data · 1 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 29 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 47 | 7 | 7/7 | 7/7 |
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 7 / 7 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): 2026-10-21T07:22:43.069954+00:00 — 2026-10-22T02:32:27.890067+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 0 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 0 | 7 | 7/7 |
| 2022 | All selected publications | 4 | 7 | 7/7 |
| 2023 | All selected publications | 12 | 7 | 7/7 |
| 2024 | All selected publications | 8 | 7 | 7/7 |
| 2025 | All selected publications | 18 | 7 | 7/7 |
| 2026 | All selected publications | 5 | 7 | 7/7 |
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 |
|---|---|
| 2022 | 7 |
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 | 7 | 29 | 47 | 7/7 | 4.14 | 2 | 71.4 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
The aim of the study is to explore the impact of brand awareness, brand loyalty and brand attitude on purchase intention in online shopping. The study was quantitative in nature adopting the survey method. Due to the absence of a sampling frame, convenience sampling, a form of non-probability sampling was utilised a total of 253 responses well collected from Braamfontein, a busy business district in Johannesburg, South Africa. In order to test the proposed hypotheses, a unique conceptual model was developed in which brand awareness, brand loyalty, and brand attitude acted as predictors while purchase intention served as the outcome. Data analysis was conducted in SPSS 27 where descriptive statistics were produced as well as regression analysis to test the proposed hypothesis. Findings suggested that customers perceived brand attitude to have the strongest impact on purchase intention while the weakest predictor of purchase intention was brand awareness as far as online purchasing was concerned. Managerial implications emerged from the study and suggestions for further research were proposed.
This paper explores the relationship between content marketing and consumer brand loyalty to the ‘New-China-Chic’ brand. It constructs a structural equation model, Through questionnaires distributed to the fan groups of various brands and offline stores, results show that the four different dimensions of content marketing strategy, namely the culture, entertainment, emotion and interaction, are the main factors affecting consumers' loyalty to the ‘New-China-Chic’ brand. Among them, emotional content and cultural content??= 0.304??= 0.209) have a strong impact on brand loyalty. Brand identity also plays a strong intermediary role in the relationship between the four different dimensions of content marketing and brand loyalty. Moreover, the data shows that consumer ethnocentrism has a significant regulatory effect on brand identity and brand loyalty in cultural content and emotional content, while interactive content and entertainment content have a weak impact.
China as a hot luxury market has witnessed high growth in luxury sales despite the COVID-19. In recent years, many luxury companies have further improved their brand value and influence via co-branding strategies, however, their brand cooperation received mixed evaluations. Drawing on the conceptual blending theory and self-concept consistency theory, this paper constructs and verifies the structural equation model of consumer evaluation of luxury co-branding from the perspectives of the brands and the consumers. The study reveals that luxury co-branding fit, advertising types and the consumers’ life-role transition have a positive impact on consumer evaluation. Both the type of advertising and consumers’ life-role transition have a moderating effect on consumer evaluation. Specifically, (i) In luxury co-branding, the co-branded products paired with a high fit between the values of the cooperative brands are more likely to receive high consumer evaluation; (ii) The publicity of the brand image of the co-branded products has a stronger moderating effect on the perceived quality, appeal and purchase intention of luxury users than the publicity of the features of the co-branded products; (iii) For luxury brands with a high degree of joint fit, consumers who have not experienced life-role transformation have a stronger regulatory effect on consumers' perceived quality, attractiveness and purchase intention than consumers who have experienced life-role transformation.
The subject of scientific research is the examination of the difference in brand loyalty factors according to the socio-demographic characteristics (age, education, income level) of confectionary consumers, as well as the examination of the connection between brand loyalty factors and brand loyalty of confectionary consumers in Serbia. 200 respondents completed the structured questionnaire. Determining the difference in brand loyalty factors according to socio-demographic characteristics of confectionary consumers was performed using the f test, while the correlation between the brand loyalty factors and brand loyalty was performed using Spearman's rank correlation as a non-parametric alternative to Pearson's correlation. It was determined that there is a significant difference in brand loyalty factors according to the age, education, and income level of confectionary consumers. There is also a statistically significant correlation between all brand loyalty factors and brand loyalty.
This study conducts an empirical analysis of the relationship between brand memory of hot mass consumption products and consumers’ intention for continuous purchase using a quantitative structural equation model. 443 surveys are collected to test the model. It is found that all dimensions of the brand memory of hot mass consumption products have a positive impact on consumers’ intention for continuous purchase. In addition, this study reveals that consumers’ brand knowledge of the hot mass consumption product plays a mediating role in the impact of brand memory of the hot product on consumers’ intention for continuous purchase. Research findings will contribute to the understanding of the antecedents of hot mass product popularity and the mediating role of brand knowledge both theoretically and practically.
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 subject of scientific research is the examination of the difference in brand loyalty factors according to the socio-demographic characteristics (age, education, income level) of confectionary consumers, as well as the examination of the connection between brand loyalty factors and brand loyalty of confectionary consumers in Serbia. 200 respondents completed the structured questionnaire. Determining the difference in brand loyalty factors according to socio-demographic characteristics of confectionary consumers was performed using the f test, while the correlation between the brand loyalty factors and brand loyalty was performed using Spearman's rank correlation as a non-parametric alternative to Pearson's correlation. It was determined that there is a significant difference in brand loyalty factors according to the age, education, and income level of confectionary consumers. There is also a statistically significant correlation between all brand loyalty factors and brand loyalty.
Modern society today relies on the ideology of consumption, not just a marker of the social status of a person or group but a mechanism used by consumers to gain social status or prestige by buying or consuming goods considered high by customers. The increasing reach of consumerism ideology has expanded the traditional definition of a "commodity" into an intangible service, especially in universities' operations. Surveys show that students tend to act as consumers in university education. Consumerism correlates with brand personality. There is a fine line that universities must build and maintain that will enable academics within universities to express integrity and intellectual qualities in both their teaching and research. This expression should include students as participants and recipients not only when they are involved in the class but as participants and recipients in the community in which the University is located.
This paper explores the relationship between content marketing and consumer brand loyalty to the ‘New-China-Chic’ brand. It constructs a structural equation model, Through questionnaires distributed to the fan groups of various brands and offline stores, results show that the four different dimensions of content marketing strategy, namely the culture, entertainment, emotion and interaction, are the main factors affecting consumers' loyalty to the ‘New-China-Chic’ brand. Among them, emotional content and cultural content??= 0.304??= 0.209) have a strong impact on brand loyalty. Brand identity also plays a strong intermediary role in the relationship between the four different dimensions of content marketing and brand loyalty. Moreover, the data shows that consumer ethnocentrism has a significant regulatory effect on brand identity and brand loyalty in cultural content and emotional content, while interactive content and entertainment content have a weak impact.
The aim of the study is to explore the impact of brand awareness, brand loyalty and brand attitude on purchase intention in online shopping. The study was quantitative in nature adopting the survey method. Due to the absence of a sampling frame, convenience sampling, a form of non-probability sampling was utilised a total of 253 responses well collected from Braamfontein, a busy business district in Johannesburg, South Africa. In order to test the proposed hypotheses, a unique conceptual model was developed in which brand awareness, brand loyalty, and brand attitude acted as predictors while purchase intention served as the outcome. Data analysis was conducted in SPSS 27 where descriptive statistics were produced as well as regression analysis to test the proposed hypothesis. Findings suggested that customers perceived brand attitude to have the strongest impact on purchase intention while the weakest predictor of purchase intention was brand awareness as far as online purchasing was concerned. Managerial implications emerged from the study and suggestions for further research were proposed.
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 |