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: 8 / 8 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 01:20 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.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 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 |
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 3 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 6 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 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 8 / 8 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): 2026-10-21T07:22:48.130499+00:00 — 2026-10-23T01:20:12.444091+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 | 8 | 8/8 |
| 2018 | All selected publications | 0 | 8 | 8/8 |
| 2019 | All selected publications | 0 | 8 | 8/8 |
| 2020 | All selected publications | 0 | 8 | 8/8 |
| 2021 | All selected publications | 0 | 8 | 8/8 |
| 2022 | All selected publications | 0 | 8 | 8/8 |
| 2023 | All selected publications | 0 | 8 | 8/8 |
| 2024 | All selected publications | 0 | 8 | 8/8 |
| 2025 | All selected publications | 4 | 8 | 8/8 |
| 2026 | All selected publications | 3 | 8 | 8/8 |
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 |
| 2024 | 4 |
| 2025 | 1 |
| 2026 | 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 Business Ecosystem & Strategy Bussecon International Academy | 3 | 0 | 0 | 3/3 | 0.0 | 0 | 0.0 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 5 | 4 | 7 | 5/5 | 0.8 | 1 | 60.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
The fashion sector stands as one of the leading contributors to both the global economy and South Africa. In South Africa, the footwear segment alone commands a value exceeding R50 billion and continues to see steady expansion. Particularly notable is the surge in sales within the South African sneaker market, outpacing other footwear categories. This trend has prompted numerous brands to enter the fray, presenting consumers with abundant choices but also fostering intense competition among sneaker manufacturers. To stay competitive, these manufacturers consistently innovate by developing enhanced sneaker models and integrating cutting-edge technologies into their production processes. The study aimed to identify the determinants influencing the purchasing intentions of Generation Y consumers regarding sneakers. A survey, administered via self-report questionnaires, gathered data from a convenience sample of 400 Generation Y consumers aged 18 to 24. These individuals were selected from two public Higher Education Institutions located in Gauteng, South Africa. Data analysis encompassed various methods including reliability and construct validity assessment, factor analysis, descriptive statistics, correlation analysis, collinearity diagnostics, regression analysis, and independent samples t-tests. Findings reveal that brand image, the desire for uniqueness, and product features significantly and positively impact the purchasing intentions of Generation Y consumers concerning sneakers. Conversely, the study indicates that price exerts an insignificant influence on the purchasing intentions of Generation Y consumers regarding sneakers. In addition, the findings suggest that males tend to place greater importance on brand image when making sneaker purchases compared to their female counterparts. These findings highlight the importance of understanding the nuanced preferences and behaviors of Generation Y consumers in the sneaker market and adapting business strategies accordingly to capitalize on opportunities for growth and differentiation.
The proliferation of internet accessibility, mobile devices, the surge in online platforms and intelligent technologies, as well as the rapid advancements in the technological domain have fostered hyper-connectivity. This hyper-connectivity influences how consumers behave and make purchase decisions. This study makes use of quantitative research to explore the factors that influence the decision-making process of the hyper-connected consumer. Non-probability, simple random sampling was utilised for the study. The data was collected through surveys, and the instrument was tested using Likert scales. An online questionnaire was disseminated to consumers from within South Africa and yielded 306 valid responses. The results were analysed using exploratory factor analysis to identify and extract the latent factors of decision making for the hyper-connected consumer from the data collected. The main findings identified six factors that are grouped into intrinsic and extrinsic factors that influence the decision-making of the hyper-connected consumer. The intrinsic factors identified include personal insights and influences, and subjective knowledge. The extrinsic factors identified include sources/channels of information, price and financial influences, and personal and family needs. The factor labelled social influences was found to encompass characteristics of both intrinsic and extrinsic factors. The study not only provides greater insights into the changing nature of consumer behaviour in a hyper-connected world but also provides actionable insights for industry stakeholders.
The study examined the factors influencing motor vehicle purchase intention during the COVID-19 pandemic. The Theory of Planned Behaviour, the Social Judgement Theory, and the Self-Congruency Theory were employed for the study. A quantitative research approach was applied, and data was collected using a questionnaire that 223 respondents completed and selected through convenience sampling. A structural equation model was used to test the proposed conceptual model of the study. The empirical results revealed that perceived value, perceived reliability, and brand awareness of the vehicle, together with the manufacturer’s and/or seller’s website quality, positively impact the consumer’s attitude, which subsequently affects their purchase intentions. The study has both practical and theoretical implications. The findings from the study could assist motor vehicle marketers in developing marketing strategies during a pandemic and provide policymakers with guidelines for the marketing of motor vehicles during a pandemic.
In the ever-changing realm of retail banking, it is essential for banks to grasp the elements that affect customer decisions to stay ahead in the competition. This study delves into customer preferences when selecting a bank, focusing specifically on Absa Bank in South Africa. By utilizing a case study approach, the research delves into the factors that influence customer behavior in the retail banking industry. Referencing the consumer decision model, the study investigates various stages such as problem recognition, information search, evaluation of options, purchase decision, and post-purchase assessment. Factors such as security, convenience, assurance, accessibility, and responsiveness are pinpointed as crucial aspects in bank selection. The study employs quantitative research techniques, conducting surveys with Absa Bank customers to dissect their preferences. Findings suggest that transaction fees, corporate image, bank coverage, and size play a significant role in influencing customer decisions. The study emphasizes the importance of addressing these customer-identified factors to deter customer attrition. Recommendations include conducting regular surveys to keep abreast of changing customer preferences and maintaining a competitive edge. The research offered valuable insights that can guide strategic decision-making and marketing efforts in the retail banking sector.
In an incisive analysis of the marketing mix's impact on small retail businesses in Durban's Central Business District (CBD), this study scrutinizes the extended 7Ps framework: product, price, place, promotion, process, people and physical evidence. Utilizing a quantitative methodology, data from 217 owner-managers, captured via a 5-point Likert scale, were analysed through ANOVA and Tukey's HSD tests, unearthing deep insights. The findings disrupt conventional marketing paradigms, revealing that an intense focus on product attributes does not correlate with enhanced performance. Small businesses that maintained competitive, yet balanced pricing mechanisms outstripped are those that engages in fierce price wars, underscoring the dangers of excessive price reductions. Strategic promotional activities and well-considered choice locations were pivotal, whereas overemphasis on physical evidence and internal processes proved detrimental. The study results advocate for a balanced, strategic approach to the marketing mix, urging small businesses to rethink traditional priorities. This study offers crucial guidance for business owners seeking to optimize performance and calls for targeted policy measures to support the retail sector’s growth and sustainability.
This study investigated the factors influencing consumer repurchase intentions of beauty and haircare products on e-commerce platforms in South Africa. With the growing trend of online shopping, understanding the determinants of repurchase intention became essential for businesses looking to retain customers. The purpose of the study was to explore how various factors such as brand trust, security risk perception, ease of use, customer readiness, and loyalty impact consumer repurchase behaviour. A quantitative research design was employed, using an online questionnaire to collect data from 164 respondents who had previously purchased beauty and haircare products on an online shopping site for cosmetics in South Africa. The study utilised multiple regression analysis to assess the relationships among the identified factors and their influence on repurchase intentions. The findings revealed that brand trust, ease of use, and customer loyalty were significant positive predictors of repurchase intentions, while security risk perception had a negative impact. Readiness did not show a significant relationship with repurchase intentions. Based on these results, the study recommends that e-commerce businesses in the beauty sector focus on building trust, enhancing user-friendly interfaces, and fostering customer loyalty programs to encourage repeat purchases.
This study provides a comprehensive analysis of the marketing mix strategies that influence customer acquisition at Spar in Durban. Utilizing a quantitative methodology, data were collected through structured questionnaires completed by 278 respondents. The findings indicate that Spar effectively employs digital marketing tools—including social media, WhatsApp, and loyalty programs—as key communication channels to engage customers. Reliability analysis confirmed the validity of the measurement instrument (Cronbach’s ? = 0.902; KMO = 0.899). The results demonstrate that younger consumers are more responsive to digital platforms, particularly social media and loyalty programs, while traditional methods such as printed flyers are less effective. No significant differences were observed in the perceived effectiveness of specific digital channels across different respondent groups, suggesting a consistent perception of Spar’s digital engagement. The study emphasizes the importance of integrating digital strategies with factors such as pricing, convenience, and product assortment to enhance customer acquisition in Durban’s competitive retail environment.
In the face of heightened global competition, micro and small enterprises (MSEs) in Durban, South Africa, face challenges such as limited resources and restricted market access, which hinder their ability to achieve sustained growth and profitability. This study aims to examine the influence of the 4Ps marketing mix on the performance of MSEs. A cross-sectional, descriptive study with a quantitative research design was employed. Data was collected from 217 MSEs using structured questionnaires, and the analysis was conducted with SPSS 29. Multiple regression analysis was used to examine the relationship between the 4Ps (product, price, promotion, place) and MSEs' performance. The findings show that pricing decisions are a significant determinant of performance, while product diversity does not necessarily enhance business outcomes, emphasizing the importance of strategic product management. Promotional efforts, while positive, were statistically insignificant, indicating complexities in their impact. The relationship between physical location (place) and performance was weak, suggesting a need for MSEs to optimise distribution channels through omnichannel strategies. In conclusion, MSEs can improve performance by refining promotional strategies, leveraging pricing and optimising distribution networks. Further research is suggested to explore the generalizability of these findings across different industries and additional factors influencing marketing strategies.
In the ever-changing realm of retail banking, it is essential for banks to grasp the elements that affect customer decisions to stay ahead in the competition. This study delves into customer preferences when selecting a bank, focusing specifically on Absa Bank in South Africa. By utilizing a case study approach, the research delves into the factors that influence customer behavior in the retail banking industry. Referencing the consumer decision model, the study investigates various stages such as problem recognition, information search, evaluation of options, purchase decision, and post-purchase assessment. Factors such as security, convenience, assurance, accessibility, and responsiveness are pinpointed as crucial aspects in bank selection. The study employs quantitative research techniques, conducting surveys with Absa Bank customers to dissect their preferences. Findings suggest that transaction fees, corporate image, bank coverage, and size play a significant role in influencing customer decisions. The study emphasizes the importance of addressing these customer-identified factors to deter customer attrition. Recommendations include conducting regular surveys to keep abreast of changing customer preferences and maintaining a competitive edge. The research offered valuable insights that can guide strategic decision-making and marketing efforts in the retail banking sector.
In an incisive analysis of the marketing mix's impact on small retail businesses in Durban's Central Business District (CBD), this study scrutinizes the extended 7Ps framework: product, price, place, promotion, process, people and physical evidence. Utilizing a quantitative methodology, data from 217 owner-managers, captured via a 5-point Likert scale, were analysed through ANOVA and Tukey's HSD tests, unearthing deep insights. The findings disrupt conventional marketing paradigms, revealing that an intense focus on product attributes does not correlate with enhanced performance. Small businesses that maintained competitive, yet balanced pricing mechanisms outstripped are those that engages in fierce price wars, underscoring the dangers of excessive price reductions. Strategic promotional activities and well-considered choice locations were pivotal, whereas overemphasis on physical evidence and internal processes proved detrimental. The study results advocate for a balanced, strategic approach to the marketing mix, urging small businesses to rethink traditional priorities. This study offers crucial guidance for business owners seeking to optimize performance and calls for targeted policy measures to support the retail sector’s growth and sustainability.
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 |