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 — 22 Oct 2026 18:20 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 |
|---|---|---|---|---|---|
| 2024 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 5 | 8 | 8/8 | 8/8 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 9 | 8 | 8/8 | 8/8 |
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): 2026-10-21T07:22:53.430718+00:00 — 2026-10-22T18:20:04.240065+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 | 5 | 8 | 8/8 |
| 2026 | All selected publications | 4 | 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 |
|---|---|
| 2024 | 8 |
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 | 1 | 1 | 1 | 1/1 | 1.0 | 1 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 7 | 4 | 8 | 7/7 | 0.57 | 0 | 42.9 | 7/7 · 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.
Understanding the impact of Risk Tolerance and Brand Trust on Investment Decisions and Customer Engagement Behavior is imperative in today's competitive financial environment. This study investigates the direct and mediating effects of Risk Tolerance and Brand Trust on Investment Decisions and Customer Engagement Behavior. Utilizing a quantitative approach with a survey method, data were collected from 144 private customers of Bank BRI in East Java through random sampling techniques. Structural Equation Modeling (SEM) was employed for data analysis. The research reveals significant direct effects of Risk Tolerance and Brand Trust on Investment Decisions. Likewise, the direct effects of brand trust and investment decision on customer engagement behavior are significant. However, the influence of risk tolerance on customer engagement behavior is not significant. These findings underscore the intricate dynamics of consumer behavior in the financial sector. This study contributes to a deeper understanding of how risk perception and trust in the brand affect investment decisions and customer engagement behavior, offering insights for strategic decision-making in the banking industry.
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 aim of this study is to evaluate the convenience, promotion, and security factors associated with the use of Shopee Pay electronic currency by visitors in malls in the Central Jakarta region. The study sample comprises persons who frequent shopping malls in the Central Jakarta Region. This survey includes a group of 103 persons who use Shopee Pay electronic money in the mall area of Centra Jakarta. The sample selection was carried out using the method of incidental sampling. The data used in this study include primary data, especially questionnaires that were distributed to respondents. The study results suggest that the convenience and promotional activities have a positive influence on the decision to use Shopee Pay digital currency. This suggests that the choice to utilise electronic currency is impacted by factors such as convenience and promotional offers. Before proceeding, consumers will evaluate whether a system would streamline their activities, considering the wide array of attractive offers offered by the shopeepay site, as well as compelling marketing about available specials on the platform. Furthermore, security concerns negatively affect the willingness to use Shopee Pay as a digital payment option. This text explores the relationship between security and the choice to use electronic money. Before choosing the Electronic Money platform, customers must ensure that the funds saved in the electronic wallet will be protected and resistant to unauthorised access, therefore reducing the likelihood of unwanted events.
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 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.
Understanding the impact of Risk Tolerance and Brand Trust on Investment Decisions and Customer Engagement Behavior is imperative in today's competitive financial environment. This study investigates the direct and mediating effects of Risk Tolerance and Brand Trust on Investment Decisions and Customer Engagement Behavior. Utilizing a quantitative approach with a survey method, data were collected from 144 private customers of Bank BRI in East Java through random sampling techniques. Structural Equation Modeling (SEM) was employed for data analysis. The research reveals significant direct effects of Risk Tolerance and Brand Trust on Investment Decisions. Likewise, the direct effects of brand trust and investment decision on customer engagement behavior are significant. However, the influence of risk tolerance on customer engagement behavior is not significant. These findings underscore the intricate dynamics of consumer behavior in the financial sector. This study contributes to a deeper understanding of how risk perception and trust in the brand affect investment decisions and customer engagement behavior, offering insights for strategic decision-making in the banking industry.
The increasing nature of competition in the higher education sector of Botswana means that universities need to craft strategies to be more competitive. The recipe for competitiveness is primarily hinged on the ability of institutions to be cognisant of the factors that influence prospective learners in selecting a university of choice to study. They also critically need to know the sources of information where prospective learners acquire information to redirect their marketing strategies. To achieve these objectives, the purpose of this study was to investigate the factors influencing the choice of university of study as well as their sources of information in influencing choice decision-making. The study followed a qualitative research approach and data was collected using in-depth interviews. Thematic narrative analysis was used to unpack the underlying influences on decision-making. The findings indicate that prospective students get their information from multiple factors. The most influential sources identified are family and friends, career fairs and exhibitions, social media, and to a lesser extent the mass media and promotional materials. The findings also showed that prospective university students’ choice of university is influenced by a variety of factors. These include university location, availability of accommodation, perceptions of university reputation, quality of academic programs, alignment of lifelong interests and desires, and the perception of employability. There are other factors that are less influential as degree of persuasion, funding issues, costs associated with applications as well as government processes and procedures. These findings have potential to influence university marketing strategies and policies in seeking competitiveness and improvement in enrolment numbers.
The aim of this study is to evaluate the convenience, promotion, and security factors associated with the use of Shopee Pay electronic currency by visitors in malls in the Central Jakarta region. The study sample comprises persons who frequent shopping malls in the Central Jakarta Region. This survey includes a group of 103 persons who use Shopee Pay electronic money in the mall area of Centra Jakarta. The sample selection was carried out using the method of incidental sampling. The data used in this study include primary data, especially questionnaires that were distributed to respondents. The study results suggest that the convenience and promotional activities have a positive influence on the decision to use Shopee Pay digital currency. This suggests that the choice to utilise electronic currency is impacted by factors such as convenience and promotional offers. Before proceeding, consumers will evaluate whether a system would streamline their activities, considering the wide array of attractive offers offered by the shopeepay site, as well as compelling marketing about available specials on the platform. Furthermore, security concerns negatively affect the willingness to use Shopee Pay as a digital payment option. This text explores the relationship between security and the choice to use electronic money. Before choosing the Electronic Money platform, customers must ensure that the funds saved in the electronic wallet will be protected and resistant to unauthorised access, therefore reducing the likelihood of unwanted events.
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 |