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: 13 / 13 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 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 00:14 UTC — 21 Oct 2026 00:14 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.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 selected publications.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 selected publications.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 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 | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 7 | 4 | 4/4 | 4/4 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 11 | 4 | 4/4 | 4/4 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 4 | 4/4 | 4/4 |
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 13 / 13 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): 2026-10-21T00:14:27.777686+00:00 — 2026-10-21T00:14:35.030364+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 | 13 | 13/13 |
| 2018 | All selected publications | 0 | 13 | 13/13 |
| 2019 | All selected publications | 0 | 13 | 13/13 |
| 2020 | All selected publications | 0 | 13 | 13/13 |
| 2021 | All selected publications | 0 | 13 | 13/13 |
| 2022 | All selected publications | 0 | 13 | 13/13 |
| 2023 | All selected publications | 4 | 13 | 13/13 |
| 2024 | All selected publications | 6 | 13 | 13/13 |
| 2025 | All selected publications | 6 | 13 | 13/13 |
| 2026 | All selected publications | 4 | 13 | 13/13 |
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 | 1 |
| 2022 | 1 |
| 2023 | 4 |
| 2024 | 1 |
| 2025 | 2 |
| 2026 | 4 |
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 | 13 | 13 | 20 | 13/13 | 1.0 | 1 | 61.5 | 13/13 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to examine and analyze the influence of social media communications created by companies (Firm-created Communication – FCC) and users (User-generated Communication – UGC) on the user's perspective on brand equity and brand attitudes that have an impact on the purchase intention of Samsung products. The population of this study is users who do not use Samsung products to describe their interest in buying Samsung products. The object of this research is social media communications made by companies and users about Samsung products. The research sample consisted of 218 respondents who were not Samsung users and who at the time of the study were domiciled in Java or outside Java. The research data were then analyzed using the Structural Equation Model (AMOS v 23). Based on the research results, it is known that social media communications made by companies positively influence brand attitudes. User-generated social media communications positively influence brand equity and brand attitudes. Brand attitude positively affects brand equity. Brand equity and brand attitude positively influence purchase intention. However, social media communications made by the company have no effect on brand equity. This study reveals that communication made by users has more influence on purchase intention through brand equity and attitudes. Where equity and brand attitude are important in buying interest in a product.
Social media has become a vital tool for entrepreneurs, enabling them to expand their reach, enhance brand visibility, and engage directly with customers. Platforms like Facebook, Instagram, and LinkedIn provide entrepreneurs with cost-effective ways to access global markets, promote their products, and foster meaningful relationships with consumers. While social media has facilitated the growth of entrepreneurship by lowering barriers to entry, challenges such as managing online presence, handling negative feedback, and addressing privacy concerns persist. This study aims to systematically review existing literature to explore how entrepreneurs can strategically leverage social media for growth, examining its economic benefits, challenges, and best practices. Findings from the review reveal that social media offers entrepreneurs substantial advantages, including increased brand awareness, enhanced customer engagement, and improved sales performance through direct sales features and promotional campaigns. Additionally, social media enables networking, resource acquisition, and business model innovation. However, challenges related to platform management, algorithm changes, and privacy risks must be navigated. Based on these findings, the study recommends that entrepreneurs develop a clear social media strategy, actively engage with customers, stay updated with trends, and leverage data analytics to optimise their marketing efforts. Building brand communities and fostering customer loyalty through personalised communication and consistent interaction can further support business growth.
The tourism industry is a sector that continues to be developed by the Indonesian government. Especially during the current Covid 19 pandemic, tourism must be given a touch of differentiation to adapt to government regulations regarding the safety of tourism objects. The development of social media is essential in the world of tourism, where it can change the behaviour of tourists to enjoy tourism services. This study aims to understand the social media preference in tourist destinations so that tourism destinations can analyze social media marketing competitive strategy according to the target market. This study uses the MDS method and cluster analysis. This study collects data from 240 respondents. Respondents were asked to rate ten social media pairs where the social media observed were Instagram, YouTube, Facebook, Twitter, and Tik Tok. This research found that a perceptual map is essential to define consumer perceptions and preferences on social media.
Digital marketing practices have had explosive growth in the past decade, especially in the insurance sector of developing countries. In particular, the internet has been instrumental in providing digital marketing services to customers from the insurance sector. The purpose of this study, therefore, is to assess the effect of digital marketing practices on the performance of the insurance sector. A desktop literature review was used for this purpose. Relevant seminal references and journal articles for the study were identified using Google Scholar. The inclusion criteria entailed papers that were not over ten years old. The study found that the use of digital marketing strategies has a positive effect on the insurance sector's performance. Profitability improved, market share grew, and they expanded their market share. Increased customer loyalty and access to new markets are benefits of internet marketing for insurance companies. According to the findings, insurance companies should make IT infrastructure investments and implement technology-enhanced processes. Employers require adequate training on the use of e-business platforms, as well as collaboration with providers of digital services to enable them to store and market their products and services online. Aside from using traditional marketing methods (such as direct mail), the study advises general insurance companies to be innovative by implementing new strategies, such as digital marketing, to gain a larger share of their target market. This is because strategies for digital marketing have a positive impact on the overall performance of the insurance industry.
This study explored the influence of electronic word-of-mouth (e-WOM) on the online purchasing behaviour of Generation Z and Millennial students in South Africa, specifically identifying key e-WOM factors influencing consumer decisions and examining the role of demographic differences in shaping these behaviours. A quantitative, cross-sectional survey was conducted with 288 students and lecturers from Durban University of Technology. Data analysis was performed using SPSS software and regression analysis to examine the causal relationships between e-WOM factors and consumer buying behaviour. Key findings indicate that e-WOM significantly influences consumer buying behaviour, with factors such as e-WOM volume, e-WOM adoption and usage emerging as strong predictors. The influence of e-WOM was consistent across age groups and gender. The consistent influence of e-WOM on both Generation Z and Millennials, regardless of gender, suggests that unified e-WOM strategies can be developed for these generational cohorts, resulting in more efficient and cost-effective marketing campaigns. Based on these findings, digital marketers must focus on increasing the volume of e-WOM, particularly by encouraging customer reviews and enhancing social media engagement and leveraging user-generated content. Businesses can benefit from these approaches by enhancing brand trust, improving consumer decision-making and ultimately driving sales performance. Future studies could incorporate a mixed methods approach to provide a more comprehensive understanding of the phenomenon.
In the era of e-commerce and the increasing digitalization of consumer journeys, online customer reviews have become a decisive factor influencing potential buyers’ decisions. This study investigates the effect of online experience sharing on consumers’ purchase intentions across six key dimensions: emotional valence, quantity, content quality, responsiveness, reviewer reputation, and review recency. A quantitative research design was employed using data collected from a sample of 320 online consumers. The dataset was analyzed through multiple linear regression models to assess the relative impact of each dimension. The findings reveal that all six dimensions exert a positive and statistically significant influence on consumers’ purchase intentions, with emotional valence and review content emerging as the most influential factors. These results contribute to the growing body of literature on online consumer behavior and provide valuable managerial insights for digital marketing practitioners aiming to optimize electronic word-of-mouth strategies.
This study explored the complex decision-making process and the factors used by people, influencers, and brands when selecting social media platforms. The various factors include target demographics, values, content style, and overall marketing strategy. The study aimed to assess the importance of aligning personal preferences, user fit, and creative vision in selecting which social media platforms to use for a brand. To build a stronger level of engagement, content must be designed in a way that creates value for individual consumers. The Uses and Gratification Theory (UGT) provided a framework for understanding the motivations of millennials seeking a specific type of content on social media and how brands select social media platforms. A mixed-methods approach was used for the study to obtain the perspectives of both social media content creators and customers. The target population comprised millennials in the greater Durban area. Purposive sampling was used to select a sample of 400 participants for quantitative data and 10 content creators for qualitative data collection. Data was analysed both qualitatively and quantitatively using thematic analysis and SPSS version 28.0, respectively. The results contribute to a deeper understanding of the dynamic interplay between personal preferences, user fit, and creative vision in shaping the digital landscape. The study findings suggest that influencer marketing can be a powerful tool for promoting brand preference. Brands should carefully select influencers whose followers align with their target audience and ensure they have a strong following and the trust of their followers. The findings emphasise the effectiveness of diverse content types and customer appreciation posts. Businesses should tailor their content strategies to suit their brand identity and connect with their audience effectively. Different social media platforms offer unique features and formats.
This study explores the impact of digital marketing on consumer decision-making within Durban’s grocery retail sector, with a particular focus on Spar South Beach. Employing a quantitative descriptive survey approach, primary data was gathered through structured questionnaires distributed to 278 shoppers, complemented by secondary data from academic and government sources. Findings indicate that digital marketing significantly influences purchasing behaviors, with 78.6% of respondents acknowledging that Spar’s digital content influenced their decision to shop there. Social media was identified as the primary engagement channel, and digital loyalty rewards were strong predictors of repeat purchase intentions. Reliability analysis showed excellent scale consistency (Cronbach’s ? = 0.941, KMO = 0.943), and results revealed notable differences across age groups, with younger consumers exhibiting greater responsiveness to digital marketing efforts. Gender and educational attainment did not significantly moderate responses. These insights highlight the importance of leveraging social media campaigns, targeted promotions, and digital loyalty programs to enhance customer engagement and drive conversions, while also considering generational preferences. The study provides valuable, context-specific insights into the South African grocery retail industry, emphasizing the role of digital touchpoints in transitioning consumers from engagement to purchase.
The rapid development of digital technologies has significantly transformed the grocery retail industry, allowing retailers to utilize digital and social media platforms to enhance customer engagement, increase brand visibility, and drive sales growth. This study assesses the effectiveness of SPAR’s digital and social media marketing strategies in Durban, South Africa. Guided by the Technology Acceptance Model (TAM), the research employed a quantitative methodology, analyzing survey data collected from 278 customers at the South Beach Super Spar. Reliability analysis indicated a high level of internal consistency (Cronbach’s Alpha = 0.883). Non-parametric statistical tests, including the Kruskal-Wallis H and Mann–Whitney U tests, were used to evaluate customer perceptions of various digital channels. The results indicate that social media is the most effective platform for SPAR, with 58.4% of respondents identifying it as their primary mode of engagement. Participants overwhelmingly agreed that SPAR's social media channels effectively promote offers; however, perceptions of the mobile app and WhatsApp marketing strategies were mixed and showed significant variation among user groups. These findings underscore the importance of social media in increasing brand awareness and customer engagement, while also highlighting potential areas for enhancing the usability and impact of SPAR’s mobile application and WhatsApp marketing efforts. This study offers valuable guidance for grocery retailers aiming to strengthen customer engagement in competitive urban environments such as Durban by providing insights into digital marketing performance in emerging markets.
Social media has become a vital tool for entrepreneurs, enabling them to expand their reach, enhance brand visibility, and engage directly with customers. Platforms like Facebook, Instagram, and LinkedIn provide entrepreneurs with cost-effective ways to access global markets, promote their products, and foster meaningful relationships with consumers. While social media has facilitated the growth of entrepreneurship by lowering barriers to entry, challenges such as managing online presence, handling negative feedback, and addressing privacy concerns persist. This study aims to systematically review existing literature to explore how entrepreneurs can strategically leverage social media for growth, examining its economic benefits, challenges, and best practices. Findings from the review reveal that social media offers entrepreneurs substantial advantages, including increased brand awareness, enhanced customer engagement, and improved sales performance through direct sales features and promotional campaigns. Additionally, social media enables networking, resource acquisition, and business model innovation. However, challenges related to platform management, algorithm changes, and privacy risks must be navigated. Based on these findings, the study recommends that entrepreneurs develop a clear social media strategy, actively engage with customers, stay updated with trends, and leverage data analytics to optimise their marketing efforts. Building brand communities and fostering customer loyalty through personalised communication and consistent interaction can further support business growth.
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 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:49 UTC · ijbes | complete · ijbes · 20 Oct 2026 19:48 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |