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 01:52 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 |
|---|---|---|---|---|---|
| 2025 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 7 | 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): 2026-10-21T07:22:59.995012+00:00 — 2026-10-22T01:52:42.026254+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 | 1 | 8 | 8/8 |
| 2026 | All selected publications | 6 | 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 |
|---|---|
| 2025 | 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 |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 1 | 2 | 1 | 1/1 | 2.0 | 2 | 100.0 | 1/1 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 2 | 3 | 3 | 2/2 | 1.5 | 1.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 5 | 3 | 3 | 5/5 | 0.6 | 1 | 60.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
This study explores the influence of digital marketing strategies on brand loyalty among young airline passengers, specifically targeting Millennials and Gen Z individuals aged 18-35 years old. With the increasing reliance on digital channels such as social media, email marketing, and search engine marketing, it is crucial to understand how these strategies impact the customer-brand relationship, brand trust, and ultimately, brand loyalty. The research employs a quantitative approach, gathering data from 230 participants who are frequent users of digital platforms and have recent travel experiences with airlines. The findings reveal that social media marketing has the most significant impact on the customer-brand relationship, followed by email and search engine marketing. Additionally, the study confirms that brand trust acts as a critical mediator between digital marketing activities and brand loyalty. These results highlight the importance of tailored digital marketing strategies for airlines aiming to engage and retain young passengers in a highly competitive industry.
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.
This paper aims to evaluate the effects of demographic targeting, platform selection, and engagement metrics on the effectiveness of social media advertising campaigns. In this paper, it is also aimed to provide a comprehensive understanding of how these factors influence conversion outcomes. We employed a hybrid analytics method combining ANOVA, correlation, and regression analysis to examine patterns of user engagement and ad performance. A dataset of 200,235 ad campaign records conducted in the United States was analyzed to assess variations across gender, age groups, and platforms. The main findings of the study demonstrate that (i) women consistently exhibited higher conversion rates compared to men, highlighting the potential of gender-specific content strategies; (ii) users aged 35–44 achieved the highest engagement, suggesting that middle-aged audiences may be more responsive to targeted campaigns; and finally, (iii) among platforms, Instagram led in conversion performance, while Facebook showed comparable engagement rates, and both significantly outperformed other platforms in terms of overall impact. Click-through rate was found to be moderately correlated with conversions, whereas impressions showed weak returns, indicating diminishing value at higher exposure levels. These results underscore the importance of optimizing both message and delivery channel to specific audience segments.This study contributes to digital marketing literature by integrating demographic variables, engagement indicators, and platform performance into a unified model. The insights derived offer practical implications for businesses and advertisers aiming to enhance return on investment and optimize campaign strategies in a fast-paced, digitally driven advertising landscape.
This study examines the impact of social media exposure to promotional discounts on the travel intentions and purchasing behaviours of Millennials and Generation X airline consumers in the National Capital Region (NCR), Philippines, as social media and technology increasingly serve as vital instruments in the airline industry's marketing and promotional sales strategies. Due to the existence of studies on this topic elsewhere, there is a paucity of research and statistics available to reflect the current state of the Philippine aviation business. Considering that airlines are gradually rebounding from the challenges posed by the early pandemic and the tourism business is currently thriving, the researchers found it compelling and recognised the potential for more investigation on this topic. The researchers conducted an analysis of data from 390 respondents using PLS-SEM, revealing that social media exposure does not directly affect travel intentions, although both brand image and promotional discounts do have an influence. Travel intentions serve as significant indicators of purchasing behaviour. Promotional discounts act as an essential intermediary between social media visibility and brand perception regarding travel intentions. These findings underscore the significance of integrating Promotional Discounts into social media and branding efforts to effectively enhance customer Travel Intention. Scholars and researchers may significantly benefit from the conceptual framework and findings of the present study. Additional investigation into the interrelations among the elements may enhance the economic resilience of the tourism and airline industries during a pandemic. The findings indicate that promotional discounts serve as a mediator; therefore, marketers and decision-makers in the tourism sector should explore strategies to enhance their advertising and marketing approaches to boost travel intentions and foster business growth.
Historically, corporations have leveraged the popularity of renowned celebrities as influencers to market their products in the hope that prospective clients will mimic the choice of these celebrities. This practice has become popular in recent times with the emergence of diverse social networking sites. With huge financial resources expended in retaining these celebrities, the question is whether the success achieved by brands can be attributable to them. This study investigates the use of celebrity influencers in building popularity and loyalty for American (iPhone), Korean (Samsung), and Chinese smartphones in the emerging Nigerian market. It employs a quantitative, cross-sectional design, working with 416 respondents. The findings indicate that the iPhone is the most popular brand in Nigeria and suggest that although participants express excitement with the notion of celebrity influencers and endorse their use in promotional pursuits, they hold the belief that the popularity of these brands cannot be attributable to the use of celebrities. It goes further to state that using celebrities may not foster brand loyalty. The study concludes that while it makes marketing sense, and indeed is exciting to use celebrity influencers in marketing activities, without other factors in consideration, such a strategy will not inspire customer loyalty.
Instagram has emerged not only as a social networking platform but also as a vital digital marketing tool for fashion brands. However, missed marketing opportunities persist due to factors such as limited computer literacy, unfamiliarity with digital tools, and resistance to new media. The aim of the study is to explore the opportunities for leveraging Instagram as an effective marketing tool within the fashion industry in Durban. Specifically, it seeks to identify how fashion businesses can utilise Instagram to enhance brand visibility, engage with their target audience, and maximize promotional efforts to drive success in the digital marketplace. This quantitative study employed a purposive sampling method and focused on descriptive analysis through a structured online questionnaire distributed to 130 fashion businesses in Durban. The findings underscore Instagram's efficacy in enabling fashion businesses to effectively showcase products, engage visually with their target audience, and amplify brand awareness. The platform's visual-centric nature inherently supports robust brand marketing and promotion, particularly in the fashion sector. Recommendations highlight the imperative for fashion brands to strategically leverage Instagram to enhance visibility and augment brand perception. Success on Instagram necessitates a well-coordinated marketing approach to ensure impactful brand promotion and engagement with followers.
This paper aims to evaluate the effects of demographic targeting, platform selection, and engagement metrics on the effectiveness of social media advertising campaigns. In this paper, it is also aimed to provide a comprehensive understanding of how these factors influence conversion outcomes. We employed a hybrid analytics method combining ANOVA, correlation, and regression analysis to examine patterns of user engagement and ad performance. A dataset of 200,235 ad campaign records conducted in the United States was analyzed to assess variations across gender, age groups, and platforms. The main findings of the study demonstrate that (i) women consistently exhibited higher conversion rates compared to men, highlighting the potential of gender-specific content strategies; (ii) users aged 35–44 achieved the highest engagement, suggesting that middle-aged audiences may be more responsive to targeted campaigns; and finally, (iii) among platforms, Instagram led in conversion performance, while Facebook showed comparable engagement rates, and both significantly outperformed other platforms in terms of overall impact. Click-through rate was found to be moderately correlated with conversions, whereas impressions showed weak returns, indicating diminishing value at higher exposure levels. These results underscore the importance of optimizing both message and delivery channel to specific audience segments.This study contributes to digital marketing literature by integrating demographic variables, engagement indicators, and platform performance into a unified model. The insights derived offer practical implications for businesses and advertisers aiming to enhance return on investment and optimize campaign strategies in a fast-paced, digitally driven advertising landscape.
This study investigates the strategic effectiveness of social media advertising by analyzing the relationship between platform selection, audience demographics, and campaign performance metrics. Using a dataset encompassing Instagram, Facebook, Pinterest, and Twitter, the research evaluates key indicators such as engagement, conversion rates, and return on investment (ROI). By employing statistical methods like ANOVA and regression analysis in SPSS, the study aims to identify optimal platform-audience combinations and assess how different campaign goals influence outcomes. The findings will provide valuable insights for advertisers and businesses seeking to enhance their social media strategies and maximize advertising effectiveness.
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.
This study examines the impact of social media exposure to promotional discounts on the travel intentions and purchasing behaviours of Millennials and Generation X airline consumers in the National Capital Region (NCR), Philippines, as social media and technology increasingly serve as vital instruments in the airline industry's marketing and promotional sales strategies. Due to the existence of studies on this topic elsewhere, there is a paucity of research and statistics available to reflect the current state of the Philippine aviation business. Considering that airlines are gradually rebounding from the challenges posed by the early pandemic and the tourism business is currently thriving, the researchers found it compelling and recognised the potential for more investigation on this topic. The researchers conducted an analysis of data from 390 respondents using PLS-SEM, revealing that social media exposure does not directly affect travel intentions, although both brand image and promotional discounts do have an influence. Travel intentions serve as significant indicators of purchasing behaviour. Promotional discounts act as an essential intermediary between social media visibility and brand perception regarding travel intentions. These findings underscore the significance of integrating Promotional Discounts into social media and branding efforts to effectively enhance customer Travel Intention. Scholars and researchers may significantly benefit from the conceptual framework and findings of the present study. Additional investigation into the interrelations among the elements may enhance the economic resilience of the tourism and airline industries during a pandemic. The findings indicate that promotional discounts serve as a mediator; therefore, marketers and decision-makers in the tourism sector should explore strategies to enhance their advertising and marketing approaches to boost travel intentions and foster 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 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 |