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: 10 / 10 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: 22 Oct 2026 01:09 UTC — 22 Oct 2026 02:50 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.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 38 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 79 | 10 | 10/10 | 10/10 |
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 10 / 10 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): 2026-10-22T01:09:59.791308+00:00 — 2026-10-22T02:50:56.605661+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 | 10 | 10/10 |
| 2018 | All selected publications | 0 | 10 | 10/10 |
| 2019 | All selected publications | 0 | 10 | 10/10 |
| 2020 | All selected publications | 0 | 10 | 10/10 |
| 2021 | All selected publications | 6 | 10 | 10/10 |
| 2022 | All selected publications | 21 | 10 | 10/10 |
| 2023 | All selected publications | 25 | 10 | 10/10 |
| 2024 | All selected publications | 16 | 10 | 10/10 |
| 2025 | All selected publications | 7 | 10 | 10/10 |
| 2026 | All selected publications | 4 | 10 | 10/10 |
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 | 10 |
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 | 3 | 1/1 | 1.0 | 1 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 9 | 37 | 76 | 9/9 | 4.11 | 3 | 100.0 | 9/9 · 100.0% |
* Percentage among publications with a known citation count.
The study was motivated by the need to highlight the roles played by social media marketing on consumers' purchase intention during the COVID-19 pandemic. Since it was a quantitative study, hypotheses were tested to generate findings. We used IBM SPSS 25.0 software to analyze using reliability statistics, descriptive statistics, and IBM SPSS Amos 26.0 software was used to do confirmatory factor analysis for the purpose of developing hypothesis, and SEM used for trying to fit the model. The primary data was mustered by personal interview in an online survey method through a structured questionnaire with five-point Likert scales from 240 Bangladeshi online consumers. These findings publicized that social media marketing (Facebook, Instagram, and YouTube) a significant stimulus on consumers purchase intention during COVID-19, and all factors except discount or coupon offer and brand awareness had an epoch-making and constructive connection with consumers’ purchase intention during the coronavirus malady (COVID-19) epidemic in Bangladesh.
This study aims to analyze the influence of elements of social media marketing activity on consumer engagement and brand knowledge including brand awareness and image. This study used a quantitative method and purposive sampling technique on 250 respondents. The research was conducted on all Indonesian citizens who use social media WhatsApp, Facebook, Instagram, youtube, and TikTok regarding the culinary business of celebrities and YouTubers in Indonesia. The method used is the Structural Equation Model with AMOS 24.0 Software. The results of this study indicate that the interaction variables, trends, and EWOM have a positive and significant effect on consumer engagement, and consumer engagement has a positive and significant effect on brand awareness and brand image. While the entertainment and customization variables have no significant effect on consumer engagement.
This research empirically investigates consumers’ perception of real-time marketing as a marketing tool that is increasingly being used by businesses. Based on the review of literature, the paper aims to delve into real-time marketing and explore the elements of real-time marketing that influence consumers' perception of RTM campaigns. This study adopted a quantitative methodology. A total of 201 consumers completed an online survey in Gauteng, South Africa. To identify underlying factors that influence the consumer's perception of various real-time marketing campaigns, exploratory factor analysis was conducted. Descriptive statistic was used to provide a further summary of the basic characteristics of the sample. The research findings indicate that consumers value real-time marketing communication campaigns that offer value. Consumers' perception of value includes any real-time marketing campaign that offers some financial gain in the form of immediate and personalized discounts. This research provides retailers with a greater understanding of what consumers perceive as valuable and what they regard as clutter when it comes to real-time marketing campaigns
Donations through social media or any online platforms are becoming a new trend these days, thanks to the use of emotional marketing through narrations and visual depictions showing the real condition of people who need supports. Organizations are led to raise people’s emotions to increase their intention to make donations. This study aims to examine the effect of emotional marketing on donation intention through social media platforms and people’s willingness to use technology (UTAUT). This is explanatory research was conducted through a survey on 365 respondents of Malang city who had seen a crowdfunding commercial of Kitabisa.com. The structural equation analysis has led to findings that emotional marketing significantly influences people’s donation intention, implying that the commercial is able to affect people’s emotion into empathy and willingness to make donations through the charity campaign. Furthermore, this study also finds that UTAUT has a significant effect on the intention. The findings are useful for Kitabisa.com in their effort to increase people’s donation intention through the use of emotional marketing.
This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.
This study aims to find out how social media marketing activities influence consumer equity through brand equity in a culinary brand. The study sample is men and women, 200 respondents, within the age range of 18 to 30 years old This study uses quantitative methods and questionnaires as data collections tools. The data was then analyzed using SmartPLS with the Structural Equation Modelling approach. It is found that social media marketing activities positively influence consumer equity through brand equity in culinary brands. Customer equity is also indirectly affected by brand equity. Therefore, this research can be a basis for future research in social media marketing activities within the scope of culinary brands especially in the context of small-medium enterprises.
Virtual Hotel Operator (VHO) trend is growing rapidly, especially in Indonesia. Two of the most popular VHO in Indonesia are OYO and RedDoorz, both have been competing to attain the first position. Both OYO and RedDoorz have their own social media marketing strategies. For example, OYO persuades other conventional hotels to collaborate and use the OYO platform in their businesses. On the other hand, RedDoorz was recorded as the most visited Virtual Hotel Operator Platform in 2019, based on the data of Konsumen Jakpat 2019. OYO and RedDoorz also utilize social media to promote their services such as Instagram and Twitter. For advertising their businesses in social media, OYO and RedDoorz often use some social media influencers or known as influencer social media marketing. Influencers should be able to effectively deliver the messages and influence people’s decisions to use the products or services they advertise. This study aims to further explore the social media marketing strategy employed by OYO and RedDoorz. The results of Social Network Analysis by using “oyoindonesia” and ‘reddoorz’ as keywords in social media Twitter showed that RedDoorz has a bigger social network and more users involved in spreading their information than OYO. On the other hand, OYO's official account on Twitter is more efficient in performing its function as marketing media.
The internet and online space have created numerous platforms for users to communicate and interact, where each platform provides access to different sources of information. The purpose of the study was to investigate the online ideal self and its influence on brand attitude and attachment towards consumer purchase intention. A unique conceptual model was developed to test the proposed hypotheses of the study. Social media is one of the leading communication platforms that have emerged in the online space. Social media allows consumers and brands to interact in an informal manner from anywhere in the world. The study adopted a quantitative approach utilizing the survey method. Data was collected from 300 consumers. The data was then processed in SPSS 24 for descriptive statistics and AMOS 24 for hypotheses testing. A key finding suggests that social media consumers’ attachment is considerably dependent on their attitudes towards those brands. Brands can use social media to receive real-time feedback from customers as well as track this feedback. Implications emerged from the findings and further research direction is proposed.
This study aims to analyze the influence of elements of social media marketing activity on consumer engagement and brand knowledge including brand awareness and image. This study used a quantitative method and purposive sampling technique on 250 respondents. The research was conducted on all Indonesian citizens who use social media WhatsApp, Facebook, Instagram, youtube, and TikTok regarding the culinary business of celebrities and YouTubers in Indonesia. The method used is the Structural Equation Model with AMOS 24.0 Software. The results of this study indicate that the interaction variables, trends, and EWOM have a positive and significant effect on consumer engagement, and consumer engagement has a positive and significant effect on brand awareness and brand image. While the entertainment and customization variables have no significant effect on consumer engagement.
As a result of exponential growth in the popularity of blogging, travel blogs have demonstrated their enormous marketing potential, and have become an increasingly important mechanism for exchanging information among tourists. The present study modeled online social support and perceived value as antecedents of the impacts of influential travel bloggers on their blog members’ travel-related behavioral intentions, and examined the mediating role of sense of virtual community (SOVC) among these relationships. The analysis results herein demonstrate that online social support, perceived value, and SOVC relate significantly to blog members’ behavior intention. Furthermore, the influence of perceived value and SOVC on behavior intention are both respectively significant. With SOVC as a mediating variable, the CI indirect effect of the perceived value on travel intention did not include 0, indicating an indirect relationship between these two variables. Referring to perceived values, the findings indicates that blog members perceive the influential travel blogs as offering epistemic value more than others. These findings have theoretical implications for social media and online interaction related literature, and have critical business implications for customer to customer (C2C) marketers to distinguish themselves within the expanding number of influential travel blogs.
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 |