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: 22 / 22 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.
22 / 22 with data · 0 missing or unmatched. Percentages use all 22 selected publications.
22 / 22 with data · 0 missing or unmatched. Percentages use all 22 selected publications.
22 / 22 with data · 0 missing or unmatched. Percentages use all 22 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 2 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | 23 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 28 | 6 | 6/6 | 6/6 |
| 2024 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 13 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | 46 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 56 | 6 | 6/6 | 6/6 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
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 22 / 22 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): 2026-10-21T07:22:45.269847+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 | 22 | 22/22 |
| 2018 | All selected publications | 0 | 22 | 22/22 |
| 2019 | All selected publications | 0 | 22 | 22/22 |
| 2020 | All selected publications | 1 | 22 | 22/22 |
| 2021 | All selected publications | 1 | 22 | 22/22 |
| 2022 | All selected publications | 6 | 22 | 22/22 |
| 2023 | All selected publications | 38 | 22 | 22/22 |
| 2024 | All selected publications | 36 | 22 | 22/22 |
| 2025 | All selected publications | 31 | 22 | 22/22 |
| 2026 | All selected publications | 15 | 22 | 22/22 |
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 |
|---|---|
| 2019 | 1 |
| 2021 | 4 |
| 2022 | 7 |
| 2023 | 6 |
| 2024 | 3 |
| 2025 | 1 |
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 | 4 | 4 | 10 | 4/4 | 1.0 | 1.0 | 75.0 | 4/4 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 0 | 2 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 16 | 54 | 116 | 16/16 | 3.38 | 1.5 | 68.8 | 16/16 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to explain the effect of product knowledge, brand image, e-WOM on purchase intentions for edtech products in Indonesia. Data were obtained using a closed questionnaire involving 230 respondents, from Indonesians who know about edtech startup products and are between 18 and 35 years old. The sampling technique used was convenience sampling. The analysis technique used is Structural Equation Modeling (SEM) and uses the help of the AMOS version 24 program. The results show that 1) product knowledge has a positive but not significant effect on purchase intention, 2) product knowledge and brand image have a positive and significant effect on e-commerce WOM, 3) brand image and e-WOM have a positive and significant effect on purchase intention. It was also found that e-WOM functions as a mediator variable from the effect of product knowledge and brand image on purchase intention. The effect of the e-WOM mediator is stronger than the direct effect of brand image on purchase intention.
Nowadays online shopping industry is growing rapidly, and social media platforms are a major part of promotional activities for many companies in Indonesia. The research aims to examine the relationship between price perception, brand image and digital marketing variables and purchase intention and brand loyalty. Design research is a quantitative research using a survey method with a questionnaire; the sampling technique is purposive random sampling. Using a structural equation modeling approach with AMOS software and 303 respondents, results show that price perception corporate image, and digital marketing promotion activities have significant and positive effects on purchase intention, while brand image does not directly have a significant effect on purchase intention. Furthermore, purchase intention has a significant effect on brand loyalty.
Along with the increasing demand for qualified skincare products these days, there are many companies in Indonesia that produce facial beauty products that emphasize a good image in the minds of the consumers and intensive promotion. This study was conducted to determine whether the promotion, product quality, and brand image affect the purchase decisions. The research was conducted using a survey method using a questionnaire to a sample of 200 respondents who used Wardah Cosmetics beauty products. The sample was obtained by doing a purposive random sampling technique. The data analysis technique used in this research was using Structural Equation Modeling (SEM) using the AMOS program. The results of this study indicated that the promotion and the product quality had a significant effect on the brand image and brand image has a significant effect on purchasing decisions.
The purpose of this study was to examine the effect of the source credibility of celebrity endorsers such as trustworthiness, expertise, and attractiveness) on brand attitudes and purchase intentions for endorsed brands. The type of sampling used is purposive sampling with a total of 300 respondents. The analytical method used is the Structural Equation Modeling (SEM) method using Smart PLS (Partial Least Square) software. This study finds that the trustworthiness, expertise, and attractiveness of a celebrity endorser have a positive and significant effect on brand attitude and purchase intention. This shows that the better the trustworthiness, expertise, and attractiveness of a celebrity endorser, the better the consumer's positive attitude towards the brand (brand credibility). Furthermore, the better the consumer's positive attitude towards the brand (brand credibility), the higher the purchase intention that arises from a consumer.
Transmart needs the right strategy to increase consumer desire to make repeat purchases at Transmart MX Mall Malang during the post-pandemic recovery period. Repurchase intention can be formed from a positive brand image and customer satisfaction. Consumer perception of price or price image positively influences repurchase intention. This research was built using Consumer Behaviour Theory. This study aimed to test and analyze store price and brand image's influence on repeat purchase intention mediated by consumer satisfaction at Transmart MX Mall Malang. This research uses Transmart MX Mall Malang as the research object. The results of this study indicate that there is an influence between store price image and consumer satisfaction. This study also shows an influence between store price image and repurchase intention. In addition, this study shows an influence between brand image and consumer satisfaction. There is an influence between brand image and repurchase intention. This study's results indicate an influence between store price image and repurchase intention through consumer satisfaction. Finally, this study's results indicate an influence between brand image and repurchase intention through consumer satisfaction.
This study aims to determine the influence of differentiation strategies, product quality, and price on purchasing decisions in Mataram coffee shops. The type of research used in this research is quantitative research. Meanwhile, the data used in this study is primary data obtained from respondents' answers to the questionnaire to be shared. The sampling method uses the accidental sampling method. The population in this study is visitors to Mataram coffee shops every day. The sample in this study was 75 respondents. The data analysis in this study used multiple linear regression using validity test, reliability test, multiple linear regression analysis test and t hypothesis test and determination coefficient test with the SPSS 26 For Windows statistical application program. The results of this study show that differentiation strategies, product quality, and price have a positive and significant effect on consumer purchasing decisions. Mataram coffee shop management should improve marketing strategies in the form of more competitive prices, good product quality, and innovative differentiation strategies in an effort to improve purchase decisions. By implementing the right differentiation strategy in mataram coffee shops. By implementing the right differentiation strategy, Mataram coffee shops can increase the attractiveness of their products, attract new customers, and build long-term loyalty. Therefore, differentiation remains an element that needs to be strengthened to strengthen the business position in the midst of fierce competition.
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 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 light of the challenges faced by Indonesia's film industry, such as limited screens, the dominance of major production houses, and low purchase intentions among local film viewers, this research aims to address the critical gaps in understanding viewer behaviour. By exploring the intricate relationships between purchase intention, e-WOM, perceived value, marketing mix, and brand equity, the study offers valuable insights and effective marketing strategies essential for the sustainable growth of the Indonesian film market. This research used quantitative research methods. A total of 255 respondents were collected using random sampling. Data were analyzed using Structural Equation Modelling through SmartPLS. The main findings of the study demonstrate that (i) marketing mix does not influence purchase intention, (ii) marketing mix influence on purchase intention is mediated by perceived value, (iii) brand equity influences purchase intention, (iv) brand equity influences on purchase intention is mediated by perceived value, (v) perceived value influences purchase intention and finally (vi) perceived value influences on purchase intention are moderated by e-WOM.
This research aims to see to how far extent the user interface and user experience an impact on consumer have purchasing decisions through E-Impulse Buying. The correspondents of this study were IKIP PGRI Samarinda students who were active in online purchases through the Shopee application with a usage time of 0-6 years and between 18-24 years of age. The total sample is 131 respondents using purposive sampling method. Research data comes from questionnaires distributed using Google Forms or Manually. The data analysis technique uses path analysis through the SPSS 22 program. The results found show that the user interface and user experience have an impact on purchasing decisions directly, the user interface has an impact on purchasing decisions through E-Impulse Buying, and User Experience has no Impact on decisions purchase through E-Impulse Buying.
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 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |