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: 5 / 5 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 — 23 Oct 2026 01:19 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 12 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 14 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 15 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 30 | 3 | 3/3 | 3/3 |
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 5 / 5 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): 2026-10-21T07:22:48.100220+00:00 — 2026-10-23T01:19:55.693376+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 0 | 5 | 5/5 |
| 2023 | All selected publications | 12 | 5 | 5/5 |
| 2024 | All selected publications | 13 | 5 | 5/5 |
| 2025 | All selected publications | 15 | 5 | 5/5 |
| 2026 | All selected publications | 5 | 5 | 5/5 |
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 |
|---|---|
| 2022 | 2 |
| 2023 | 3 |
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 Research in Business and Social Science SSBFNET | 5 | 26 | 45 | 5/5 | 5.2 | 5 | 80.0 | 5/5 · 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.
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.
Technological developments and pandemic conditions that limit people's movement have triggered an increase in the use of online shopping platforms. Therefore, it is necessary to analyze in more depth the factors that increase online purchase intention. This study aims to analyze the effect of website quality on EWOM and the effect of EWOM and receiver perspective on consumer satisfaction and brand image. An analysis was also conducted on the influence of satisfaction and brand image on online purchase intention. This research is a quantitative study using primary data from distributing questionnaires to 250 online shopping platform consumers. The data in this study were then analyzed using the SEM (Structural Equation Model) method with AMOS 24 software. The results of this study indicate that website quality has a significant effect on EWOM. Furthermore, the receiver perspective and EWOM have a significant effect on consumer satisfaction and brand image. Consumer satisfaction and brand image have a significant effect on online purchase intention.
This study aims to research healthy foods utilizing the theory of reasoned action and including factors such as social and emotional value. The idea of research study is to determine whether there is a positive relationship between social values attitude and subjective norms, emotional values toward subjective norms and attitude, attitude toward buy intention, and subjective norms toward purchase intention. This research used the quantitative approach and the program used in data processing to find findings from the data, AMOS SEM. The population consists of people in Yogyakarta and Pekanbaru, with a non-probability sampling sample and a number of samplings of 303 respondents. The method employed for collecting data entails utilizing a questionnaire that has undergone rigorous testing to establish its validity and reliability. Finding shows that all hypothesis was accepted. It means there was a positive relationship for each variable toward healthy foods. The findings indicated that all the relationships between the hypotheses were positive, which could be evaluated based on the minimum score. If the value of C was larger than R and the accompanying P-value was less than 0.05 but more significant than 1.96, the association was declared positive.
Yogyakarta is one of the regions in Indonesia that has a fast-growing culinary industry. The growth in the number of restaurants present in Yogyakarta shows that the business sector has experienced growth. One of the food businesses that is taking part in feeling the tight competition today is the satay restaurants business. Satay is a traditional food that has a prominent level of popularity in Indonesia and even in the world. Yogyakarta already has the most variety of satay with a total of twenty-one types of satays and even every year it continues to grow. As a form of food business, this satay restaurant needs to have a competitive advantage to survive and win the business competition. One way to create a competitive advantage is to apply service quality, product quality, price, and innovation properly to satisfy customers. The study aims to decide the effect of service quality, product quality, price, and innovation on customer satisfaction at satay restaurants in Yogyakarta. The analytical method used in this study is Structural Equation Modeling (SEM) which was conducted with the help of SmartPLS software. The population in this study were all individual customers who had visited a satay restaurant in the province of Daerah Istimewa Yogyakarta with a total sample of 211 respondents. The result of the study shows that service quality, product quality, price, and innovation have a positive and significant impact on customer satisfaction at Satay restaurant in Yogyakarta.
Yogyakarta is one of the regions in Indonesia that has a fast-growing culinary industry. The growth in the number of restaurants present in Yogyakarta shows that the business sector has experienced growth. One of the food businesses that is taking part in feeling the tight competition today is the satay restaurants business. Satay is a traditional food that has a prominent level of popularity in Indonesia and even in the world. Yogyakarta already has the most variety of satay with a total of twenty-one types of satays and even every year it continues to grow. As a form of food business, this satay restaurant needs to have a competitive advantage to survive and win the business competition. One way to create a competitive advantage is to apply service quality, product quality, price, and innovation properly to satisfy customers. The study aims to decide the effect of service quality, product quality, price, and innovation on customer satisfaction at satay restaurants in Yogyakarta. The analytical method used in this study is Structural Equation Modeling (SEM) which was conducted with the help of SmartPLS software. The population in this study were all individual customers who had visited a satay restaurant in the province of Daerah Istimewa Yogyakarta with a total sample of 211 respondents. The result of the study shows that service quality, product quality, price, and innovation have a positive and significant impact on customer satisfaction at Satay restaurant in Yogyakarta.
This study aims to research healthy foods utilizing the theory of reasoned action and including factors such as social and emotional value. The idea of research study is to determine whether there is a positive relationship between social values attitude and subjective norms, emotional values toward subjective norms and attitude, attitude toward buy intention, and subjective norms toward purchase intention. This research used the quantitative approach and the program used in data processing to find findings from the data, AMOS SEM. The population consists of people in Yogyakarta and Pekanbaru, with a non-probability sampling sample and a number of samplings of 303 respondents. The method employed for collecting data entails utilizing a questionnaire that has undergone rigorous testing to establish its validity and reliability. Finding shows that all hypothesis was accepted. It means there was a positive relationship for each variable toward healthy foods. The findings indicated that all the relationships between the hypotheses were positive, which could be evaluated based on the minimum score. If the value of C was larger than R and the accompanying P-value was less than 0.05 but more significant than 1.96, the association was declared positive.
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.
Technological developments and pandemic conditions that limit people's movement have triggered an increase in the use of online shopping platforms. Therefore, it is necessary to analyze in more depth the factors that increase online purchase intention. This study aims to analyze the effect of website quality on EWOM and the effect of EWOM and receiver perspective on consumer satisfaction and brand image. An analysis was also conducted on the influence of satisfaction and brand image on online purchase intention. This research is a quantitative study using primary data from distributing questionnaires to 250 online shopping platform consumers. The data in this study were then analyzed using the SEM (Structural Equation Model) method with AMOS 24 software. The results of this study indicate that website quality has a significant effect on EWOM. Furthermore, the receiver perspective and EWOM have a significant effect on consumer satisfaction and brand image. Consumer satisfaction and brand image have a significant effect on online purchase intention.
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.
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 |