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: 27 / 27 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 12:56 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.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 selected publications.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 selected publications.
27 / 27 with data · 0 missing or unmatched. Percentages use all 27 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 |
|---|---|---|---|---|---|
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 12 | 12 | 12/12 | 12/12 |
| 2023 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 12 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 15 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 33 | 12 | 12/12 | 12/12 |
| 2023 | All selected publications | 11 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 5 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 25 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 44 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 26 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 65 | 12 | 12/12 | 12/12 |
| 2023 | All selected publications | 23 | 5 | 5/5 | 5/5 |
| 2024 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | 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 27 / 27 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): 2026-10-21T07:22:43.927206+00:00 — 2026-10-22T12:56:30.842375+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 | 27 | 27/27 |
| 2018 | All selected publications | 1 | 27 | 27/27 |
| 2019 | All selected publications | 1 | 27 | 27/27 |
| 2020 | All selected publications | 6 | 27 | 27/27 |
| 2021 | All selected publications | 13 | 27 | 27/27 |
| 2022 | All selected publications | 22 | 27 | 27/27 |
| 2023 | All selected publications | 48 | 27 | 27/27 |
| 2024 | All selected publications | 59 | 27 | 27/27 |
| 2025 | All selected publications | 25 | 27 | 27/27 |
| 2026 | All selected publications | 12 | 27 | 27/27 |
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 |
|---|---|
| 2015 | 1 |
| 2019 | 1 |
| 2020 | 2 |
| 2021 | 3 |
| 2022 | 12 |
| 2023 | 5 |
| 2024 | 2 |
| 2026 | 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 Finance & Banking Studies SSBFNET | 2 | 7 | 17 | 2/2 | 3.5 | 3.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 25 | 79 | 170 | 25/25 | 3.16 | 2 | 76.0 | 25/25 · 100.0% |
* Percentage among publications with a known citation count.
Communication and information technology have encouraged the use of e-learning systems in the education world. Even the application of the system has become a must in this COVID-19 pandemic health protocol. Nevertheless, it still needs to be observed, whether the consumers would keep using the e-learning system in the future. This study aims to see the effect of interaction variables and learner characteristic toward perceived usefulness and perceived satisfaction on e-learning system that has been used, with the effect of continuance intention toward the system in the future. To answer the purpose of this study, there is a research model has been developed which includes seven hypotheses. For the research object, the researcher chose non-government-owned colleges in Jakarta with the students as the sample chosen by purposive sampling technique. The result of this research shows those seven hypotheses accepted with the significant level at 1%, as well as 5%. It means each of the interaction variables and learning characteristics significantly direct and indirect influence the perceived satisfaction variable as well as the perceived usefulness variable. Moreover, it is proven that perceived usefulness is a significant determinant toward perceived satisfaction, even both of them significantly direct influence continuance intention at e-learning system that has been used.
The accelerated advancement in technology resulted to the appearance of Self Service Technology. One form of self-service technology in the banking sector is the presence of mobile banking. This study aims to examine the influence of five factors toward the reusing of Mobile Bank Central Asia (BCA) in Bandung. Those factors used in this study were the extension of Technology Acceptance Model (TAM) constructs, i.e perceived usefulness, perceived ease of use, perceived credibility, customer awareness and social influence. Data was collected through distributed questionnaire to 100 respondents who used Mobile BCA by using judgment sampling. Multiple linear regression technique was employed to investigate the influence among variables. This study empirically concluded that consumer intention to reuse BCA mobile services was positively influenced by social influence, customer awareness and perceived ease of use. On the other hand, perceived usefulness and perceived credibility did not influence the intention of reusing Mobile BCA in Bandung. Further study is suggested to use probability sampling technique to cover the real voice of mobile banking user in Bandung and to explore the lack influence of perceived usefulness and perceived credibility toward reusing of Mobile BCA.
E-commerce is one of the industries that are able to grow in the middle of the crisis because of the COVID-19 pandemic. This research aims to investigate the factors that influence the continuance intention of online shopping services in the scope of e-commerce. This research uses perceived ease of use as an independent variable that affects the intention with perceived usefulness and trust as mediating variables. This research is categorized as explanatory research. Respondents in this study are Klikindomaret users and the determination of the number of samples in this study using purposive sampling technique with a total sample of 170 respondents. The data collection method used a questionnaire and the data was analyzed using PLS-SEM. The findings of this study indicate that perceived ease of use, perceived usefulness, and trust have a significant effect on continuance intention. Perceived usefulness and trust also play a role in mediating the relationship between perceived ease of use and continuance intention.
This study aims to examine and prove empirically the effect of perceived usefulness, perceived ease of use, social influence, facilitating conditions on tax compliance. The sample selection technique uses convenience sampling obtained 100 samples taxpayers in Directorate General of Taxation III East Java. Data analyzed using partial least square. The result shows that (1) perceived ease of use does not affect tax compliance. (2) Perceived usefulness has a positive effect on tax compliance. (3) Social influence has a positive effect on tax compliance. (4) Facilitating conditions does not affect tax compliance.
This study aims to analyze the perceived ease of use, perceived usefulness, and perceived benefits on interest in using Bank Syariah Indonesia mobile banking. The research method used is a quantitative approach. The sample size for this study was 250 respondents. Data were analyzed by structural equation modeling (SEM) and processed with AMOS 24.0. The results of the SEM analysis show that perceived usefulness has a significant positive impact on attitudes toward mobile banking use. Perceived Ease of Use has a positive and significant effect on the Perceived Usefulness of mobile banking. Perceived ease of use has no significant effect on attitudes toward using mobile banking. Perceived Usefulness has a positive and significant effect on Behavioral Intention to Use mobile banking. Therefore, attitudes toward using mobile banking have a significant positive impact on behavioral intentions to use mobile banking.
The rapid growth of internet penetration and smartphone adoption has significantly accelerated the development of Subscription Video on Demand (SVOD) services in Indonesia, transforming the way consumers access digital entertainment. The increasing competition among streaming service providers has highlighted the importance of understanding the factors that influence users' continuance usage intention. In this paper, it is also aimed to examine the effects of Perceived Usefulness and Perceived Ease of Use on Continuance Usage Intention by extending the Technology Acceptance Model (TAM) and investigating the mediating roles of Trust and User Satisfaction among SVOD users in Indonesia. We employed a quantitative analytics method using a survey method, and the collected data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). A dataset of 180 respondents as active user of an SVOD platform through either an individual (private) subscription account or a shared subscription account has been analyzed in 2025. Main findings of the study demonstrate that (i) a satisfactory model fit with a Goodness-of-Fit (GoF) value of 0.659 and a Standardized Root Mean Square Residual (SRMR) of 0.054. (ii) The hypothesis testing results revealed that Perceived Usefulness, Perceived Ease of Use, Trust, and User Satisfaction had significant positive effects on Continuance Usage Intention., (iii). Perceived Usefulness and Perceived Ease of Use significantly influenced both Trust and User Satisfaction. (iii). The mediation analysis showed that Trust partially mediated the relationship between Perceived Usefulness and Continuance Usage Intention, whereas Trust did not mediate the relationship between Perceived Ease of Use and Continuance Usage Intention. User Satisfaction also did not exhibit a significant mediating effect.
In Indonesia, a QR code payment is referred to as QRIS (Quick Respond Code Indonesian Standard). QR code technology is employed by QRIS, a contemporary payment system, to establish connections between a variety of financial transactions. QRIS offers numerous advantages to businesses, including the ability to obtain numerous promotions, the automated recording of transactions, the ability to track financial income and expenses, and the elimination of the need to search for change. Regrettably, the low level of digital literacy in Indonesia has prevented certain individuals from adopting digital transactions. Consequently, policymakers and regulators will be able to make more informed decisions regarding the expansion of QRIS in Indonesia by gaining a more comprehensive understanding of the perceptions of utility and perceived ease of use among Indonesian users. This research involves individuals who have implemented QRIS. The sample size in this study was sufficient due to the use of PLS-SEM, a powerful multivariate analysis technique that is recognized for its statistical efficacy in small sample sizes. The study explores the behavioral intention to use QRIS among Indonesian users, emphasizing perceived usefulness and perceived ease of use while incorporating control variables such as age, experience, gender, income, and education. The analysis results indicate that perceived usefulness has a substantial impact on the behavior intention of QRIS, and perceived ease of use also has an impact on the behavior intention of using QRIS. Education and income were found to have no significant difference in relation to behavior intention of using QRIS, whereas age, experience, gender, and age were associated with a significant difference.
The number of digital banks in Indonesia is very large, resulting in intense competition between each digital bank. The tighter competition for digital banks, makes the interest in reusing digital bank users low and makes users tend to switch brands or providers in using digital banks. This study aims to determine the factors that influence e-servicescape on continuance intention mediated by brand image and performance expectancy. This research is categorized as explanatory research. Respondents in this study were users of the Blu by BCA Digital application on the island of Java, determining the number of samples in this study using purposive sampling technique with a total sample size of 249 respondents. The data collection method used a questionnaire, the data was analyzed using PLS-SEM. The results showed that e-servicescape had no significant effect on continuance intention. E-servicescape has a significant effect on brand image, brand image has a significant effect on continuance intention. E-servicescape has a significant effect on performance expectancy, performance expectancy has a significant effect on continuance intention. Brand image and performance expectancy can play a fully mediating role in the relationship between e-servicescape and continuance intention. Although e-servicescape does not have a significant influence directly, it is still part of the customer experience in using the Blu by BCA Digital app. Therefore, Blu by BCA Digital should continue to invest in technology and innovation to improve their e-servicescape. This includes the use of the latest technologies such as artificial intelligence (AI), data analytics, and personalized user experience. The better the e-servicescape, the better the brand image, performance expectancy and continuance intention of customers to keep using the service.
The aim of this study in general is to examine the influence of perceived ease of use, perceived usefulness, and perceived risk on intention to use. The subject of this study is the account officer of the big data user of a state-owned company in Malang, East Java, Indonesia. Specifically, this research has the purpose of finding out both the simultaneous and partial influence of perceived use, perceived usefulness, and perceived risk on the intention to use the big data of State-Owned Bank customers. This study is a survey employing both quantitative and qualitative data analysis. The samples of the subjects used were 95 account officers of a state-owned bank in East Java who used customer big data. The analysis conducted in this study included multiple linear regression testing and hypothesis testing for both simultaneous and partial The result of the F testing indicates that collectively, the perceived ease of use, perceived usefulness, and perceived risk variables have a simultaneous and positive influence on the intention to use the customer's big data. However, based on the T-test, it was observed that perceived usefulness is the only variable that has a partial influence on the intention to use the big data of the customers. While the other two variables, perceived ease of use and perceived risk, were found to have no significant influence on the intention to use the bank’s customers' big data.
This study aims to analyze the perceived ease of use, perceived usefulness, and perceived benefits on interest in using Bank Syariah Indonesia mobile banking. The research method used is a quantitative approach. The sample size for this study was 250 respondents. Data were analyzed by structural equation modeling (SEM) and processed with AMOS 24.0. The results of the SEM analysis show that perceived usefulness has a significant positive impact on attitudes toward mobile banking use. Perceived Ease of Use has a positive and significant effect on the Perceived Usefulness of mobile banking. Perceived ease of use has no significant effect on attitudes toward using mobile banking. Perceived Usefulness has a positive and significant effect on Behavioral Intention to Use mobile banking. Therefore, attitudes toward using mobile banking have a significant positive impact on behavioral intentions to use mobile banking.
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 |