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: 12 / 12 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 02:30 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.
12 / 12 with data · 0 missing or unmatched. Percentages use all 12 selected publications.
12 / 12 with data · 0 missing or unmatched. Percentages use all 12 selected publications.
12 / 12 with data · 0 missing or unmatched. Percentages use all 12 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 |
|---|---|---|---|---|---|
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 19 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 33 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 14 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 6 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 11 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 1 | 2 | 2/2 | 2/2 |
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 12 / 12 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): 2026-10-21T07:22:45.242361+00:00 — 2026-10-22T02:30:22.221062+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 | 12 | 12/12 |
| 2018 | All selected publications | 0 | 12 | 12/12 |
| 2019 | All selected publications | 1 | 12 | 12/12 |
| 2020 | All selected publications | 5 | 12 | 12/12 |
| 2021 | All selected publications | 3 | 12 | 12/12 |
| 2022 | All selected publications | 9 | 12 | 12/12 |
| 2023 | All selected publications | 10 | 12 | 12/12 |
| 2024 | All selected publications | 15 | 12 | 12/12 |
| 2025 | All selected publications | 17 | 12 | 12/12 |
| 2026 | All selected publications | 8 | 12 | 12/12 |
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 |
|---|---|
| 2018 | 1 |
| 2019 | 2 |
| 2020 | 2 |
| 2021 | 2 |
| 2022 | 1 |
| 2023 | 2 |
| 2024 | 2 |
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 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 1 | 4 | 5 | 1/1 | 4.0 | 4 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 10 | 37 | 63 | 10/10 | 3.7 | 2.5 | 70.0 | 10/10 · 100.0% |
* Percentage among publications with a known citation count.
Social entrepreneurship is a potential alternative to address social problems but social business still needs to be strengthened to provide far-reaching impact. One strategy to flourish is benchmarking against successful social enterpreneurs because previous studies show that entrepreneur’s competence is a determinant of small-medium business performance and growth. Social entrepreneur competencies which drive social business success and how these competencies are developed, unfortunately have not clear yet. This study aims to build a competency model for social entrepreneurs and to find out pattern (in method, period, sources) for developing competencies by studying successful Indonesian social entrepreneurs. The reports on social entrepreneur competency model presented in this paper. This research adopt qualitative approach using multiple case study design. Data collected by indepth interviewing 29 informants, studying documents and conducting field observation in eight cities. Results show that successful social entrepreneurs have shared competencies which indicate existence of social entrepreneur competency model. The result of this study complements empirical studies in social entrepreneurs’ competencies by showing competencies that drive success of social business i.e: Achievement orientation, Persistence, Initiative, Courage to take opportunities, Networking, Influencing others, Team leadership, Developing others, Teamwork-Colaboration, Orientation to help and serve others, Mission orientation, Affiliate interest, Creative problem solving. The finding has direct implication on social entrepreneur education and development programs included method, materials, design and sources of development because the competencies determine the success constitute mostly of attitudes, motives and traits instead of knowledge and skills.
This research was conducted to explore the factors predicting the Entrepreneurial Intention among female entrepreneurs in the Balinese tourism industry. The theory of planned behaviour (TPB) framework was utilised as the mediating variables, while Exposure to Role Models, Psychological Characteristics, Entrepreneurship Education, and Access to Financial Capital are used as the exogenous variables. This study used a quantitative method by employing the Likert scale for the questionnaires with a total of 352 respondents and analysed using the Structural Equation Modelling (SEM). This study found that Psychological Characteristics and Entrepreneurship Education had an indirect influence on Entrepreneurial Intention through the mediating variables of Personal Attitude and Perceived Behavioural Control. Access to Financial Capital was also found to have an indirect influence on Entrepreneurial Intention with the Perceived Behavioural Control as the mediating variable
The study analyzed whether family influence, gender, and entrepreneurial education would influence vocational students’ desire to become entrepreneurs. A survey was conducted in 6 vocational schools in Tasikmalaya, West Java, involving 246 vocational students. Using multiple regression analysis, findings show that entrepreneurial education has the highest influence (57.5%) shaping entrepreneurial intention among vocational students, while gender account for 30% influence on students’ entrepreneurial intention. Male and female students believed that they must be given the same opportunities for entrepreneurship, yet there are feminine and masculine attributes that differentiate successful entrepreneurial plans between genders. Lastly, findings show that family background has the least influence (16%) on entrepreneurial intentions. Respondents disclosed that there are many choices open to them aside from being entrepreneurs, and they would opt for this choice instead of following their parents. Nevertheless, they believe in family support through advice and access to capital. Implications for research, policy, and practice are discussed. This study has shown evidence that entrepreneurship can be a solution to Indonesia’s high unemployment problem for young vocational students, but this entails better entrepreneurial education, the provision of gender-equal opportunities for males and female students, and enhanced family support for entrepreneurial ventures.
As one of the essential elements of the country's current economic development, Indonesia's government still supports entrepreneurial endeavors. Young entrepreneurs can only be developed with the help of universities. Students' entrepreneurial attitudes are anticipated to be shaped through the practical entrepreneurship program. As a foundation for student preparation to engage in entrepreneurial activity, this study investigates entrepreneurial intention. Students' entrepreneurial intents in Jakarta will be compared to three factors, including attitudes, subjective norms, and perceived behavioral control, that are based on the Theory Planned of Behavior. Purposive sampling was used to sample 120 students. Through the use of partial least squares structural equation modeling (PLS-SEM), variance-based SEM was employed to analyze the data. All variables are reliable and legitimate, according to the test results. The study's key conclusions show that while subjective norms have a minimal impact on entrepreneurial intention, attitude and perceived behavioral control have a positive and considerable impact. Entrepreneurial intent is also recognized to have a favorable and significant impact on readiness to launch a firm. The study's findings could be incorporated into entrepreneurship curricula at colleges to help the government's attempts to accomplish development objectives through entrepreneurial endeavors.
Technological developments and innovation create challenges for businesses to develop sustainable innovations in the light of global shifts in social, environmental and economic conditions in order to advance or maintain their position. Digital startups are an alternative for businesses to create value, and in the long term improve a country's economy. Entrepreneurial ecosystem theory is widely used to research digital startup ecosystems, but the factors in the model have not been tested quantitatively in terms of their effect on productive entrepreneurship. This study is a quantitative study by embarrassingly distributing the survey to 120 respondents who are founders and C-level at digital start-ups in Indonesia. Regression analysis using SPSS was carried out to see the correlation between variables. The results of this study explain that networking, leadership, finance, human resources and knowledge have an influence on productive entrepreneurship in the startup and digital ecosystem in Indonesia.
This research aims to determine whether a top cosmetic company’s Beauty for Better Life Women's Empowerment Program (BFBL – WEP) has encouraged women to become entrepreneurs in the micro, small, and medium enterprises (MSME) sector, and identify the various obstacles and challenges they face in navigating their entrepreneurship journey. Launched by the L'Oréal Foundation in 2009 in 27 countries including Indonesia, the BFBL Program believes that a program like this will play a central role in helping vulnerable, underprivileged, or marginalized women regain their self-esteem, develop self-confidence and enhance their well-being. Using a qualitative research design with primary data collected through semi-structured interviews of thirteen (13) female beneficiaries of the Program, the research covered six (6) regions in Indonesia. Additional data was obtained from two (2) more key informants representing the Head of the BFBL Program in L’Oreal Indonesia and a beauty coach. Interviews were done through hybrid methods of offline and online engagements with respondents, enabling reach as well as convenience as the respondents came from different regions across the country. Findings show that the BFBL produces successful women MSME entrepreneurs through a) training in the planning and design of beauty services; b) resource support provides mentoring and coaching, and c) marketing support skills through social media promotion, creating a business portfolio, and learning ethical practices in dealing with clients. Geographical challenges in program implementation as well as logistical capabilities of participants were detected. Implications to organizational practices related to women’s entrepreneurship promotion are presented.
This research investigates the factors influencing the transition from entrepreneurial intention to actual entrepreneurial activity among college graduates, focusing on the role of strategic thinking as a determinant of entrepreneurial behavior. Additionally, the study seeks to broaden understanding beyond entrepreneurial intention by incorporating strategic thinking variables as moderators in examining the causal relationships between entrepreneurial activity and its antecedents. The sampling method used in this study was nonprobability sampling. 142 respondents were collected and analyzed using Partial Least Square through SmartPLS. The main findings of the study demonstrate that (i) attitude, subjective norm, and perceived behavioral control significantly affect entrepreneurial intention (ii)attitude, subjective norm, and perceived behavioral control do not significantly affect entrepreneurial activity, (iii) entrepreneurial intention does not significantly affect entrepreneurial activity, (iv) the effect of attitude, subjective norm and perceived behavioral control toward entrepreneurial activity does not mediated by entrepreneurial intention, (v) strategic thinking does not moderate the effect of attitude, subjective norm and perceived behavioral control towards entrepreneurial activity, (vi) strategic thinking significantly affects entrepreneurial activity. The study brought several implications related to the predictors of entrepreneurial activity and the integration of strategic thinking into the theory of planned behavior model.
Technological developments and innovation create challenges for businesses to develop sustainable innovations in the light of global shifts in social, environmental and economic conditions in order to advance or maintain their position. Digital startups are an alternative for businesses to create value, and in the long term improve a country's economy. Entrepreneurial ecosystem theory is widely used to research digital startup ecosystems, but the factors in the model have not been tested quantitatively in terms of their effect on productive entrepreneurship. This study is a quantitative study by embarrassingly distributing the survey to 120 respondents who are founders and C-level at digital start-ups in Indonesia. Regression analysis using SPSS was carried out to see the correlation between variables. The results of this study explain that networking, leadership, finance, human resources and knowledge have an influence on productive entrepreneurship in the startup and digital ecosystem in Indonesia.
As one of the essential elements of the country's current economic development, Indonesia's government still supports entrepreneurial endeavors. Young entrepreneurs can only be developed with the help of universities. Students' entrepreneurial attitudes are anticipated to be shaped through the practical entrepreneurship program. As a foundation for student preparation to engage in entrepreneurial activity, this study investigates entrepreneurial intention. Students' entrepreneurial intents in Jakarta will be compared to three factors, including attitudes, subjective norms, and perceived behavioral control, that are based on the Theory Planned of Behavior. Purposive sampling was used to sample 120 students. Through the use of partial least squares structural equation modeling (PLS-SEM), variance-based SEM was employed to analyze the data. All variables are reliable and legitimate, according to the test results. The study's key conclusions show that while subjective norms have a minimal impact on entrepreneurial intention, attitude and perceived behavioral control have a positive and considerable impact. Entrepreneurial intent is also recognized to have a favorable and significant impact on readiness to launch a firm. The study's findings could be incorporated into entrepreneurship curricula at colleges to help the government's attempts to accomplish development objectives through entrepreneurial endeavors.
Entrepreneurship is an innovative and creative process that can add value to products, create job opportunities, raise productivity, revitalize, and diversify markets, improve social welfare, and, more broadly, develop the economy. Entrepreneurship education encourages the founding of new businesses by students and alums and equips them with critical decision-making skills that enhance the success of graduates in the job market. That is why we seek to develop better entrepreneurs. Part of that is raising their intentions to start a business; another is making their intentions more realistic. To do both requires a deeper, richer understanding, and analysis of an entrepreneurial implementation intention in vocational education students is essential. In this study, researchers want to know what variables affect Entrepreneurial Implementation Intention in vocational education students at Universitas Padjadjaran. The results of this study found that Entrepreneurial Knowledge affects the main determinant of this research to encourage the increase of Entrepreneurial Implementation Intention.
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 |