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: 7 / 7 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 08:55 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.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 6 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 8 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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 7 / 7 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): 2026-10-21T07:22:52.679692+00:00 — 2026-10-22T08:55:38.270859+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 0 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 0 | 7 | 7/7 |
| 2022 | All selected publications | 0 | 7 | 7/7 |
| 2023 | All selected publications | 0 | 7 | 7/7 |
| 2024 | All selected publications | 0 | 7 | 7/7 |
| 2025 | All selected publications | 6 | 7 | 7/7 |
| 2026 | All selected publications | 2 | 7 | 7/7 |
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 |
|---|---|
| 2023 | 1 |
| 2024 | 3 |
| 2026 | 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 6 | 6 | 8 | 6/6 | 1.0 | 0.0 | 16.7 | 6/6 · 100.0% |
* Percentage among publications with a known citation count.
Partial Least Squares Structural Equation Modeling has gained considerable attention across diverse academic fields, including business, social sciences, marketing, and management. A key challenge in utilizing PLS-SEM is balancing explanatory and predictive power when selecting the most suitable model from competing alternatives. This paper explores the effectiveness of various quality criteria for evaluating causal-predictive models, with a focus on resistance to change in Vietnamese SMEs. The study emphasizes the importance of both in-sample and out-of-sample predictions, using metrics such as R², BIC, AIC, Q², RMSE, MAE, and CVPAT. The findings reveal that traditional criteria like R² may not be sufficient for identifying the best model, while PLSpredict, CVPAT, BIC, and AIC offer superior performance in determining the optimal balance between explanatory and predictive capabilities. These insights provide practical implications for researchers and practitioners, highlighting the need to tailor model selection to specific objectives, such as theory development or real-world forecasting. For practitioners, the study underscores the benefits of leveraging simpler, more generalizable models for robust decision-making in dynamic or resource-constrained environments.
This study investigates portfolio optimization within the Mean–Variance framework using alternative estimators for expected returns and risk. Based on daily data of VN30 stocks from March 2021 to December 2025, nine portfolio strategies are constructed by combining three return estimators (historical mean, CAPM, and Exponential Moving Average) with three risk estimators (sample covariance, Ledoit–Wolf shrinkage covariance, and semicovariance). Portfolios are optimized by maximizing the Sharpe ratio under realistic weight constraints and a post-optimization sparsification procedure to improve implementability. Empirical results indicate that portfolios using EMA-based expected returns combined with Ledoit–Wolf or semicovariance estimators deliver more stable and superior out-of-sample performance over 1-, 3-, and 6-month horizons. In contrast, strategies relying on historical mean returns with sample covariance suffer from severe performance degradation, while CAPM-based approaches underperform consistently. These findings underscore the importance of adaptive return estimation and robust risk modeling in emerging equity markets and offer timely implications for portfolio construction in Vietnam as it prepares for a potential upgrade to emerging market status.
Physical activity plays a crucial role in maintaining health and reducing stress, particularly among students in demanding disciplines such as nursing. This study examines how social media and self-efficacy influence exercise behavior and stress relief, drawing on the Social Cognitive Theory and Uses and Gratifications Theory. Data were collected from 295 Vietnamese undergraduate nursing students and analyzed using structural equation modeling (SEM). The results reveal that both social media use and self-efficacy significantly and positively affect stress relief, with exercise behavior acting as a mediating variable. The proposed model explains 69.2% of the variance in exercise behavior and 57.8% in stress relief. These findings suggest that exposure to fitness-related content and higher confidence in one’s ability to exercise contribute to greater engagement in physical activity and improved stress management. The study highlights the importance of integrating digital media and self-efficacy enhancement strategies into university health promotion programs. Universities should consider using social media platforms to share motivational content, facilitate online exercise communities, and organize student-led fitness initiatives. Policy-makers may also support campaigns promoting physical activity as an effective stress management strategy for health-related professions.
In recent years, increased understanding has led individuals to prioritize exercise for the purposes of sustaining health, achieving weight loss, preventing various diseases, and alleviating stress. This research aims to deepen our understanding of human exercise behavior by examining the factors that influence this trend. The writers utilize the framework of "Social Learning Theory" to elucidate the correlation among influencing factors, exercise behavior, and stress relief. This study details a survey that involved 323 participants, primarily Vietnamese college students with a focus on tourism. The analysis comprised 151 males and 172 females. This research employed structural equation modeling (SEM) for data analysis. The results showed that enabling circumstances and social impact have a positive impact on stress relief, with exercise activity playing a mediating role. The model accounts for 57.3% of the variance in exercise behavior and 57.1% in stress relief. Moreover, social impact has a direct favorable impact on students' stress relief. In conclusion, both enabling factors and social impact are associated with increased exercise activity. These characteristics increase the likelihood of students participating in exercise and reducing their academic stress. The study also that the institution introduces a course that combines academics with yoga and team sports to the general education curriculum. The institution should offer on-campus fitness or partner with local gyms. Finally, joining clubs and organizations might encourage university students to exercise.
This research aims to explore the recognized advantages of Communities of Practice (CoPs) in enhancing knowledge sharing and spurring organizational transformation. Despite their acknowledged importance, CoPs often receive inadequate attention or representation in numerous organizations, likely due to leaders' unfamiliarity or insufficient skills to manage such groups. This study introduces the "Real Option Perspective" as the recommended approach for top executives to understand and leverage CoPs. Initially, it clarifies the concepts of CoPs and the Real Option Perspective, highlighting their significance. These concepts then lay the groundwork for developing a management model for CoPs. The proposed management trajectory for CoPs involves five phases: Investment in CoPs, Recognition of Stagnation, Re-engagement with CoPs, Transition of Value, and finally, Dissolution and Feedback. This research seeks to expand the applicability of the Real Options framework in managing CoPs, providing leaders with strategic insights to fully realize the potential of CoPs in line with organizational objectives.
This study investigates portfolio optimization within the Mean–Variance framework using alternative estimators for expected returns and risk. Based on daily data of VN30 stocks from March 2021 to December 2025, nine portfolio strategies are constructed by combining three return estimators (historical mean, CAPM, and Exponential Moving Average) with three risk estimators (sample covariance, Ledoit–Wolf shrinkage covariance, and semicovariance). Portfolios are optimized by maximizing the Sharpe ratio under realistic weight constraints and a post-optimization sparsification procedure to improve implementability. Empirical results indicate that portfolios using EMA-based expected returns combined with Ledoit–Wolf or semicovariance estimators deliver more stable and superior out-of-sample performance over 1-, 3-, and 6-month horizons. In contrast, strategies relying on historical mean returns with sample covariance suffer from severe performance degradation, while CAPM-based approaches underperform consistently. These findings underscore the importance of adaptive return estimation and robust risk modeling in emerging equity markets and offer timely implications for portfolio construction in Vietnam as it prepares for a potential upgrade to emerging market status.
Physical activity plays a crucial role in maintaining health and reducing stress, particularly among students in demanding disciplines such as nursing. This study examines how social media and self-efficacy influence exercise behavior and stress relief, drawing on the Social Cognitive Theory and Uses and Gratifications Theory. Data were collected from 295 Vietnamese undergraduate nursing students and analyzed using structural equation modeling (SEM). The results reveal that both social media use and self-efficacy significantly and positively affect stress relief, with exercise behavior acting as a mediating variable. The proposed model explains 69.2% of the variance in exercise behavior and 57.8% in stress relief. These findings suggest that exposure to fitness-related content and higher confidence in one’s ability to exercise contribute to greater engagement in physical activity and improved stress management. The study highlights the importance of integrating digital media and self-efficacy enhancement strategies into university health promotion programs. Universities should consider using social media platforms to share motivational content, facilitate online exercise communities, and organize student-led fitness initiatives. Policy-makers may also support campaigns promoting physical activity as an effective stress management strategy for health-related professions.
Grounded in Conservation of Resources theory, this study examines how psychological capital influences organizational citizenship behavior among Vietnamese IT expatriates in Taiwan, focusing on the mediating role of cross-cultural adjustment and the moderating influence of cultural intelligence. Survey data from 500 participants were analyzed using PROCESS Macro and AMOS. The results show that hope, self-efficacy, and optimism significantly predict cross-cultural adjustment, whereas resilience does not. All psychological capital dimensions positively predict organizational citizenship behavior, and cross-cultural adjustment partially mediates these relationships, indicating that psychological resources promote discretionary behaviors more effectively when expatriates achieve cultural ease. Cultural intelligence significantly strengthens the psychological capital, cross-cultural adjustment link, with the strongest effects observed for self-efficacy and optimism, highlighting the importance of cultural capability in resource deployment. This study advances expatriate research by integrating psychological capital, cross-cultural adjustment, cultural intelligence, and organizational citizenship behavior into a unified model within an East Asian technology context. Practical implications include developing psychological capital-cultural intelligence training, enhancing intercultural onboarding practices, and supporting migrant professional networks to improve expatriate retention and performance.
Partial Least Squares Structural Equation Modeling has gained considerable attention across diverse academic fields, including business, social sciences, marketing, and management. A key challenge in utilizing PLS-SEM is balancing explanatory and predictive power when selecting the most suitable model from competing alternatives. This paper explores the effectiveness of various quality criteria for evaluating causal-predictive models, with a focus on resistance to change in Vietnamese SMEs. The study emphasizes the importance of both in-sample and out-of-sample predictions, using metrics such as R², BIC, AIC, Q², RMSE, MAE, and CVPAT. The findings reveal that traditional criteria like R² may not be sufficient for identifying the best model, while PLSpredict, CVPAT, BIC, and AIC offer superior performance in determining the optimal balance between explanatory and predictive capabilities. These insights provide practical implications for researchers and practitioners, highlighting the need to tailor model selection to specific objectives, such as theory development or real-world forecasting. For practitioners, the study underscores the benefits of leveraging simpler, more generalizable models for robust decision-making in dynamic or resource-constrained environments.
In recent years, increased understanding has led individuals to prioritize exercise for the purposes of sustaining health, achieving weight loss, preventing various diseases, and alleviating stress. This research aims to deepen our understanding of human exercise behavior by examining the factors that influence this trend. The writers utilize the framework of "Social Learning Theory" to elucidate the correlation among influencing factors, exercise behavior, and stress relief. This study details a survey that involved 323 participants, primarily Vietnamese college students with a focus on tourism. The analysis comprised 151 males and 172 females. This research employed structural equation modeling (SEM) for data analysis. The results showed that enabling circumstances and social impact have a positive impact on stress relief, with exercise activity playing a mediating role. The model accounts for 57.3% of the variance in exercise behavior and 57.1% in stress relief. Moreover, social impact has a direct favorable impact on students' stress relief. In conclusion, both enabling factors and social impact are associated with increased exercise activity. These characteristics increase the likelihood of students participating in exercise and reducing their academic stress. The study also that the institution introduces a course that combines academics with yoga and team sports to the general education curriculum. The institution should offer on-campus fitness or partner with local gyms. Finally, joining clubs and organizations might encourage university students to exercise.
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 |