The impact of individual and environmental characteristics on students’ entrepreneurial intention
Bibliographic record
Abstract
The primary objective of this study is to investigate the effects of personal attitude toward entrepreneurship, self-efficacy (individual characteristics) and social capital, country norms (environmental characteristics) on entrepreneurial intention among students at universities and colleges in Vietnam. By collecting data from 210 students in Vietnam, authors employ the quantitative approach such as certain descriptive statistics, explorative factor analysis (EFA), KMO and Bartlett test, correlation coefficient analysis, ANOVA test and multiple regression analysis to test hypothesizes. The study investigates the relationship between entrepreneurial attitude, self-efficacy, social capital, country norms and entrepreneurial intention. The result of this research indicates that a large proportion of students only study and only a small percentage of them study and run their own business. In terms of willingness to take the risks, the highest figure belongs to the neutral level. In addition, the correlation coefficient and multiple regressions analysis indicate that all four factors were positively associated with entrepreneurial intention. Specially, country norms are seen as the most influential factors on entrepreneurial intention, followed by social capital, personal attitude, and self-efficacy, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".