Entrepreneurial intentions among university students: the role of mentoring, self-efficacy and motivation
Bibliographic record
Abstract
Purpose This research examines whether mentoring is a predictor of entrepreneurial intentions. It also explores how intent translates into action through implementation intentions. The study tests if the mentoring-intentions association is mediated by self-efficacy. The potential moderating effect of achievement motivation on the relationship was also investigated. Design/methodology/approach PLS-SEM was used to test the hypotheses of the 242 valid responses collected from final-year students from Libyan public universities. Findings Results show that self-efficacy partially mediated the mentoring-intentions association, while motivation negatively moderated the relationship. Entrepreneurial intentions had a significantly strong effect on implementation intentions. Research limitations/implications The results verify mentoring as a practical socializing instructional approach. Therefore, universities should implement structured mentoring programs, offering emotional guidance, counsel and networking opportunities. Also, mentors should undergo training, and progress tracking is essential for improvement. Originality/value Examining entrepreneurial self-efficacy as a mediator and achievement motivation as a moderator in the mentoring-intentions association is unprecedented. The findings narrow the search for antecedents to entrepreneurial intentions and pinpoint intervention points.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".