Green entrepreneurial intentions among university students in Chile: use of PLS-SEM
Bibliographic record
Abstract
The current study evaluated factors that explain green entrepreneurship intention (GEI) among 407 university students in Chile, who were presented with an online questionnaire.Thirty-nine questions evaluated their GEI, and the data was analysed using multivariate techniques.Results showed thatconcept development support (CDS), business development support (BDS) and academic training support (ATS) had a positive effect on institutional support (IS).Country support (CS) had a positive effect on self-efficacy (SE).IS did not have a positive effect on SE.Finally, SE had a positive effect on GEI.The model explained 25.3% of GEI.Bootstrapping led support to these results.The effects of CDS, BDS, ATS, CS and SE were positive and significant.Recognizing which factors have a significant effect can be useful to devise university programs aiming to enhance GEI among university students.The results of this paper may provide useful indications about future entrepreneurship and possibly suggest ways in which students' participation in private companies may create successful green products and services.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".