Social cognitive career theory and higher education students’ entrepreneurial intention: The role of perceived educational support and perceived entrepreneurial opportunity
Bibliographic record
Abstract
PURPOSE: This study aims to integrate insights from the Socio-Cognitive Career Theory (SCCT) and entrepreneurship literature to develop a research framework of how perceived entrepreneurial opportunities (PEO) and perceived educational support (PES) shape the progression of entrepreneurial self-efficacy (ESE) and entrepreneurial career interests (ECI). Additionally, this study investigates whether ECI mediates the effects of PEO and PES on entrepreneurial intention (EI) and how PEO and PES moderate the effects of ESE and ECI on EI. METHODOLOGY: A sample of 888 university students was recruited from Vietnam. Cronbach’s alpha and confirmatory factor analyses were adopted to test the reliability and validity of the scales. Structural equation modeling (SEM) is then used to test formulated hypotheses. FINDINGS: The current study demonstrates that ESE and ECI directly trigger EI. Although PES and PEO did not directly impact EI, their influence on EI was mediated through ESE and ECI. In addition, PEO was found to act as a positive catalyst for the transformation of ESE and ECI into EI. The greater the entrepreneurial opportunities students perceive, the more likely they are to convert ESE and ECI into intentions to become entrepreneurs. IMPLICATIONS: This study makes a significant contribution by emphasizing the relevance of the SCCT framework in understanding entrepreneurship and brings to the forefront the role of PES and PEO in shaping the progression of ESE, ECI and, ultimately, EI. In addition, the findings of this study provide practical implications for nascent entrepreneurs, entrepreneurship educators, and policymakers. ORIGINALITY AND VALUE: This study is one of the first to investigate the role of PEO and PES in the development of Vietnamese students’ SES, ECI and, ultimately, their intention to engage in entrepreneurship.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".