Factors Influencing Innovation-Driven Entrepreneurship among Undergraduate Students in Private Universities: A Scoping Review
Bibliographic record
Abstract
This study presents a scoping review of factors influencing innovation-driven entrepreneurship among undergraduate students in private higher education institutions. Guided by the methodological framework of Arksey and O’Malley (2005) and the PRISMA-ScR reporting guidelines (Tricco et al., 2018), this review systematically synthesizes theoretical, conceptual, and empirical research published between 2013 and 2025. A total of fifty studies were identified through international and Thai databases, and nineteen were included in the final analysis after applying inclusion and exclusion criteria. The review identifies three key domains of variables: (1) independent variables—including personality traits, attitudes, and intentions toward entrepreneurship, external supports (family, culture, and institution), and experiential or innovation-oriented learning; (2) the mediating variable—innovative thinking ability; and (3) the dependent variable—entrepreneurial innovativeness. The findings reveal that innovative thinking ability mediates the relationship between individual and contextual factors and entrepreneurial innovativeness. The study contributes to both theory and practice by developing a conceptual framework that integrates individual-level, institutional, and environmental determinants of innovation-driven entrepreneurship. It also highlights the unique characteristics of private universities, where flexibility, autonomy, and market orientation create fertile ground for innovation-oriented entrepreneurial ecosystems. The paper concludes with implications for policy and higher education practice, recommending the strengthening of experiential learning opportunities, institutional support systems, and family-community engagement to enhance students’ innovative capacities and entrepreneurial outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".