The Components of Entrepreneurial Orientation of Higher Education Student: A Systematic Literature Review
Bibliographic record
Abstract
The objective of this article is to synthesize the components of entrepreneurial orientation of higher education student using a systematic literature review methodology. Information was sought by searching the following electronic journal databases: 1) Eric (Education Resources Information Center), 2) Science Direct, 3) Scopus, and 4) Thai-Journal Citation Index Centre (TCI) covering publications from 2015 to 2023. The tool used in this systematic literature review consists of 3 parts: research screening form, critical appraisal form and data extraction table. Research selection is carried out by researchers and experts. Analyzing data by using descriptive statistics such as frequency, percentage, and summary analysis of content. The research results indicate that out of a total of 1,205 studies identified, only 13 met the criteria. The researchers selected the components of entrepreneurial orientation of higher education student level that occurred with a frequency of three or more, constituting 25 percent of the total frequency. In conclusion, the components of entrepreneurial orientation of higher education student consists of 5 elements, ranked from highest to least frequent, as follows: 1) Risk Taking, 2) Innovativeness, 3) Proactiveness, 4) Autonomy, and 5) Competitive Aggressiveness.
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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 | 0.023 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.024 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".