Specific Antecedents of Entrepreneurial Intention Among Newly Returned Chinese International Students
Bibliographic record
Abstract
A growing group of Chinese students is returning to China following graduation, especially young returnees. This group is seen as one of the most innovative sectors of Chinese society. Based on the theory of planned behavior (TPB) and three kinds of capital theories, this study explores entrepreneurial intention (EI) and its influencing factors among Newly Returned Chinese International Students (NRCIS). A survey of 211 NRCIS showed a low level of EI and little knowledge of supporting policies about entrepreneurship. Influencing factors included culture harmony as culture capital, overseas social networks as social capital, and foreign entrepreneurship education and foreign language proficiency as human capital. Attitude mediated the effects of foreign language proficiency, culture harmony, and foreign entrepreneurship education on EI. Perceived behavior control mediated the effect of foreign language proficiency, Chinese language proficiency, culture harmony, foreign entrepreneurship education, domestic entrepreneurship education, and overseas social networks on EI, and subjective norms have no significant mediating effect in any mediation path. Based on these findings, policymakers could pay attention to examining whether the current policies are working and accessible for NRCIS, and domestic entrepreneurship education could keep cultivating students' cross-cultural communication and understanding abilities, and society and education sectors could encourage positive cognition of entrepreneurship and guide students to form a positive attitude toward entrepreneurship and enhance their confidence.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| 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".