Psychological Contract and Young Talent Retention in Vietnam: Development and Validation of a Hierarchical Reflective Structural Model
Bibliographic record
Abstract
This research investigates the relationship between relational psychological contract and the retention of young talents in Vietnam. The study surveyed young employees pertaining to (Generations Y and Z) at BBB Company. The results show an equal weight of transactional and relational psychological contracts in the job satisfaction and retention of young Vietnamese employees. The research compared the relative importance of future growth potential against existing good practices. The results indicate that these two constructs have equal importance, as the value for r square is almost equal. This suggests that from a strategic standpoint Human Resource Management (HRM) ought to prioritise the development of practices that enhance both relational and transactional psychological contracts among young talents in Vietnam. This derives from a cultural transition, which means that both the weights of national culture and globalisation are influencing the choices and loyalty of the younger generations in the workplace. These findings have significant implications for the understanding of how generational differences and culture influence how a company retains their young talents and the importance of psychological contract for young employee commitment in Vietnam in an increasingly competitive environment.
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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 | 0.013 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".