The effects of operational, relational, and transformational e-HRM practices on HR service effectiveness: The mediating role of user training
Bibliographic record
Abstract
This study aims at investigating the effects of e-HRM (operational, relational, and transformational) practices on the effectiveness of human resource service through user training. A questionnaire was used to collect data from a sample consisting of HR staff in fifteen food firms. The results showed that the influence of operational e-HRM on the effectiveness of human resource service was fully mediated by user training, and the influence of relational e-HRM on the effectiveness of human resource service was partially mediated by user training. Further, it was found that transformation has an insignificant effect on HR service effectiveness. The study contributes to the literature through identifying the effects of operational, relational, and transformational e-HRM practices on the effectiveness of human resource service and therefore help filling such a gap in literature. In addition to providing HR managers with results, acknowledge the importance of user training to implement e-HRM effectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".