Mediation Effect of Knowledge Sharing Quality on Employee Creativity
Bibliographic record
Abstract
Employee creativity requires knowledge sharing, according to many experts. What aspects of the knowledge sharing cycle encourage employee creativity? In this study, authors examined three factors, i.e., ‘opportunity for exchange (OFE), value anticipation (VA), and motivation to engage (MTE)’, that influence the production of intellectual capital (as antecedents) and its effects on employee creativity (as outcomes) through knowledge sharing (KS) and quality of knowledge sharing (QKS: as mediating mechanism). To test the hypothesized relationships, Mplus was used to analyze 371 Russian IT employees. The findings suggest that OFE, VA and MTE are important antecedents of both KS and QKS. Moreover, KS and QKS mediates the relationship between antecedents (OFE, VA and MTE) and outcome variable (employee creativity). Theoretical contribution and future research are discussed.
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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 | 0.008 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".