Team reflexivity, individual intellectual capital and employee innovative behavior: a multilevel moderated mediation
Bibliographic record
Abstract
Purpose Based on experiential learning theory (ELT), this study explores the cross-level effect of team reflexivity on employee innovative behavior. The authors especially focus on the mediating effect of individual intellectual capital (IIC) and the moderating effect of empowering leadership on the relationship between the two constructs. Design/methodology/approach This study collects data from 76 work units, which include 362 employees and their direct supervisors. A cross-level moderated mediation model was tested by using multilevel path analysis. Findings The results show that team reflexivity significantly contributes to employee innovative behavior. IIC mediates the above relationship. Empowering leadership not only positively moderates the relationship between team reflexivity and IIC but also reinforces the linkage of team reflexivity → IIC → employee innovative behavior. Practical implications The study suggests that organizations should invest more in promoting team reflexivity and empowering leadership in the workplace. Furthermore, managers should make members aware of the importance of IIC for employee innovative behavior. They need to make efforts to enhance IIC via internal communication channels or open discussions, which facilitate IIC and employee innovative behavior. Originality/value This research tests the relationship between team reflexivity and employee innovative behavior and identifies IIC as a key mediator that links team reflexivity to employee innovative behavior. It also highlights the moderating role of empowering leadership in the process.
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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".