Does top management team responsible leadership help employees go green? The role of green human resource management and environmental felt‐responsibility
Bibliographic record
Abstract
Abstract Drawing on social information processing theory, the current study investigates the relationship between top management team (TMT) responsible leadership and employee organizational citizenship behavior for the environment (OCBE) from a vertical perspective, and whether green human resource management (GHRM) and employee environmental felt‐responsibility can play a sequential mediating role between them. Totally, 102 middle‐level managers and 527 employees in 102 Chinese teams voluntarily participated in our study. Drawing on above data, our study verifies that TMT responsible leadership was positively associated with both GHRM and employee environmental felt‐responsibility. In addition, GHRM mediated the positive effects of TMT responsible leadership and employee environmental felt‐responsibility. Also, GHRM can further promote employee OCBE through employee environmental felt‐responsibility. Overall, the positive relationship between TMT responsible leadership and employee OCBE was sequentially mediated by GHRM and employee environmental felt‐responsibility. Therefore, the current study shows the way to achieve corporate environmental sustainability strategy.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".