Green Human Resources Management on Business Performance: The Mediating Role of Green Product Innovation and Environmental Commitment
Bibliographic record
Abstract
This study aims to empirically examine and analyze the role of Green Human Resource Management (GHRM) and Environmental Management (EM) on Business Performance (BP) mediated by Green Product Innovation (GPI) and Environmental Commitment (EC). This study involved managers in creative industry companies in DKI Jakarta, Indonesia. From the survey conducted, the researchers obtained the research data from 275 questionnaires distributed. Then from all the data, there were 209 questionnaires that could be processed for further analysis. This study utilized the Structural Equation Model (SEM) analysis technique with PLS 23 software in the data testing process. This study has confirmed a number of findings including: Green Human Resource Management (GHRM) has a positive effect on Business Performance (BP); (2) Green Human Resource Management (GHRM) has a positive effect on Environmental Commitment (EC), (3) Green Human Resource Management (GHRM) has a positive effect on Green Product Innovation (GPI); (4) Environmental Commitment (EC) has a positive effect on Business Performance (BP); (5) Green Product Innovation (GPI) has a positive effect on Business Performance (BP); (6) Environmental Commitment (EC) mediates the effect of Green Human Resource Management (GHRM) on Business Performance (BP); (7) Green Product Innovation (GPI) mediates the effect of Green Human Resource Management (GHRM) on Business Performance (BP).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".