Striving to Implement Green Human Resource Management (GHRM) Policies and Practices: A Study from HR Managers Perspective (FMCG Sector)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this research is to explore the implementation of Green Human Resource Management practices and policies by the FMCG manufacturing companies of Pakistan. The researchers have enlightened various Green HRM strategies, initiatives, and practices that HR managers have undertaken in their respective organizations. Also, this research highlights the significance of Green HR practices and policies in employee retention, organizational citizenship behavior, and overall organizational image. This research is exploring the perception of Green HR from the HR professionals associated with FMCG companies of Karachi. For this purpose, in-depth interviews were taken by the HR managers of targeted companies to explore the implementation of HR practices and policies in Pakistan. The interview was conducted with the help of an interview protocol, consisting of various open-ended questions based on research objectives and research questions. The findings of this research suggest that the concept of Green HR practices and its benefits that an organization can gain by implementing such practices is vague among the HR professionals of Pakistan. The research has identified the need to train the managers regarding the Green HR initiatives and develop awareness campaigns which guide the managers about the significance that green practices have on the overall organizational performance and its image in the industry.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it