Green Workplace Culture and Employees’ Commitment: Overcoming Socioeconomic Challenges Towards Sustainable Development
Bibliographic record
Abstract
The increase in the awareness of sustainability practices in most companies and the intensity of the commitment of employees have made the workplace undergo noticeable changes in workplace socio-economic dynamics. This study explored the relationship between green work culture and the level of employee commitment in selected pharmaceutical companies in Nigeria, the most populous and largest consumer market in Africa. A total of 400 questionnaires were distributed, and 389 were returned and analyzed using the Pearson product moment correlation method. The results revealed a weak and negative relationship between green work culture and employee commitment within the pharmaceutical companies studied (R = -0.044, p > 0.05). The findings suggest that employees in these organizations demonstrated limited engagement with green work culture practices that could strengthen their commitment and socioeconomic levels. The study identified several factors contributing to this outcome, including inadequate physical and social parameters supporting green initiatives, poor cultural alignment, discouragement, and low employee motivation. These issues are further compounded by broader socioeconomic challenges that affect both organizational policies and individual attitudes toward sustainability. The study emphasizes the need for pharmaceutical organizations in Lagos State to reassess and enhance their green workplace strategies despite prevailing socioeconomic challenges. It recommends that both the physical and social work environments be redesigned to promote employee satisfaction and align with sustainable goals. Addressing socioeconomic challenges through improved incentives, supportive organizational culture, and inclusive workplace design can foster stronger employee commitment and create a more resilient, environmentally conscious workforce.
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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 | 0.001 | 0.002 |
| 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".