Exploring the Role of Governance Mechanisms in Promoting Sustainability Across Supply Chains
Bibliographic record
Abstract
Abstract This qualitative research delves into the intricate relationship between governance mechanisms and sustainability practices within supply chains. Employing a qualitative approach, the study aims to elucidate the nuanced ways in which various governance mechanisms influence and promote sustainability initiatives across supply chains. Drawing upon interviews, case studies, and literature reviews, the research uncovers multifaceted insights into the role of governance mechanisms in fostering sustainable practices, thereby contributing to a deeper understanding of sustainable supply chain management. The findings reveal the significance of regulatory frameworks, industry standards, collaborative initiatives, contractual arrangements, buyer-supplier relationships, organizational culture, and leadership in shaping sustainability outcomes within supply chains. Regulatory frameworks and industry standards provide the foundation for ensuring compliance with environmental, social, and ethical requirements, while collaborative governance mechanisms foster transparency, accountability, and collective action across supply chain networks. Buyer-supplier relationships and organizational culture play critical roles in driving innovation, capacity-building, and continuous improvement in sustainability performance. Overall, the research underscores the interconnectedness of governance mechanisms across different levels of analysis and emphasizes the need for a holistic and integrated approach to sustainable supply chain management. By recognizing and leveraging these interdependencies, stakeholders can develop more effective strategies for advancing sustainability goals and creating shared value for stakeholders within and beyond the supply chain.
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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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.000 | 0.003 |
| 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".