The Effect of Sourcing Policies on Suppliers’ Sustainable Practices
Why this work is in the frame
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Bibliographic record
Abstract
To meet the growing demand for sustainably produced products, firms must be able to source sustainably produced parts from their suppliers. In this study, we analyze how a buyer (manufacturer or retailer) can use sourcing policies to influence their suppliers to adopt sustainable processes that can meet certain sustainability criteria. We study two sustainable sourcing policies commonly observed in practice, which influence suppliers’ process decisions by committing to offer sustainable products. Under a Sustainable Preferred policy, a buyer commits to offering a sustainable product if she can source sustainably produced parts from the supplier, but will otherwise offer a conventional product. In contrast, under a Sustainable Required sourcing policy, a buyer will only offer a sustainable product, and therefore will only source from the supplier if he has adopted a sustainable process. Our results offer insights for managers by identifying how these sustainable sourcing policies influence upstream suppliers to switch to a sustainable process, and how this affects the ability of a downstream buyer to offer a sustainable product. We find that when the buyer sources from a sole supplier, the Preferred policy can deter the supplier from switching as compared to when the buyer remains noncommittal. However, only the Required policy can induce the supplier to switch. In contrast, when a buyer has multiple suppliers, the Preferred policy does not deter the supplier, but can induce him to switch to a sustainable process, similar to the Required policy. Accordingly, our results suggest that to induce the supplier to switch to a sustainable process, a buyer should adopt a Required policy when sourcing from a sole supplier, but utilize a Preferred policy when there are multiple suppliers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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 it