Supply chain short‐term financing for responsible production at small and medium‐sized enterprises
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
Companies have increasingly used supply chain financing instead of bank financing when engaging with financially constrained suppliers. We investigate the effectiveness of different financing mechanisms at supporting supply chain responsibility. We consider a decentralized supply chain where a buyer sources from a financially constrained supplier who borrows from either a bank or the buyer to finance his production. The buyer audits the supplier for responsibility compliance and will refuse to accept and pay for the order if the supplier fails the audit. We find that under conventional bank financing, the bank is concerned with the supplier's audit failure and will raise the interest rate. This not only hinders the supplier's compliance effort but also hurts the profitability of every stakeholder. In contrast, under buyer financing, the buyer may offer the supplier a low interest rate to motivate him to be more compliant when the supplier's collateral is of low value. However, if the supplier's collateral is of high value, the buyer may be tempted to set a high interest rate to exploit the supplier—leading to a reduction in supplier's compliance and supply chain profitability. Thus, we conclude that buyer (bank) financing is more preferable for encouraging responsibility when the supplier has low (high) collateral. Our findings suggest that buyer financing may not always be an effective approach for encouraging supply chain responsibility. As such, we propose an alternative mechanism under which the buyer offers a reward to the supplier if he passes the audit while the supplier continues to borrow from a bank. We prove that this combination of bank financing and buyer reward always improves the compliance level and in most cases increases the total supply chain profit. It is even more effective than buyer financing in encouraging responsibility especially when the supplier's collateral is of low value.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 it