Break up or tolerate? The post-disruption cooperation in global supply chains
Bibliographic record
Abstract
Due to globalisation and outsourcing, a manufacturer may suffer supply disruptions from the overseas supplier whose capacity is impaired by unruly events such as pandemic and geopolitical tensions. Since the recovery process of the overseas supplier’s capacity after the disruption is unpredictable, the manufacturer faces a choice of whether to continue cooperation or to shift to localised procurement. This paper first explores the effects of disruptions on the global supply chain, then considers the option to order from local suppliers. The results reveal that the overseas supplier whose capacity is affected by disruption at various degrees would take different actions, including raising the wholesale price, disguising its capacity impaired, or passing up the opportunity to cooperate with the manufacturer. In addition, we propose a tolerating strategy for the manufacturer and provide a long-term insight into supplier selection. The results show that the tolerating strategy can foster cooperation and enhance supply chain visibility. Notably, we find that manufacturers serving large markets can benefit from allowing the overseas supplier to recover gradually. Moreover, we discuss the importance of flexibility in designing the tolerating strategy.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".