Investment Strategies in Supplier Development under Capacity and Demand Uncertainty
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Bibliographic record
Abstract
ABSTRACT We study joint investment by a buyer and a supplier in improving the supplier's capacity using a Stackelberg game model. We analyze both buyer‐led and supplier‐led situations. We show that in both cases the players have an opportunistic behavior toward investment. In the buyer‐led game, when the buyer finds the supplier motivated enough to invest, he avoids any direct contribution on capacity improvement. In this situation, the buyer follows an order inflation strategy to increase the investment of the supplier. However, when the supplier does not show the desire to make enough investment, the buyer will engage in direct investment in the supplier's capacity. We showed that although the order inflation strategy increases the buyer's optimal order quantity, it does not coordinate the supply chain. Also, in the case that the buyer is forced to share the investment costs with the supplier, he relies less on order inflation strategy. In the supplier‐led game, we demonstrated that the buyer has no motivation to use order inflation strategy. In the case that the supplier is the only investor, the buyer‐led game results in a higher profit for the buyer, supplier, and the supply chain. Finally, we looked at two extensions where the supplier is penalized for unsatisfied demand and the buyer uses an order‐postponement strategy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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