Production-and-order strategy with demand information updating and uncertain spot price
Bibliographic record
Abstract
We study production-and-order strategy in a two-echelon supply chain consisting of a single manufacturer and a single retailer in which both market demand and spot price are uncertain. The retailer updates early demand information through observing new market signal during long production season. The retailer may order product before the demand is updated by signing wholesale price contract (called a contract order), or order from the manufacturer in spot market after the demand is updated (called a spot order). In a retailer-led Stackelberg game, we construct a two-stage dynamic decision model to derive the optimal equilibrium solutions for the production and order quantity under both contract order strategy and spot order strategy. We characterize the conditions under which demand information updating benefits or hurts the members and a win-win is achieved. In sharp contrast to the existing findings in that the retailer always prefers to order late until demand information is updated, we discover that the retailer may prefers to order early when the spot price uncertainty is above a certain threshold. Then, we design a single-side payment contract to stimulate the manufacturer to choose order mode satisfying the retailer’s preference.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".