Joint Pricing-Production Decisions in Supply Chains of Complementary Products with Uncertain Demand
Bibliographic record
Abstract
Consider n manufacturers, each producing a different product and selling it to a market, either directly or through a common retailer. The n products are perfectly complementary in the sense that they are always sold and consumed jointly or in sets of one unit of each. Demand for the products during a selling season is both price sensitive and uncertain. Each of the n manufacturers faces the problem of choosing a production quantity and a selling price for his product. Two settings are considered, regarding the decision sequence of the n manufacturers: They are either simultaneous or sequential. The retailer, when present, employs a consignment-sales contract with revenue sharing to bind her relationship with the manufacturers and to extract profit for herself. Using a multiplicative demand model in this paper, we fully characterize individual firms’ decisions in equilibria, under each of the two game settings, and derive closed-form performance measures, both for the channel and for individual channel members. These closed-form solutions allow us to explore the effects of channel structure and parameters on firms’ decisions and performance that lead to conclusions of managerial interest.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".