Resale Price Maintenance with Strategic Customers
Bibliographic record
Abstract
We consider a decentralized supply chain (DSC) under resale price maintenance (RPM) selling a limited‐lifetime product to forward‐looking customers with heterogeneous valuations. When customers do not know the inventory level, double marginalization under RPM leads to a higher profit and aggregate welfare than without RPM under a two‐part tariff contract (TT). Both RPM and TT profits are higher and aggregate welfare is lower than in a centralized supply chain (CSC). When customers know the inventory, RPM coincides with CSC. Thus, overestimation of customer awareness may lead to overcentralization of supply chains with profit loss comparable with the loss from strategic customers. The case of RPM with unknown inventory is extended to an arbitrary number of retailers with inventory‐independent and inventory‐dependent demand. In both cases, the manufacturer, by setting a higher wholesale price, mitigates the inventory‐increasing effect of competition and reaches the same profit as with a single retailer. The high viability and efficiency of RPM in using double marginalization as a strategic‐behavior‐mitigating tool may serve as another explanation of why manufacturers may prefer DSC with RPM to a vertically integrated firm.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".