Bibliographic record
Abstract
Purpose Contracting is an important issue in supply chain management. In this paper, the authors aim to discuss and compare the manufacturer's contracting options when the retailer faces a traditional newsvendor problem with a fixed retail price: a wholesale price only contract, a wholesale price discount contract, a returns policy contract, and a returns policy with the wholesale price discount contract. The paper also aims to examine how these contracting options affect decisions of the manufacturer and the retailer, as well as the supply chain efficiency. Design/methodology/approach Models are developed based on the manufacturer's four contracting options. The manufacturer's optimal wholesale prices have been obtained. The ordering decisions of the retailer are discussed in each of the manufacturer's four contracting options. The paper also uses numerical examples to illustrate the author's managerial insights and results. Findings As compared to the wholesale price only contract, it is found that implementing a wholesale price discount policy effectively encourages the retailer to order more product and enhances the retailer's profit at the expense of lowering the manufacturer's profit. It is also found that when the manufacturer offers a returns policy and if this policy cannot enhance the retailer's profit, a returns policy with the wholesale price discount contract can lead to a win‐win situation for both the manufacturer and the retailer. Originality/value The research provides managerial insights on how different contracts affect decisions and efficiency of the supply chain.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".