Trade-in and Save: A Two-period Closed-loop Supply Chain Game with Price and Technology Dependent Returns
Bibliographic record
Abstract
Consumers evaluate the convenience of changing their products according to the price paid as well as the technology (quality) level. When the consumers wish to capitalize the products residual value, they should return them as early as possible. Accordingly, we develop a model of Closed-loop Supply Chain (CLSC) where consumers seek to gain as much as possible from their returns and the return rate is a function of both price and quality. We model a two-period Stackelberg game to capture the dynamic aspects of a CLSC, where the manufacturer is the channel leader. We investigate who, namely, manufacturer or retailer, should collect the products in the market. Thus, we identify the best CLSC structure to adopt when the return rate is both price- and quality-dependent. Our results demonstrate that it is always worthwhile for companies to collect products and adopt an active return approach for returns. We investigate the effect of retail competition in both forward and backward channels and show the impact of eliminating the double marginalization on market outcomes.
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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 | 0.005 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| 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".