Strategic analysis of manufacturer encroachment in dual-channel supply chains with platform service
Bibliographic record
Abstract
This paper considers a dual-channel supply chain with two members, comprising a manufacturer and an online platform. We mainly investigate the influence of various key system variables on manufacturer encroachment strategy and all members’ optimal decisions through Stackelberg game models. Our findings show that, regardless of the size of each parameter, the encroachment strategy is always optimal to the manufacturer; the manufacturer may be motivated to choose the direct selling channel and the platform may opt for the agency selling channel due to a high commission rate. Moreover, when the inter-channel substitution rate is high, the encroachment strategy has a diminishing positive effect on the manufacturer and an increasing negative effect on the platform so that the platform may temporarily benefit from the manufacturer encroachment; in cases where the inter-channel substitution rate is not high, the encroachment strategy always yields advantages for the manufacturer while causing disadvantages for the platform. In addition, if the elasticity coefficient is large, both the manufacturer and the platform are inclined to the reselling channel, that is, if the platform service cost is high, it is advisable for the platform to reduce its investment of service to avoid negative effect.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".