Complexity Analysis of Pricing in a Multichannel Supply Chain with Spillovers from Online to Offline Sales
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, many manufacturers have been selling their products to online consumers through e-tailers by adopting reselling mode and agency selling mode simultaneously. The sales from the online channels inevitably incur spillover effect to the traditional offline channels. This paper develops a dynamic pricing game model on the basis of a long-term gradient adjustment mechanism for a multichannel supply chain that consists of a manufacturer and an e-tailer and focuses on examining the impacts of spillover effect, agency fee, and adjustment speed on the stability and complexity of the dynamic game system. The results show that both a greater spillover effect and a higher agency fee can make the dynamic game system more stable, and a higher adjustment speed can destabilize the dynamic game system through period doubling bifurcation. Furthermore, it is interesting to find that the destabilization of the game system benefits the e-tailer and the supply chain while having little influence on the manufacturer, and thus the dynamic adjustment strategy may improve the supply chain efficiency.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it