Heterogeneity of Reference Effects in the Competitive Newsvendor Problem
Why this work is in the frame
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Bibliographic record
Abstract
This paper demonstrates the mathematical equivalence between two recently proposed reference effect formulations for the newsvendor problem and then extends them to a competitive setting. The analysis of the resultant game shows that the heterogeneity of reference effects can explain multiple regularities observed in recent experimental studies of newsvendor competition. In particular, our model explains the main experimental finding that one newsvendor tends to ignore the policy of its competitor. Other experimental observations such as profit disparity, underordering in a high margin scenario, and overordering when there is no expected overflow can all be attributed to the heterogeneity of reference effects in our model’s equilibrium. In addition to explaining these observations, our model also produces a number of new testable hypotheses regarding the competitive newsvendor behavior.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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