Bibliographic record
Abstract
The behavioral literature has demonstrated that the format of supply chain contracts matters even when theoretically it should not and that contracts that in theory coordinate channels fail to do so in laboratory experiments. The existing body of experimental evidence uses an ultimatum bargaining protocol to test analytical models, but there is no reason to think that bargaining in supply chains is in the form of ultimatum offers. We investigate the effect of bargaining on contract performance by extending the bargaining protocol to allow the manufacturer to make concessions. We test coordinating contract with bargaining in the laboratory by comparing wholesale price and the two-part tariff contracts using two different bargaining protocols. We then develop and estimate a statistical model of behavior with bargaining and find that this model organizes our data well. Our main finding is that the contracts that we study are more efficient when participants are allowed to make concessions. The additional channel efficiency is owing to more efficient offers made by manufacturers. The higher channel efficiency primarily benefits the retailer—the weaker party. Our main contribution is the observation that, when testing analytical models of contracts in the laboratory, the way that the bargaining process is implemented, such as the ability to make concessions, has a critical effect on conclusions. This paper was accepted by Vishal Gaur, operations management.
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How this classification was reachedexpand
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".