Inefficient incentives and nonprice allocations: Experimental evidence from big‐box restaurants
Bibliographic record
Abstract
Abstract Queues are puzzling because they are consistent with wasted profit in equilibrium. Standard rationales trace the puzzle to the pricing of goods. This article uses field experimental evidence from large‐scale restaurants to trace the puzzle to the pricing of labor. The customary wage contract in these settings fosters congestion and longer queues because it can encourage workers to emphasize the quality rather than quantity of output. To study this problem, the field experiment pays waiters bonuses for customer volume on days with excess demand, in addition to the tips and hourly wages they customarily receive. The experimental contract shortens queues substantially, generating surplus gains for consumers with no discernible cost in terms of perceived service quality. Workers earn more via the bonuses and because they earn more in tips. Short‐run profits increase by at least 49%. There is no discernible reduction in long‐run profit. The firm reverted to the baseline contract on excess demand days after many months of evidence, even after acknowledging the gains from the experimental contract. The evidence suggests the puzzle may partly be explained by inefficient wage contracting.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".