Employee Reactions to Preservice Tips and Compliments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Preservice tips are becoming increasingly common in the marketplace (e.g., online food delivery, quick-service restaurants). While prior research has investigated how the practice of preservice tipping is perceived by customers, how preservice tipping impacts the perceptions and behaviors of employees remains unexplored. Does tipping early actually elicit better service? Through a series of four studies, our research compares the effectiveness of tips—a financial incentive, with compliments—a nonfinancial incentive. The results indicate that early tips and compliments are both effective in obtaining better service, but the relative effectiveness of a tip versus a compliment depends on the service context. In closed service contexts—which involve a continuous, relatively short interaction—tips are superior. For example, when getting a drink at a bar, buying a sandwich at a quick-service restaurant, or dropping off a car for valet parking, tipping early should lead to better customer service. In contrast, in open service contexts—which involve multiple interactions over a more extended period and provide an opportunity for a social connection—compliments become more effective. The results have practical implications for customers wishing to enhance their service experiences and for managers in motivating their employees.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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