Disclosing Delivery Performance Information When Consumers Are Sensitive to Promised Delivery Time, Delivery Reliability, and Price
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
Problem definition: We investigate how the characteristics of consumers and a service firm influence the firm’s optimal pricing and promised delivery-time decisions as well as the optimal investment in the quality of delivery reliability information available to consumers. Methodology/results: We use utility, queuing, and choice modeling theories to model consumers’ behavior and to find solutions to the firm’s profit maximization problem. Managerial implications: The optimal strategy is to disclose either error-free delivery reliability information or no information at all. We also delineate conditions for each of the two strategies to dominate. Funding: This research was supported by the General Research Fund (GRF) of the Hong Kong Research Grants Council under Research Project LU13500822. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0223 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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