Inventory, Discounts, and the Timing Effect
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
We introduce and analyze a model that explicitly considers the timing effect of intertemporal pricing—the concept, found in practice, that demand during a sale is increasing in the time since the last sale. We present structural results that characterize the interaction between the decision to hold a sale and the inventory-ordering decision. We show that the optimal inventory-ordering policy is a state-dependent base-stock policy; however, the optimal pricing policy can be quite complicated due to both the value and the cost of holding inventory and delaying sales. In our computational analysis, we find that compared to a fixed-price policy, we see an average gain in profit of almost 5% from optimally varying promotion and inventory decisions accounting for intertemporal demand, and we find that this potential profit gain increases as demand variability decreases. We also develop a heuristic based on deterministic pricing and find that it performs well relative to the optimal policy.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it