An integrated production-inventory model for deteriorating items to evaluate JIT purchasing alliances
Bibliographic record
Abstract
The implementation of just-in-time (JIT) principles has been shown to be worthy of analysis due to its potential economic benefits. Yet, while several empirical studies have reported the success of adopting JIT management concepts, little work has been accomplished in offering analytical tools for assisting managers for implementing JIT strategy. This paper proposes a new inventory model to better embrace JIT purchasing. In pursuing this goal, we develop a deterministic singlesetup multiple-delivery model for deteriorating items by considering the effect of the time value of money (TVM). We propose a solution procedure to determine the optimal decisions that maximize the discounted profit function of this analytical model, and compare it with some other alternatives. Here, we show the derivation of the mathematical model, the algorithm of the proposed solutions, and the application of the new approach through two numerical experiments. The study reveals that modeling the TVM effect complicates the determination of an optimal JIT inventory policy; nevertheless, we find that accounting for TVM can be decisive in terms of promoting and implementing JIT purchasing agreements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".