Sustainability strategies in an EPQ model with price‐ and quality‐sensitive demand
Bibliographic record
Abstract
Purpose The purpose of this paper is to present a mathematical model that illustrates the trade‐offs between sustainability, demand, costs, and profit in a supply chain with a single supplier and a single manufacturer. Design/methodology/approach It is assumed that a single product is produced and sold on a market where demand is sensitive to price and quality. Sustainability is treated as a quality attribute and is measured in terms of the levels of scrap and emissions generated in the supply chain. It is assumed that the emissions and scrap can be controlled by varying production rates or by investing in production processes. The impact of cooperative and non‐cooperative behaviour between the supplier and the manufacturer is explored. Numerical studies are used to illustrate the behaviour of the model. Findings The analysis shows that the supplier and the manufacturer can attract additional customers by controlling scrap and emissions. The behaviour of the supplier and the manufacturer are dictated by the decision criteria, such as changes in the level of sustainability, used by customers to evaluate the product. It is shown that the profit of the system is higher and that the level of quality is lower in the case of cooperation than in the case of non‐cooperation. Research limitations/implications Several areas for future work are highlighted. The study of alternative demand functions, linking sustainability to a monetary component, including additional players, and incorporating additional sustainability indicators all offer possibilities for extending the model. Originality/value There is an identified need for analytical models that consider sustainability in the supply chain. The results are especially important for companies operating in markets where customers perceive the sustainability of a product as a quality criterion.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".