Closed‐loop supply chains in process industries: An empirical study of producer re‐use issues
Bibliographic record
Abstract
Abstract Closed‐loop supply chain research has primarily focused on discrete industries, leaving important issues involving waste disposal and re‐use in process industries unaddressed. This exploratory study investigates re‐use issues and practices related to process industry firms—from the producer's perspective—with the objective of identifying important issues that need further research in the field. Site visits were conducted to identify and clarify re‐use issues unique to process industry firms for the purpose of developing a mail survey instrument. The mail survey provided detailed information about the sources of returned product and materials and the subsequent re‐use decisions made by 141 different manufacturing facilities in a wide variety of process industries including chemicals, food, rubber, and plastics. Results indicate that process industry firms are quite diverse, that some common beliefs about re‐use in process industry firms do not apply to all process types in these industries, and that research efforts are needed in the areas of network design and product acquisition; inventory; production planning and control; and scheduling. The paper concludes by identifying specific research questions important to re‐use in process industry environments.
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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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".