Environmental performance measures for supply chains
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
Abstract Purpose – The paper seeks to develop an analytical decision model that is used to investigate the performance of a supply chain when product, process, and environmental quality characteristics are considered. Design/methodology/approach – Environmental performance measures and methods to quantify quality are reviewed and then used to develop a method to measure environmental quality and its associated costs. This was translated into a two‐level supply chain coordination model that captures most aspects of green supply chains. Numerical examples are provided and solved using Excel Solver enhanced with VBA codes. Findings – The results confirmed some findings in the literature that investing to reduce environmental costs improves environmental performance and increases total profits. Research limitations/implications – The environmental quality cost function that was used was of a form that guarantees a global optimal solution. A limitation is that the function may take more complex forms where different analytical and solution methods would be needed. Originality/value – The model fills a gap in the literature where there is a lack of models to help managers implement environmentally acceptable coordinated two‐level supply chains.
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 | 0.006 | 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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