The practitioner perspective is more complete: analysing supply chain collaboration for the circular economy
Bibliographic record
Abstract
Collaboration is crucial in integrating circular economy (CE) into operations and supply chains (SCs). However, a comprehensive discussion among scholars and practitioners is limited. Hence, this study aims to amalgamate expert viewpoints and understand how collaboration empowers CE implementation in SCs. A three-round Delphi study was designed with experts from industry and academia to identify factors affecting SC collaboration and suitable collaboration practices. Collected data was analysed using content, frequency and cluster analyses. While identifying these factors through three expert cluster groups: CE-focused academics, OSCM-focused academics, and practitioners, seven core facets of collaboration in CE were conceptualised: partner orientation, economic performance, joint operations, strategic positioning of the focal firm, linking CE business models to SCs, smoothening complexities in SCs and involving regulatory bodies. With this empirically validated conceptualisation, the role of collaboration in integrating CE into SCs is exemplified while highlighting the distinct viewpoints among academics and practitioners.
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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 | 0.019 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".