The practitioner perspective is more complete: analysing supply chain collaboration for the circular economy
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
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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 it