Are Ecosystems the Missing Link in Circular Transitions? Insights From a Comprehensive Literature Analysis
Bibliographic record
Abstract
ABSTRACT Although recent literature on the circular economy ( CE ) has highlighted the important role of ecosystems, there is still limited understanding of the main themes that characterize circular ecosystems. This study addresses this gap by combining a comprehensive topic modeling analysis employing latent Dirichlet allocation (LDA) with a systematic literature review of 66 articles focused on circular ecosystems. The main results reveal that circular ecosystems have often been analyzed through the lens of (i) circular business models and ecosystem innovation, (ii) CE policies and stakeholder governance, and (iii) implementation and transition to CE . Furthermore, based on this study's findings, topics that have not yet been explored in this area are identified, and a research agenda is suggested. The results of this study also underscore key themes in the relationship between CE and ecosystems and provide managers with guidance on better integrating their businesses into ecosystems aligned with circularity objectives.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".