Stakeholder Theory and Supply Chains in the Circular Economy
Bibliographic record
Abstract
Abstract Recently, 181 CEOs of notable corporations signed a joint statement at the Business Roundtable (2019) on the “Purpose of a Corporation” – declaring its aim as the creation of benefits for “all stakeholders.” This will likely accelerate the circular economy transition process. Harmonizing the interests of various stakeholders is essential for managing successful organizations and supply chains, which is similar to the first principle of using natural ecosystem thinking. According to that principle, it is essential to strike a balance between the producers, consumers, scavengers, and decomposers. We draw on stakeholder theory to identify various challenges and risks that restrict businesses from building sustainable circular systems. We turn our attention toward increasing the numbers of “scavengers” and “decomposers” in the system for attaining sustainable growth. Our emphasis is on (1) empowering organizational life cycle stages, (2) designing for “decomposability” and “scavengers,” and (3) suggesting the use of advanced optimization models for harmonizing stakeholder relationships.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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 teacher head, 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".