Enablers and Barriers of Implementing Circular Economy for Micro and Small Manufacturing Enterprises (M-MSEs) in West Sumatera
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
This study aims to analyze the barriers and enablers to implementing a circular economy (CE) at M-MSEs in West Sumatera, identify M-MSEs in West Sumatera that can implement a circular economy, and identify the influencing factors.Questionnaire were distributed to 110 respondents from several M-MSEs in West Sumatera, Indonesia, from March to September 2022.Descriptive analysis and Pearson Correlation was employed in data analysis, and result showed that several CE practices have been implemented by M-MSEs in West Sumatra, thus supporting the notion that CE implies a systemic approach to increasing firm value.In particular, resource-efficient production processes have been widely implemented, namely 36%; this achievement is undoubtedly relatively high compared to the rarity of M-MSEs, which use residual materials in the production process.The most significant barrier to implementing CE that employers feel is the lack of financial support in implementing CE.However, companies that have started implementing CE see it as a business enabler rather than a cost, so CE can be an added value and innovation of the products they produce.
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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 | 0.000 | 0.000 |
| 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