The Effect of Institutional Pressure on Circular Economy Performance in Courier Express Parcel in Indonesia
Bibliographic record
Abstract
Circular economy refers to minimizing inputs and recapturing waste to address environmental, economic, and social issues that arise if the linear economic model continues.However, only a few countries have implemented the concept.Moreover, the logistics sector is not included.This occurs due to the lack of regulations regarding the circular economy.Based on those issues, this study aims to analyze the effect of institutional pressure on circular economy performance mediated by circular economy capabilities in Indonesian courier express parcel companies.The respondents of this study are middle-up managers in courier express parcel companies in DKI Jakarta.This research used quantitative approach.The sampling technique used in this research was purposive sampling technique.The data were collected using an online questionnaire, and then it was distributed to 82 companies.The survey data were analyzed using the partial least squares-structural equation modeling (PLS-SEM) method using SMART PLS 4. The result shows that institutional pressure has negative correlation effect on environmental performance and financial performance.Institutional pressure affects circular economy capability.In addition, circular economy capability significantly affects environmental performance and financial performance.Finally, circular economy capability fully mediates institutional pressure and environmental performance and fully mediates institutional pressure and financial performance.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".