The role of green supply chain management (GSCM) on the competitiveness and performance of Indonesian manufacturing companies
Bibliographic record
Abstract
There are several environmental issues that are in the spotlight globally, including: global warming, depletion of the ozone layer, the greenhouse effect, and acid rain. This problem is a concern and needs serious action for human survival. Supply chain activities are suspected of contributing to environmental damage. The purpose of this study is to analyze the effect of Green Supply Chain Management on competitiveness, the effect of Green Supply Chain Management on Performance and the effect of competitiveness on Performance. The study used quantitative methods and research data were obtained using online questionnaires distributed via social media. The research respondents were managers of manufacturing companies in Indonesia and the number of samples used was 540 respondents who were determined using a purposive sampling technique. Data analysis in this study used Structural Equation Modeling (SEM) and software used for data processing by SmartPLS. The results showed that Green Supply Chain Management had a positive and significant effect on competitiveness, Green Supply Chain Management did not have any positive and significant effect on Performance and competitiveness had a positive and significant effect on Performance.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| 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 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".