The effect of supply chain integration capability and green supply chain management (GCSM) on manufacturing industry operational performance
Bibliographic record
Abstract
The purpose of this study was to determine the effect of supply chain integration capabilities on operational performance by mediating green supply chain management in manufacturing companies. This research method is quantitative and the sampling method in this study uses probability sampling. The primary data is obtained by distributing 490 online questionnaires to manufacturing companies. Validity and reliability testing were carried out using Structural Equation Modeling Partial Least Square (SEM-PLS) and data processing was accomplished using SmartPLS. The findings in this study found that supply chain integration capabilities had a direct positive and significant effect on operational performance while supply chain integration capabilities had a positive and significant effect on green supply chain management. In addition, green supply chain management had a direct positive and significant effect on operational performance. The ability of supply chain integration also maintained a positive and significant effect on operational performance mediated by green supply chain management.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".