The role of industry 4.0 in supply chain sustainability: Evidence from the rubber industry
Bibliographic record
Abstract
The objective of the current study is to examine the role of Industry 4.0 in supply chain sustainability (SCS). To examine the effect of Industry 4.0 on SCS, the big data technology is considered. As the supply chain process requires a significant data handling system among the companies, however, companies are lacking in this area. Therefore, the relationship between data storage, data transformation, data utilization, order management and SCS were examined. Data was collected from the rubber industry. For the purpose of data collection, questionnaires were used, and data were collected from the rubber companies of Indonesia. Results of this study shows that Industry 4.0 has a vital role in SCS. Implementation of Industry 4.0 among the rubber companies shows a positive effect on SCS. Particularly, the applications of big data technology have a vital role in order management and SCS. Big data technology has a significant positive effect on SCS. Big data technology has a positive role to promote order management which further influences positively on SCS.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".