The Impact of Green Supply Chain Management Practices on Organizational Performance: A Study of Jordanian Food Industries
Bibliographic record
Abstract
The purpose of this study is to test The Impact of Green Supply Chain Management Practices on Organizational Performance: A study On Jordanian Nutrition Industries. The Data was collected through a questionnaire; the consistency percentage was 85%; Cranach's alpha for all the domains and the whole tool is (0.89). Means, standard deviation, and simple and multiple linear regressions analysis were used to test the study hypothesis and the relationships between the dependent and independent variabeles. The researcher built the model and hypothesis based on the dimensions of green supply chain management practices. The researchers chose (6) firms specialized in industrial food sector and which the firms that applied the concept of green manufacturing. The results of the study showed that there was an impact of green supply chain management practices and its elements on organizational performance. The implications of this study are; academic implications, and managerial implications. The researchers include all the green supply chain management elements, on organizational performance which are; environmental performance, financial performance, and Operational Performanc. As a recomendation for this study, it may play an important role for managers and firms through understanding the green supply chain management and increasing the sales and benefits.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".