The Factors Affecting Green Supply Chains: Empirical Study of Agricultural Chains in Vietnam
Bibliographic record
Abstract
This paper aims at identifying the factors affecting green supply chain in agriculture in Vietnam currently. The literature indicates 14 factors affecting green supply chains in agriculture including: (i) manager commitment, (ii) IT system, (iii) new technology, (iv) organizational culture, (v) HR quality, (vi) energy & waste management, (vii) market & competition, (viii) political supports, (ix) knowledge & experience, (x) actors’ participation, (xi) costs, (xii) suppliers, (xiii) logistics management, and (xiv) consumer awareness. Our regression model with 14 independent variables was established to determine the factors affecting the success of green supply chains in Vietnam agriculture. The regression results show six factors affecting significantly and positively green supply chain in agriculture in Vietnam, including: (i) manager commitment, (ii) new technology, (iii) HR quality, (iv) knowledge & experience, (v) logistic management, and (vi) consumer awareness. Hence, the paper suggests some recommendations to Vietnam firms and State for improving green supply chain in agriculture.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".