Concerns of Vietnamese Producing-exporting Seafood SMEs (VPESSMEs) on Supply Chain
Bibliographic record
Abstract
Supply chain has been discussed for many decades, however, previous researches have focused on the supply chain in general, in industrial fields or in developed countries. It is rare to find articles about supply chain in agricultural and fishing industries in a developing country like Vietnam. Moreover, there have been few researches using FsQCA in analyzing the factors affecting supply chain of small and medium enterprises (SMEs). This research focuses on using FsQCA to analyze the weight of factors that influence a supply chain of an industry which is one of the key exporting industries in Vietnam especifically seafood industry. Findings show that Vietnamese producing-exporting seafood SMEs (VPESSMEs) do not have any clear supply chain structure and sufficient consideration into building an effective supply chain. The authors would like to draw up some limitations of the supply chain management of Vietnamese producing-exporting seafood SMEs (VPESSMEs) then offer some suggestions especially for the fishing and agricultural industry.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".