The effect of risks from the supply chain on corporate financial performance: A case study in Vietnam
Bibliographic record
Abstract
This study aims to examine the impact of risks from information in the supply chain on the financial performance of enterprises, with the case study in Vietnam, using quantitative research methods, through SEM linear structure model analysis. With 412 samples who are managers of different ranks at enterprises, the study results show that risks from information in the supply chain not only have a direct, reverse impact but also have an indirect impact on financial performance depending on the level of interdependence of businesses. In addition, opportunistic behavior and the degree of interdependence have also been shown to have a reverse impact on the level of cooperation of enterprises. The findings of this study show a contribution both theoretically and practically, demonstrating the inherent negative risks of information in the supply chain to the financial performance of the enterprise. Research has shown the intermediate role of the degree of interdependence in the relationship between the above two factors. Based on the research results, the authors propose several recommendations to improve the financial performance of enterprises.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".