How does supply chain management affect financial performance? Evidence from coffee sector
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study investigates the impact of supply chain management on the corporate financial performance of the coffee industry in Vietnam. Particularly, supply chain management is measured in three dimensions, namely relationship with suppliers, relationship with intermediaries and distributors, and relationship with customers. Data are collected by conducting a survey among 248 coffee company representatives of supply chain participants in Vietnam. The multiple regression analysis is adopted in the model estimation. The findings reveal that financial performance (FP) was positively influenced by relationship with intermediaries and distributors (RID), relationship with customers (RC), and relationship with suppliers (RS). In specific, the relationship with intermediaries and distributors (RID) is the most significant driver of financial performance (FP). The study greatly succeeds in providing an unprecedented finding which is the considerable effect of the participants representing supply chain management on financial performance. The findings are essential to the management of supply chain members in the coffee sector. Accordingly, to boost the financial performance, the companies should pay more attention on improving supply chain management efficiency. Supply chain management can be achieved not only by improving processes internally but also by working with suppliers, customers and most notably partners like intermediaries and distributors.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it