Supply Chain Collaboration Between Retailers and Manufacturers: Do They Trust Each Other?
Bibliographic record
Abstract
This study examines the collaboration in the food supply chain focusing on two chain partners: the retailers and the manufacturers. The authors examine the impact of key factors on collaboration performance including trust and the duration of collaboration. This study compares and contrasts the perceptions by retailers and manufacturers on the role of supply chain management. It illustrates that different food supply chain partners perceive differently the key critical factors which lead to supply chain effectiveness and casts doubts on the viability of current collaboration efforts which aim to achieve mutual benefits across the entire supply chain. It shows that the effectiveness of collaboration, and thus the functioning of the food supply chain, is highly dependent on retailers′ initiative to build and foster trust with their partners. It also depends on manufacturers′ ability to fulfil a complex set of retailers′ requirements including physical distribution management, commitment to the partnership, and effective information management. Managerial implications are discussed particularly for small and medium sized companies and directions for future research are provided.
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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 | 0.014 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".