The impact of supply chain capability and supply chain performance on marketing performance of retail sectors
Bibliographic record
Abstract
To increase competitive advantage, any company needs to improve its supply chain management. The aim of this study is to define the relationships between supply chain capability, supply chain performance and marketing performance. Some of the retail stores are no longer operating. Tool of analysis is the partial least square that is suitable for small sample size. The result of PLSSmart 3.0 shows that the relationship between supply chain capability and supply chain performance is positive and significant. However, the relationship between supply chain performance and marketing performance is positive but non-significant. Direct relationship between supply chain capability and marketing performance appears to be positive and significant. Indirect relationship between supply chain capability and marketing performance through supply chain performance also appears to be non-significant. The study can be a reference for retail managers to increase the supply chain in their marketing performance. Some further research needs to add other variables to see a more concrete relationship between supply chain capability and marketing performance.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".