The effect of supply chain practices on retailer performance with information technology as moderating variable
Bibliographic record
Abstract
Today, the retail industry has been overgrowing in offering various products to its customers. The retailer needs excellent support from the supplier to replenish the requirement based on the demand. This support can be achieved by using a secure and fast information system. Retailers, suppliers, and customers should be integrated using information technology and also practicing supply chain management for the benefit of all parties. This study examined the influence of supply chain practices on retailer performance and moderated by information technology. The study has surveyed eighty-six (86) retailer, using a questionnaire, domiciled in the city of Surabaya, Indonesia. Data analysis used SPSS software version 25 to examine the hypothesis. The results showed that supply chain practices had a direct impact on retailer performance; secondly, information technology moderated the effect of supply chain management practices on retailer performance with an increase of 14.70%. Finally, information technology had an impact on increasing retailer performance. This research has an impact on modern retailers to keep adjusting their business with the use of information technology. This finding also contributes to the current research in supply chain management.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".