The mediating role of supply chain digitization in the relationship between supply chain agility and operational performance
Bibliographic record
Abstract
This study investigates the mediating role of supply chain digitization in the relationship between supply chain agility and operational performance. To test the study hypothesis, a survey questionnaire was distributed to 320 respondents occupying different managerial positions at pharmaceutical manufacturing companies in Jordan. However, 285 questionnaires were retrieved, of which 17 were excluded for their invalidity. Thus, only 268 questionnaires were found to be valid for statistical analysis. The results show There is a relationship that is statistically significant between supply chain agility and operational performance; there is an impact of supply chain agility on supply chain digitization; there is an impact of supply chain digitization on operational performance; and there is no significant mediating role of supply chain digitization in the relationship between supply chain agility and operational performance. The study concludes by emphasizing the importance of supply chain agility in enhancing the operational performance and supply digitization of pharmaceutical manufacturing companies in Jordan. The study recommends other researchers conduct further studies on how digitalization, information systems, and technology may improve supply chain agility, examine the ideas of responsiveness and resilience in agile supply chains, and recognize how these factors might be balanced by businesses to attain the best possible operational performance.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".