The impact of information sharing on supply chain performance: an empirical study
Bibliographic record
Abstract
Many studies, both theoretical and practical, have emphasised the benefits of information sharing (IFO SH). Most of the research gives mathematical algorithm models that quantify the benefits of IFO SH in the supply chain, but few studies examine the empirical side. This study has empirically tested the relationships among environmental uncertainty (EU), internal integration (INT IN), external integration (EXT IN), IFO SH, and performance. We conducted a field study of 110 firms in the automotive manufacturing industry in Canada and tested the proposed model using the structural equation modelling (SEM) technique. Our results indicated that EU, INT IN, and EXT IN positively impact IFO SH. IFO SH has a positive and direct impact on operational and financial performance, and it enhances the supply chain performance. The study shows that IFO SH is crucial to supply chain performance because it provides the facts that supply chain managers need to make decisions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".