Segmentation achats dans la gestion des relations client-fournisseur
Bibliographic record
Abstract
L’article présente les résultats d’une recherche qualitative sur les dispositifs de segmentation achats au cœur des relations client-fournisseur. Depuis Kraljic (1983), la littérature en stratégie spécialisée dans l’étude du choix d’un fournisseur ne cesse de proposer des matrices stratégiques à l’attention des dirigeants d’entreprise. Toutefois, il est difficile de déterminer comment ces dispositifs peuvent réellement éclairer les décisions et permettre des coopérations industrielles durables. L’article tente de combler ce manque en précisant comment les dispositifs de segmentation achats sont inséparables des capacités dynamiques d’une entreprise. Le choix d’un fournisseur n’est plus réduit à une décision stratégique statique, mais est conçu comme l’appréciation dynamique des ressources et compétences à allouer au pilotage de coopérations industrielles.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.003 |
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".