Retailers facing the challenge of digitalization: a comparison France - Canada [Les détaillants face au défi du commerce connecté : une comparaison France-Canada Prix de la meilleure communication]
Bibliographic record
Abstract
Les detaillants ne sont pas epargnes par la transformation digitale. La premiere phase de cette transformation s'est traduite par l'ajout du canal digital, dans une logique d'organisation en silos. Ils doivent aujourd'hui relever un nouveau defi, celui du commerce connecte, qui tend vers une logique d'integration des canaux. La strategie de digitalisation de six detaillants francais et canadiens, appartenant a trois secteurs (chaussures & accessoires, culture & loisirs creatifs, vin & spiritueux), a ete etudiee selon la methode des cas. Quatre types de changements sont mises a jour (1) des changements organisationnels (integration des systemes d'information ; formation des vendeurs) ; (2) des changements concernant la proposition de valeur (redefinition de l'offre, de l'experience client et reorganisation du point de vente de maniere a y integrer le web-to-store et le store-to-web) ; (3) des changements logistiques (afin d'orienter la logistique vers le client) ; (4) des changements quant aux regles de partage de la valeur entre les differents canaux, ainsi que la creation de nouveaux indicateurs de performance. Mots cles : Commerce connecte, omnicanal, digitalisation du point de vente, T.I., e-logistique
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".