Communautés de consommateurs B-to-C : approche des stratégies internationales
Bibliographic record
Abstract
Les communautés virtuelles de consommateurs B-to-C constituent un outil de plus en plus sollicité par les entreprises internationales. Pourtant l'étude de ces stratégies reste fortement délaissée par les milieux académiques. Cet article contribue à améliorer la compréhension des mécanismes de création et de gestion d'une communauté virtuelle de consommateurs à l'échelle internationale. D'une part, nous y présentons une typologie permettant de distinguer trois types de communautés virtuelles B-to-C pouvant être implémentées au niveau international. D'autre part, l'analyse du processus de création de deux communautés virtuelles lancées en France et au Royaume-Uni par une multinationale, permet d'identifier les décisions et les acteurs impliqués dans la mise en place d'une stratégie communautaire au niveau international. Mots Clé : Communauté virtuelle B-to-C, stratégie internationale, Decision Systems Analysis, communauté de consommation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".