MétaCan
Menu
Back to cohort
Record W3006632396 · doi:10.1522/revueot.v28n3.1084

Accompagner la transformation numérique des PME : une perspective écosystémique de la création de valeur

2020· article· fr· W3006632396 on OpenAlexaffvenue
Claudia Pelletier, Vanessa Martel

Bibliographic record

VenueRevue Organisations & territoires · 2020
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Dans le monde actuel des affaires, la transformation numérique des PME dépasse désormais le simple choix d’un « outil » technologique. Cela suppose aussi des mutations profondes dans l’organisation, incluant le capital social. Une perspective écosystémique de ce phénomène permet de mieux comprendre comment les acteurs en présence intègrent de nouvelles ressources, tangibles et intangibles, par l’échange de services avec des intervenants socioéconomiques et des spécialistes en technologies de l’information (TI). En organisant la transformation numérique dans un système soutenant la cocréation de valeur, on observe ainsi l’émergence d’une panoplie de programmes visant l’accompagnement de cette transformation. Or, qu’en est-il vraiment de ces échanges entre acteurs indépendants? De quoi sont-ils constitués plus précisément? L’exploration des pratiques d’accompagnement au numérique existantes met de l’avant une logique de services qui se combine aux principes reconnus de l’innovation en contexte de PME. Des contributions théoriques et pratiques complètent le portrait présenté.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.011
Scholarly communication0.0090.008
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.019
GPT teacher head0.240
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueRevue Organisations & territoiresSame topicBusiness Strategy and InnovationFrench-language works237,207