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Record W4200195645 · doi:10.3917/mav.126.0115

Développement d’un assistant virtuel en tourisme : rôles clés de l’utilité et du plaisir perçus sur l’intention d’adoption

2021· article· fr· W4200195645 on OpenAlex
Pablo José Vásquez García, Sandrine Prom Tep, Manon Arcand, Lova Rajaobelina, Line Ricard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueManagement & Avenir · 2021
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

Le recours aux assistants virtuels (AV) pour les services aux consommateurs ne cesse de croître, et l’industrie touristique ne fait pas exception à ce phénomène. Réalisée auprès de personnes de 45 ans et moins, cette étude montre l’importance de l’utilité et du plaisir perçus d’un chatbot touristique pour accroître l’ intention d’adoption. Pour sa part, la facilité d’utilisation perçue n’a pas d’effet. Cette recherche confirme le rôle modérateur de l’expérience antérieure avec un AV alors que l’effet du plaisir perçu sur l’intention d’adoption est plus élevé pour les consommateurs ne les ayant jamais utilisés. Diverses recommandations managériales sont avancées pour optimiser la conception et le succès d’implémentation des chatbots, et leur permettre de prendre ainsi la place qui leur revient parmi les outils numériques assistant les touristes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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