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Record W2560206442 · doi:10.3166/rfg.2016.00078

Démarches environnementales, source de performance ?

2016· article· fr· W2560206442 on OpenAlexaff
Aurélie Corne, Élisabeth Robinot

Bibliographic record

VenueRevue française de gestion · 2016
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesComputer scienceArt

Abstract

fetched live from OpenAlex

L’objectif de ce travail est d’analyser la performance d’un échantillon de 12 agglomérations représentatives du secteur hôtelier 4 et 5 étoiles français et monégasque. Nous cherchons à identifier le lien entre l’adoption de démarches environnementales et la performance de ces établissements. L’apport de la théorie du signal permet de considérer les labels comme signal d’une démarche environnementale. Cette contribution mobilise la méthode Data Envelopment Analysis (DEA) afin de proposer une mesure de performance opérationnelle comparable. Les résultats obtenus permettent de confirmer l’impact positif des démarches environnementales sur la performance et les recommandations managériales préconisent une poursuite des efforts de signal via la labellisation.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations4
Published2016
Admission routes1
Has abstractyes

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