MétaCan
Menu
Back to cohort
Record W2171575424 · doi:10.1080/13032917.2008.9687072

Why Go Green? The Business Case for Environmental Commitment in the Canadian Hotel Industry

2008· article· en· W2171575424 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnatolia · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBusinessHotel industryMarketingTourismCompetitive advantageLoyaltyEnvironmental complianceHospitality industryAction (physics)Loyalty business modelService (business)Environmental protection

Abstract

fetched live from OpenAlex

ABSTRACT Despite several studies, international treaties and individual organization's commitment to going green in the tourist hotel industry, there has been limited discussion of the business case for implementing environmental practices. Several hotels have determined that there are numerous benefits to greening their hotel operations; however, there is still a gap between attitude and action in this industry. Cost savings; competitive advantage; employee loyalty; customer retention; regulatory compliance; risk management and social responsibility have been identified as the benefits to environmental commitment however with very limited discussion and proof in relation to the hotel industry. This paper seeks to identify the business case for environmental commitment with a focus on the Canadian hotel industry. Concrete examples of benefits that apply to this industry are discussed as well as future trends that support the case that going green is necessary for an economically viable and efficiently run hotel.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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