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Record W2606130436 · doi:10.1002/bse.1949

Measuring the Choice of Environmental Sustainability Strategies in Creating a Competitive Advantage

2017· article· en· W2606130436 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.

Bibliographic record

VenueBusiness Strategy and the Environment · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSustainabilityCompetitive advantageBusinessContext (archaeology)Sustainability organizationsMarketingLegitimacyWork (physics)Environmental economicsIndustrial organizationEconomicsPoliticsEngineering

Abstract

fetched live from OpenAlex

Abstract Environmental sustainability has often been claimed as a means to providing a competitive advantage by encouraging efficiencies, attracting customers and obtaining business. This work critically considers this idea in the context of the hotel industry by comparing the strategic intent and implementation of sustainability initiatives in hotels across North America. Environmental sustainability strategies can employ a low cost, a differentiated or a hybrid (a combination of the two) approach to creating a competitive advantage. Controlling for the type and age of hotel we find that the hotels sampled in this study used a combination of all three approaches but tended to rely on their need to create environmental sustainability legitimacy by placing an emphasis on differentiation through environmental sustainability branding. A lack of recognition by management of the contribution to their future economic success that low cost strategies can provide has implications for hotel owners. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
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 studies0.0010.003
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.014
GPT teacher head0.225
Teacher spread0.212 · 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