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Record W1995551699 · doi:10.1002/bse.603

The mediating effect of information availability between organization design variables and environmental practices in the Canadian hotel industry

2007· article· en· W1995551699 on OpenAlexaffabout

Bibliographic record

VenueBusiness Strategy and the Environment · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsConcordia University
Fundersnot available
KeywordsBenchmarkingBusinessHotel industryEnvironmental management systemMarketingStructural equation modelingKnowledge managementProcess managementEnvironmental resource managementEconomicsComputer scienceTourismEcology

Abstract

fetched live from OpenAlex

Abstract This study examines whether providing employees with information about environmental impacts, industry practices, technologies, regulations and benchmarking of environmental practices mediates the influence of organization design variables on environmental impact reduction. The study finds that both organization design variables (discretionary slack, coordination mechanisms and performance evaluation) and information availability have a direct influence on environmental impact reduction practices in the Canadian hotel industry. However, information availability partially mediates the influence of organization design variables, indicating that effecting changes in organization design alone may be less effective in generating proactive environmental practices without providing employees with information and benchmarking of industry environmental practices. Copyright © 2007 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.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.155
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.010
GPT teacher head0.203
Teacher spread0.192 · 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 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

Citations52
Published2007
Admission routes2
Has abstractyes

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