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Record W2767786522 · doi:10.1002/bse.2003

Linking Environmental Management to Environmental Performance: The Interactive Role of Industry Context

2017· article· en· W2767786522 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 institutionsWestern University
FundersDeutsche Forschungsgemeinschaft
KeywordsDynamismLeverage (statistics)SustainabilityCompetitive advantageBusinessEnvironmental scanningContext (archaeology)Industrial organizationMarketingKnowledge managementEnvironmental resource managementEnvironmental management systemEconomicsComputer scienceEcology

Abstract

fetched live from OpenAlex

Abstract In the past, corporate sustainability scholars advocated that, for many firms, environmental management could turn into a valuable capability conferring a competitive advantage. However, little attention has been paid to the role of the industry context and its influence on the relationship between environmental management and organizational performance. In this study, we examine the effect on this relationship of three contextual variables: munificence, dynamism and complexity. Drawing on longitudinal data from 336 firms representing 30 industries, we find that munificence enhances the degree to which a firm can leverage its environmental management capabilities to improve environmental performance. 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 categoriesMeta-epidemiology (narrow), Science 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 score0.358
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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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