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Record W1538847299 · doi:10.1109/iemc.2001.960532

Environmental performance and managerial involvement in SMEs: some empirical evidence

2002· article· en· W1538847299 on OpenAlexaff
Stéphane Talbot, Élisabeth Lefebvre, L. Lefebvre, Mario Bourgault

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsDimension (graph theory)BusinessIndustrial organizationOrder (exchange)Product (mathematics)Empirical evidenceEnvironmental scanningMarketingEmpirical researchSurvey data collectionSmall to medium enterprisesEnvironmental management systemKnowledge managementComputer science

Abstract

fetched live from OpenAlex

This research paper investigates how managerial involvement in the formulation and implementation of environmental strategy affects the environmental performance of manufacturing SMEs. The paper analyzes firms' environmental strategies along two dimensions: operations and products. The results of a survey of 241 firms indicate that, along the operations dimension, SMEs should seek everyone's participation in the improvement of their operations' environmental performance. However, along the products dimension, in order to improve the probability of success of their environmental product differentiation strategy, SMEs should favor the involvement of a limited number of technically skilled people, acting as technological champions and gatekeepers.

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)0.005
metaresearch head score (Gemma)0.033
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.035
GPT teacher head0.225
Teacher spread0.189 · 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

Citations4
Published2002
Admission routes1
Has abstractyes

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