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Record W2171278069 · doi:10.1002/smj.299

Proactive environmental strategies: a stakeholder management perspective

2002· article· en· W2171278069 on OpenAlexaff
Kristel Buysse, Alain Verbeke

Bibliographic record

VenueStrategic Management Journal · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProactivityStakeholderBusinessPerspective (graphical)Sample (material)Resource (disambiguation)Stakeholder managementGovernment (linguistics)Stakeholder theoryEnvironmental resource managementEnvironmental management systemEmpirical researchStakeholder analysisIndustrial organizationEconomicsManagementEcologyComputer science

Abstract

fetched live from OpenAlex

Abstract This paper includes an empirical analysis of the linkages between environmental strategy and stakeholder management. First, it is shown that several simultaneous improvements in various resource domains are required for firms to shift to an empirically significant, higher level of proactiveness. Second, more proactive environmental strategies are associated with a deeper and broader coverage of stakeholders. Third, environmental leadership is not associated with a rising importance of environmental regulations, thereby suggesting a role for voluntary cooperation between firms and government. Finally, the linkages between environmental strategies and stakeholder management, based on a sample of 197 firms operating in Belgium, appear more limited than expected. Country‐specific characteristics may to a large extent account for these results. Copyright © 2002 John Wiley & Sons, Ltd.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0030.001
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 head0.036
GPT teacher head0.219
Teacher spread0.183 · 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 designQualitative
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

Citations2,099
Published2002
Admission routes1
Has abstractyes

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