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Record W2767619340 · doi:10.1177/1548051817738940

Uncovering How and When Environmental Leadership Affects Employees’ Voluntary Pro-environmental Behavior

2017· article· en· W2767619340 on OpenAlexaff
Jennifer L. Robertson, Erica Carleton

Bibliographic record

VenueJournal of Leadership & Organizational Studies · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of SaskatchewanWestern University
Fundersnot available
KeywordsTransformational leadershipAntecedent (behavioral psychology)TurnoverSustainabilityBusinessLocus of controlPsychologyPublic relationsMarketingSocial psychologyManagementPolitical scienceEcologyEconomics

Abstract

fetched live from OpenAlex

Environmental sustainability at the firm level is largely shaped by and dependent on individual-level pro-environmental behavior. Accordingly, investigating the antecedents of employees’ environmentally friendly behavior has become the focus of much scholarly inquiry. Research in this area has identified environmentally specific transformational leadership as an important antecedent. Little is known, however, about the mechanisms through which this type of leadership affects employees’ voluntary pro-environmental behavior, and the conditions under which any such effects are enhanced or attenuated. The present research sought to fill this gap. Data from 125 employee dyads revealed that environmentally specific transformational leadership directly and indirectly affects employees’ voluntary pro-environmental behavior, and the indirect effect is only present for employees who are moderate, high, and very high in environmental locus of control. Theoretical and practical implications are discussed.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.245
Teacher spread0.180 · 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

Citations235
Published2017
Admission routes1
Has abstractyes

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