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Record W3122266293

Voluntary Environmental Decision Making in Firms: Green Electricity Purchases and the Role of Champions

2009· article· en· W3122266293 on OpenAlexaffabout
Travis Gliedt, Tom M. Berkhout, Paul Parker, Joseph A. Doucet

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaUniversity of British Columbia HospitalUniversity of Waterloo
Fundersnot available
KeywordsChampionBusinessPurchasingStakeholderElectricityMarketingGovernment (linguistics)TurnoverEconomicsManagement
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the corporate decision to voluntarily purchase premium-priced Green Electricity (GE) by examining the internal and external factors which influence environmental decision making. In-depth interviews were conducted with eight paired firms in Alberta, Canada. Firms purchasing GE typically employed a top-down decision-making process, while firms characterised by a participative process did not. An internal driver (environmental champion) was more significant than external factors (regulations, stakeholder pressure) at influencing firms to voluntarily adopt GE purchasing, while organisational culture was found to moderate the effect of drivers. Cost is a common inhibitor to green purchase decisions, but customer (oil industry) perceptions and government regulations were also identified in some cases.

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)0.017
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.003
GPT teacher head0.194
Teacher spread0.191 · 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

Citations1
Published2009
Admission routes2
Has abstractyes

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