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Record W2127112528 · doi:10.5539/jms.v4n1p96

Using the Technology-Organization-Environment Framework for Analyzing Nike’s “Considered Index” Green Initiative, a Decision Support System-Driven System

2014· article· en· W2127112528 on OpenAlex
Rebecca Angeles

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Management and Sustainability · 2014
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsNikeSustainabilityContext (archaeology)Index (typography)Process managementBalanced scorecardBusinessDecision support systemKnowledge managementComputer scienceData mining

Abstract

fetched live from OpenAlex

This study explains the implementation of an environmental management information system that supports the sustainability goals of Nike using the technology-organization-environment (TOE) framework of Tornatzky and Fleischer. Literature review is applied to a single firm in using the TOE framework, with particular emphasis on the technological context of the framework. The use of Nike’s firm level decision support systems is highlighted in this study. Suggestions are made about improving Nike’s Material Sustainability Index (MSI), its key sustainability tool, which is at the heart of the firm's group decision support system tool.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.657
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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