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Record W2776860853 · doi:10.1002/bse.2002

Is Supply's Actual Contribution to Sustainable Development Strategic <i>and</i> Operational?

2017· article· en· W2776860853 on OpenAlexaff
André Tchokogué, Jean Nollet, Nathalie Merminod, Gilles Paché, Véronique Goupil

Bibliographic record

VenueBusiness Strategy and the Environment · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversité de SherbrookeHEC Montréal
Fundersnot available
KeywordsLeverage (statistics)BusinessSustainable developmentReputationMaturity (psychological)SustainabilityProcess managementOrder (exchange)MarketingEnvironmental resource managementKnowledge managementIndustrial organizationEconomicsComputer sciencePolitical scienceFinance

Abstract

fetched live from OpenAlex

Abstract This paper addresses the issue of how sustainable supply practices are actually used as a leverage for sustainable development (SD). In order to assess the level of sustainable supply management within an organization, the authors have reviewed the literature extensively and then developed a five‐step maturity model around five management dimensions. A qualitative exploratory approach based on two detailed case studies of organizations whose reputation for SD is recognized internationally has been used. This methodology allowed us to show (1) how sustainable supply practices could be used as a leverage for an organization's sustainable development approach and (2) that sustainable supply practices still have quite a distance to go with regards to the maturity model for sustainable supply, even in organizations that are often mentioned as leaders in the SD area. In these organizations, managers still emphasize environmental considerations, while neglecting practices that would make it possible to reach the three SD objectives simultaneously. Copyright © 2017 John Wiley &amp; Sons, Ltd and ERP Environment

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations14
Published2017
Admission routes1
Has abstractyes

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