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Reconceptualizing Value Creation for Regenerative Supply Chains: The Role of Non-Traditional Actors

2025· article· en· W4416001717 on OpenAlexaff
Eugenia Rosca, Kelsey M. Taylor, Wendy L. Tate, Lydia Bals, Francesca Ciulli, Aline Seepma, Nazli Turken, Liliane Carmagnac

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSupply chainValue (mathematics)Supply chain managementFunction (biology)Value creationService management

Abstract

fetched live from OpenAlex

Regenerative supply chains necessitate a significant change in how organizations operate at all tiers of the supply chain to effectively create value. The transition to regenerative supply chains requires the engagement a broad range of actors with strong moral commitments toward regeneration who recognize the interdependence between social, economic and ecological well-being. Traditional operations and supply chain management function with a “take-make-waste” conceptualization, which includes many assumptions about value that conflict with the principles of regeneration. We problematize the existing frames used to understand what constitutes value, and how it is created and distributed within supply chains. We reconceptualize value and propose alternative approaches to value creation and distribution in regenerative supply chains that centres non-traditional actors and recognizes the enabling force of functional social and ecological systems. In light of these reconceptualizations, we advance research principles to guide future research on regenerative value in supply chains.

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)0.018
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0090.066
Scholarly communication0.0250.030
Open science0.0040.013
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.252
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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