MétaCan
Menu
Back to cohort
Record W4386318574 · doi:10.1002/bse.3552

Examining sustainable supply chain management via a social‐symbolic work lens: Lessons from Patagonia

2023· article· en· W4386318574 on OpenAlexafffund
Mojtaba Mohammadnejad Shourkaei, Kelsey M. Taylor, Bruno Dyck

Bibliographic record

VenueBusiness Strategy and the Environment · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSupply chainSustainabilityWork (physics)BusinessReductionismSupply chain managementLens (geology)Spillover effectSociologyProcess managementKnowledge managementEnvironmental resource managementMarketingEconomicsComputer scienceMicroeconomicsEpistemologyEcologyEngineering

Abstract

fetched live from OpenAlex

Abstract Patagonia, Inc. is widely recognized as a leading brand in sustainable supply chain management in the garment industry, an industry known for its sustainability shortcomings. This study examines Patagonia's supply chain practices through a social‐symbolic work lens. It describes the intentional material work related to Patagonia's inputs, throughputs, and outputs, and also its complementary relational and discursive work. We argue that Patagonia's relational and discursive work are crucial to understanding how Patagonia (a) pursues sustainable supply chain practices, (b) influences its stakeholders to support sustainability, and (c) has positive spillover effects beyond its primary stakeholders. Incorporating a social‐symbolic work lens draws attention to important theoretical and managerial insights—in particular, the need for a holistic rather than reductionist approach and the merit in creating self‐reinforcing positive feedback loops—which are prone to be overlooked in conventional studies of sustainable supply chain management.

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 categoriesMeta-epidemiology (narrow)
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 score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.207
Teacher spread0.185 · 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

Citations32
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueBusiness Strategy and the EnvironmentSame topicSustainable Supply Chain ManagementFrench-language works237,207