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Record W4412060476 · doi:10.1016/j.jclepro.2025.146122

Misalignment in the automotive supply Chain: Sustainability commitments of automotive manufacturing firms and their suppliers

2025· article· en· W4412060476 on OpenAlexaffabout
David Benjamin Billedeau, Jeffrey Wilson

Bibliographic record

VenueJournal of Cleaner Production · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAutomotive industrySupply chainBusinessSustainabilityManufacturing engineeringIndustrial organizationSupply chain managementEngineeringMarketing

Abstract

fetched live from OpenAlex

This study investigates whether the net zero pledges and broader sustainability commitments of major firms influence similar commitments among their suppliers. Using a case study of Canada's entire automotive manufacturing sector, we examine original equipment manufacturers and their supply chains to assess the extent of alignment in environmental sustainability practices. Our findings reveal a significant gap between the commitments of large companies and those of their suppliers across multiple dimensions, including net zero targets, environmental, social, and governance integration, and adoption of sustainability reporting frameworks. To evaluate this alignment, we introduce a novel metric—the mirroring impact factor—which quantifies the degree to which supplier practices reflect those of original equipment manufacturers. The consistently low mirroring impact factor scores highlight limited diffusion of sustainability commitments across the supply chain, underscoring the need for more effective mechanisms to drive supplier engagement in decarbonization and broader sustainability efforts.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.274
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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.

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

Citations4
Published2025
Admission routes2
Has abstractyes

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