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Record W4408651604 · doi:10.1016/j.exis.2025.101649

Driving factors for responsible sourcing in Europe: Motivations of renewable energy technology manufacturers

2025· article· en· W4408651604 on OpenAlexaff
Marie-Theres Kügerl, Michael Hitch, Katharina Gugerell

Bibliographic record

VenueThe Extractive Industries and Society · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsRenewable energyBusinessNatural resource economicsIndustrial organizationCommerceEconomic geographyMarketingEconomicsEngineering

Abstract

fetched live from OpenAlex

• The study focuses on mineral sourcing by solar PV and wind turbine manufacturers. • Expert interviews explore drivers of responsible sourcing policies in Europe. • Altruism and compliance motivate manufacturers to implement responsible sourcing. • Complexity impedes responsible sourcing implementation in upstream supply chains. • Justice in supply chains needs more comprehensive approaches. The paper highlights the urgent demand for sustainable energy transitions within planetary boundaries while addressing social injustices. This transformation significantly relies on increasing the proportion of renewable energy sources, which requires extensive mining and utilisation of energy transition metals like copper, cobalt, and lithium. Particular concerns arise when Indigenous lands are involved in mining operations, raising issues of human rights and environmental integrity. The European Union and the United States of America have responded to these concerns with legislative measures to enhance supply chain transparency and prevent conflicts stemming from unethical practices. The study aims to explore responsible sourcing efforts among renewable energy technology manufacturers operating in Europe in the context of these regulations and the obstacles they encounter. Through semi-structured interviews with sustainability and procurement managers, the research investigates internal and external drivers for responsible sourcing, identifying altruistic values and regulatory compliance as critical factors. Despite acknowledging the importance of responsible sourcing, supply chain complexity and resource limitations persist. Ultimately, the study suggests that while responsible sourcing initiatives have the potential to promote justice within supply chains, there is a pressing need for holistic approaches to overcome existing barriers and effectively implement sustainable practices across the renewable energy sector.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.230
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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