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Record W4381381102 · doi:10.1080/13675567.2023.2226611

Supply chain pressures and SMEs’ CSR practices: the moderation effect of supply chain position

2023· article· en· W4381381102 on OpenAlexaff
Rébecca Stekelorum, Jean-Marie Courrent, Martine Spence

Bibliographic record

VenueInternational Journal of Logistics Research and Applications · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Ottawa
FundersMinistry of Higher Education, MalaysiaUniversiti Kebangsaan MalaysiaAgence Nationale de la Recherche
KeywordsModerationBusinessSupply chainNormativeIndustrial organizationUpstream (networking)Corporate social responsibilityStructural equation modelingSituatedDownstream (manufacturing)Position (finance)Institutional theorySupply chain managementResource (disambiguation)MarketingPublic relationsEconomicsManagementPsychologyPolitical science

Abstract

fetched live from OpenAlex

Drawing from institutional and resource dependence theories, this paper investigates how supply chain pressures influence the various dimensions of CSR, i.e. environmental practices, human resources practices, community involvement practices, and marketplace practices, in SMEs. Using a structural equation modelling approach and data collected from 273 SMEs, our findings indicate that institutional pressures exerted by supply chain partners differently influence the level of CSR practices in SMEs. Notably, the study demonstrates that coercive pressures have no significant influence on CSR practices, whereas mimetic and normative pressures positively and significantly influence the level of CSR practices. Furthermore, the positive influence of normative pressures on CSR practices is stronger for SMEs situated downstream in their supply chains, whereas SMEs in further upstream positions are sensitive to mimetic pressures for their environmental, workplace and marketplace practices. Overall, this study provides unique insight on the association between supply chain pressures and CSR practices in SMEs.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.052
GPT teacher head0.375
Teacher spread0.322 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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