MétaCan
Menu
Back to cohort
Record W2073619362 · doi:10.1108/02651330910971940

Are supply chains global or regional?

2009· article· en· W2073619362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Marketing Review · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsBrock UniversitySimon Fraser University
Fundersnot available
KeywordsSupply chainUpstream (networking)BusinessDownstream (manufacturing)Industrial organizationOriginalitySample (material)Economic geographyPerspective (graphical)Value (mathematics)MarketingEconomicsComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to investigate the following questions: Are supply chains global or regional? What are the performance implications for firms? Design/methodology/approach This paper classifies 183 large North American firms into home‐region oriented, host‐region oriented, bi‐regional, and global firms by using geographic distributions of their upstream and downstream activities. The performance implications of the regional supply chains of a broader set of 273 firms by using Tobin's Q and data on intra‐regional sales or assets are further evaluated. Findings It is found that the evidence to support the regional nature of supply chains – that is, over 85 percent of firms in our sample – have their supply chains within North America. The paper also finds that a regional focus of firms in terms of sales contributes to improved performance as measured by Tobin's Q. Originality/value The regionalization perspective proposed by Rugman and Verbeke to develop and test the regional nature of supply chains is applied.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.279
Teacher spread0.182 · 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