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Unpacking Dimensions of Foreignness: Firm‐Specific Capabilities and International Dispersion in Regional, Cultural, and Institutional Space

2013· article· en· W1773851362 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

VenueGlobal Strategy Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsQueen's University
Fundersnot available
KeywordsUnpackingSpace (punctuation)Economic geographyBusinessDispersion (optics)Institutional theoryGeographical distanceIndustrial organizationInternational tradeSociologyEconomicsManagementComputer scienceLinguistics

Abstract

fetched live from OpenAlex

While recent research has pointed to the importance of regional strategy and the ‘interregional liability of foreignness,’ critics have pointed out that this argument obscures important differences within regions as well as the similarities across them. Bridging these diverging viewpoints, our research is designed to unpack this debate into cultural, institutional, and regional components. Using a large data set, we find that firms are significantly more dispersed across cultural and, in particular, institutional boundaries, than they are across geographically defined regional boundaries. Further, our results indicate that certain firm‐specific resources influence firms' global dispersion; in particular, we find that a nuanced interplay of proprietary capabilities such as technology, marketing, and partnering capabilities has an impact on the location of firm activities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.038
GPT teacher head0.257
Teacher spread0.219 · 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