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Record W2535943760 · doi:10.46697/001c.16857

Responses to Subpar Performance in Foreign Subsidiaries

2017· article· en· W2535943760 on OpenAlex
Vanessa C. Hasse

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

VenueAIB Insights · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsWestern University
Fundersnot available
KeywordsOrchestrationSynchronizingSubsidiaryResource (disambiguation)PhenomenonBusinessPsychologyComputer scienceMultinational corporationEpistemologyFinanceTelecommunicationsArtPhilosophy

Abstract

fetched live from OpenAlex

A finalist for the 2017 Peter J. Buckley and Mark Casson AIB Dissertation Award, this dissertation (summarized in the article) investigates the phenomenon of responses to subpar performance in foreign subsidiaries. Using the resource-based view, resource orchestration, and related lenses, a three-pronged framework is proposed and tested which combines the notions of “Identifying” (detection of response determinants), “Responding” (assessment of response effectiveness for recovery and survival prospects), and “Synchronizing” (exploration of the predictors and outcomes of response timing). Implications for practitioners and avenues for future research are discussed.

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 categoriesInsufficient payload (model declined to judge)
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 score0.804
Threshold uncertainty score0.999

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.037
GPT teacher head0.255
Teacher spread0.217 · 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