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Record W1628132850 · doi:10.1002/cjas.1282

MNE practice transfer as a process of institutional change

2014· article· en· W1628132850 on OpenAlexaffvenue
Gwyneth Edwards, Rick Molz

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsConcordia UniversityHEC Montréal
Fundersnot available
KeywordsPraxisMultinational corporationSociologyHumanitiesProcess (computing)Political scienceManagementPhilosophyComputer scienceLawEconomics

Abstract

fetched live from OpenAlex

Abstract We build upon current theory on strategic organizational practice transfer in multinational firms by incorporating the agency of actors and applying an institutional lens to the transfer process. Our theoretical analysis suggests that practice transfer is a process of institutional change that leads not only to practice adoption, adaptation, or nonadoption, but also to reconstruction. We argue that when contradictions exist within and across institutional environments, misaligned interests motivate actors to engage in praxis. As a parent‐subsidiary coalition, these actors reconstruct the practice by transcending the multitude of institutional environments that comprise the institutional system. Our process theory provides insight into how less powerful subsidiary actors engage in praxis to extend knowledge and build new capabilities within the firm. Copyright © 2014 ASAC. Published by John Wiley & Sons, Ltd.

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)0.016
metaresearch head score (Gemma)0.041
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 score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.016
Scholarly communication0.0080.008
Open science0.0020.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.120
GPT teacher head0.331
Teacher spread0.211 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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