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Record W4321795249 · doi:10.4236/jhrss.2023.111003

Interplay of Strategic and Institutional Factors in the Process of Transfer of Human Resource Management Practices in MNCs

2023· article· en· W4321795249 on OpenAlex
Igor Volkov, Benoît Cherré

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

VenueJournal of Human Resource and Sustainability Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Practices
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec en Outaouais
Fundersnot available
KeywordsMultinational corporationSubsidiaryHuman resource managementKnowledge transferBusinessKnowledge managementProcess (computing)Adaptation (eye)Resource (disambiguation)Function (biology)StandardizationProcess managementIndustrial organizationPolitical scienceComputer sciencePsychology

Abstract

fetched live from OpenAlex

Current research on international human resource management (HRM) is structured around the issue of global standardization versus the local adaptation of HRM practices. Numerous studies tended to adopt either an institutional or a strategic perspective. This article examines the interaction between these two groups of factors when MNCs transfer HRM knowledge from their HQ to foreign subsidiaries. The integrative theoretical framework proposed and empirically validated at three MNCs suggests that the choice of the knowledge to be transferred and transfer mechanisms is determined by both institutional and strategic variables. Moreover, the effectiveness of the transfer mainly depends mainly on organizational strategy and the role of HR function in this process.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.056
GPT teacher head0.351
Teacher spread0.295 · 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