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Global Talent Management: A Critical Review and Research Agenda for the New Organizational Reality

2024· review· en· W4391100270 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

VenueAnnual Review of Organizational Psychology and Organizational Behavior · 2024
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMultinational corporationTalent managementBusinessKnowledge managementMacroProcess managementMarketingComputer science

Abstract

fetched live from OpenAlex

Global talent management (GTM) refers to management activities in a multinational enterprise (MNE) that focus on attracting, motivating, deploying, and retaining high performing and/or high potential employees in strategic roles across a firm's global operations. Despite the critical importance for individual and firm outcomes, scholarly analysis and understanding lack synthesis, and there is limited evidence that MNEs are managing their talent effectively on a global scale. In this article, we review the GTM literature and identify the challenges of implementing GTM in practice. We explore how GTM is aligned with MNE strategy, examine how talent pools are identified, and highlight the role of global mobility. We discuss GTM at the macro level, including the exogenous factors that impact talent management and the outcomes of GTM at various levels. Finally, we identify some emerging challenges and opportunities for the future of GTM.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.103
GPT teacher head0.451
Teacher spread0.348 · 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