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Change of Subsidiary Mandates in Emerging Markets: The Case of Danish MNCs in India

2011· article· en· W626095296 on OpenAlexvenueno aff
Michael W. Hansen, Bent Petersen, Peter Wad

Bibliographic record

VenueTransnational Corporation Review · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsMandateSubsidiaryMultinational corporationDanishBusinessEmerging marketsIndustrial organizationEconomic geographyMarket economyEconomicsPolitical scienceFinanceLaw

Abstract

fetched live from OpenAlex

In recent years, the activities of Danish MNCs in India have expanded dramatically. Previously dormant subsidiaries have been transformed into integral components in the global strategies of Danish MNCs, either as crucial cash cows catering to the rapidly growing Indian markets, or as platforms for sourcing of increasingly advanced value chain activities. This paper aims to provide an understanding of the relationship between changes in the Indian business environment and mandate trajectories of Danish subsidiaries in India. A review of the literature on subsidiary mandates reveals that it largely fails to conceptualize how the specificities of emerging market business environments affect subsidiary mandate evolution. The paper develops a theoretical model for business environment change influence on subsidiary mandates, and demonstrates how the model can capture much of recent years dramatic mandate change of Danish subsidiaries in India.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.263
Teacher spread0.201 · 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 designObservational
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

Citations7
Published2011
Admission routes1
Has abstractno

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