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Record W4225623395 · doi:10.1111/joms.12817

A Blessing and a Curse: Institutional Embeddedness of Longstanding MNE Subsidiaries in Emerging Markets

2022· article· en· W4225623395 on OpenAlexaff
Christiaan Röell, Félix Arndt, Vikas Kumar

Bibliographic record

VenueJournal of Management Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEmbeddednessSubsidiaryMultinational corporationExpatriateBusinessInstitutional theoryEmerging marketsPoliticsEconomic systemEconomicsSociologyPolitical scienceManagement

Abstract

fetched live from OpenAlex

Abstract This article examines the institutional strategies of multinational enterprises (MNEs) operating in an emerging market, drawing attention to how longstanding foreign subsidiaries proactively negotiate their involvement with socio‐political actors. We build on institutional logics to explain how MNE subsidiaries develop sustained political, cultural, and cognitive embeddedness. Using an inductive, interpretive study of four century‐old Dutch MNE subsidiaries with a colonial legacy in Indonesia, we examine these three dimensions of the institutional environment, finding that local employees embedded in both the MNE and the host country sets of logics ‒ rather than expatriate managers ‒ most effectively facilitated sustained institutional embeddedness. Our findings also suggest that embedding practices in host institutional contexts and developing structures that align with host institutional expectations provided a platform for the unfolding of institutional strategies by local employees. However, MNE subsidiaries face contrasting logics between home and host country institutions, placing significant strains on MNEs’ ability to enact change.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.523
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.027
GPT teacher head0.278
Teacher spread0.250 · 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 teacher head, 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

Citations49
Published2022
Admission routes1
Has abstractyes

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