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Record W4382460788 · doi:10.1002/tie.22359

An emerging market multinational Company's internationalization: From original equipment manufacturer to global brand leader

2023· article· en· W4382460788 on OpenAlexaff
Liu Su, Dwarka Chakravarty, Paul W. Beamish

Bibliographic record

VenueThunderbird International Business Review · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsWestern University
Fundersnot available
KeywordsMultinational corporationInternationalizationBusinessOriginal equipment manufacturerMarketingBrand equityReputationEmerging marketsBrand managementChinaCompetitive advantageIndustrial organizationInternational trade

Abstract

fetched live from OpenAlex

Abstract We examine an emerging market multinational company's (EMNC's) transformation from an original equipment manufacturer (OEM) to an original brand manufacturer (OBM) and global leader. Our longitudinal study of Hisense—China's largest TV company (and the world's third largest) spans three decades and involves detailed interviews with over 50 executives. We study how the company's global value chain network evolved, how it reconfigured its organization, upgraded its capabilities, and enhanced its brand reputation. We develop propositions that may contribute to improved explanations for an EMNC's internationalization sequence, development of competitive advantages, overseas management practices, and brand building.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.005

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 head0.039
GPT teacher head0.324
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations14
Published2023
Admission routes1
Has abstractyes

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