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Record W2784946951 · doi:10.1108/ribs-09-2017-0077

The role of knowledge in international expansion

2018· article· en· W2784946951 on OpenAlexaff
Daniel Gulanowski, Nicolas Papadopoulos, Llynne Plante

Bibliographic record

VenueReview of International Business and Strategy · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsCarleton University
Fundersnot available
KeywordsInternationalizationOriginalityConstruct (python library)Theme (computing)Value (mathematics)EpistemologySociologyManagement sciencePolitical scienceComputer scienceSocial scienceQualitative researchEconomics

Abstract

fetched live from OpenAlex

Purpose This paper aims to critically review and integrate the literature available on Uppsala (incremental) and Born Global (rapid) internationalization models and propose an integrative model that applies to both the initial and subsequent stages in internationalization. Design/methodology/approach This study draws on a systematic review and analysis of the relevant literature, using 87 articles from 28 journals which deal with the Uppsala and/or Born Global conceptualizations. Findings To date, the two views of internationalization have been presented as competing and fundamentally different explanations, as past research focuses mostly on the original 1977 Uppsala model without accounting for its five subsequent extensions (1990-2013) and not considering in sufficient depth the critical role of the knowledge construct in both models. Research limitations/implications The study focuses on English-only publications dealing expressly with the Born Global and Uppsala models; while some studies which address the focal theme tangentially may have been missed, the systematic approach to identifying the key studies of interest and the focus on a carefully delineated research domain provides confidence that the main studies relevant to the theme have been captured. Originality/value The study highlights the important role of knowledge in the internationalization of firms, and it addresses the current divide between the “incremental” and “rapid” conceptualizations which have impeded the development of theory, by positing six research propositions and an integrative model that accounts for both the incremental and rapid approaches.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.640
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.272
Teacher spread0.257 · 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 designTheoretical or conceptual
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

Citations41
Published2018
Admission routes1
Has abstractyes

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