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Record W3161036815 · doi:10.1057/s41267-021-00431-4

Trevino and Doh’s discourse-based view: Do we need a new theory of internationalization?

2021· article· en· W3161036815 on OpenAlexaff
Joshua K. Ault, Aloysius Newenham‐Kahindi, Sanjay Patnaik

Bibliographic record

VenueJournal of International Business Studies · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsInternationalizationSociologyFraming (construction)International businessEpistemologyRelevance (law)CounterpointNoveltyResource-based viewPositive economicsPolitical scienceEconomicsLawPsychologyManagementSocial psychologyEngineering

Abstract

fetched live from OpenAlex

Abstract This counterpoint examines the relevance of Trevino and Doh’s proposed new discourse-based view of internationalization for the field of International Business (IB). Trevino and Doh introduce their framework to address gaps in Internationalization Process Theory (IPT), which does not account for the underlying processes that lead to the initial managerial decision to internationalize. Framing our counterpoint around recent debates on how interdisciplinary research fields determine which new ideas to adopt, we explore whether the introduction of the discourse-based view adds sufficient novelty to justify the risk of fragmentation within IB. To stimulate debate around this question, we explore a number of issues, such as (1) whether the constructs found in the discourse-based view are distinct from pre-existing IB concepts, (2) the relative value of isolating the initial decision to internationalize within the broader internationalization process, and (3) the degree to which Trevino and Doh have isolated discourse as a primary mechanism driving the decision to internationalize. We conclude with a call for more dialog around the questions of how IB can embrace greater openness while still maintaining coherence and advancing collective knowledge.

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)0.002
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: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.291
Teacher spread0.264 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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