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Record W3194868905 · doi:10.1108/mbr-11-2020-0210

The death of distance, revisited: disseminative capacity and knowledge transfer

2021· article· en· W3194868905 on OpenAlexaff
Chansoo Park

Bibliographic record

VenueMultinational Business Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTacit knowledgeKnowledge transferInternational joint ventureOriginalityKnowledge managementExplicit knowledgeAbsorptive capacityValue (mathematics)Empirical researchPsychologyBusinessEmpirical evidenceSocial psychologyComputer scienceJoint ventureMathematicsBusiness administrationStatisticsCreativityEpistemology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to assess how the transfer of explicit and tacit knowledge is affected by the knowledge disseminative capacity of a foreign parent firm, with an emphasis on the moderating role of psychic distance, by developing and testing a theoretical model of international joint venture (IJV) learning. Design/methodology/approach The author tested the hypotheses with survey data collected from 199 IJVs in South Korea, estimating a structural equation model using AMOS 23.0. Findings The author found that the capacity of the foreign parent to disseminate knowledge to the IJV has a greater impact on explicit knowledge transfer than tacit knowledge transfer. He also found that the relationship between disseminative capacity and explicit knowledge transfer is significantly moderated by psychic distance, but the relationship between disseminative capacity and tacit knowledge transfer is not. Originality/value The results are critical for IJVs and parent firms seeking to improve knowledge transfer, as they establish the importance of parent firms’ disseminative capacities and the moderating role of psychic distance in the process of both tacit and explicit knowledge transfer. This research addresses the research gap regarding disseminative capacity by providing empirical evidence.

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)0.001
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: Review · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.277
Teacher spread0.245 · 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
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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