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Record W2996584241 · doi:10.1002/sres.2658

From the deliberate managerial strategy towards international business performance: A psychic distance vs. global mindset approach

2019· article· en· W2996584241 on OpenAlexfundno aff
Elena‐Mădălina Vătămănescu, Vlad‐Andrei Alexandru, Andreea Mitan, Dan‐Cristian Dabija

Bibliographic record

VenueSystems Research and Behavioral Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
FundersOntario Ministry of Research, Innovation and Science
KeywordsMindsetInternationalizationPsychicStructural equation modelingVariance (accounting)International businessBusinessKnowledge managementPsychologyMarketingManagementComputer scienceEconomicsInternational tradeAccounting

Abstract

fetched live from OpenAlex

Abstract The current paper aims to address, within a comprehensive framework, two different facets of the internationalization strategies of small and medium‐sized enterprises, that is, the roles of psychic distance and global mindset within managerial dyadic collaborations. By considering cross‐border ventures as outcomes of deliberate managerial strategies in the quest for achieving international business performance, the study lays emphasis on several dimensions apposite to each of the two constructs, namely, geographic distance and intercultural compatibility for the psychic distance and trust‐based relationships and network‐based connectivity for the global mindset. A questionnaire‐based survey with top managers from 112 European industrial small and medium‐sized enterprises was conducted, the data being processed by means of a structural equation modelling technique. The findings showed that the structural model accounts for 63.9% of the variance in international business performance, whereas the dimensions of psychic distance exert significant positive influences on the endogenous variable.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.006
Scholarly communication0.0050.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.351
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations50
Published2019
Admission routes1
Has abstractyes

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