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Record W4414822746 · doi:10.1016/j.ibusrev.2025.102521

Heuristics and decision rationality in entry mode choice: Implications for decision effectiveness and international performance

2025· article· en· W4414822746 on OpenAlexaff
Anisur R. Faroque, Arafat Rahman, Mohammad Osman Gani, Imranul Hoque

Bibliographic record

VenueInternational Business Review · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity Canada West
Fundersnot available
KeywordsHeuristicsRationalityMode (computer interface)Decision theoryDecision analysisDecision support systemEvidential reasoning approachDecision model

Abstract

fetched live from OpenAlex

This study explores how heuristics (availability and representativeness) and analytic rational decision-making influence the selection of international business entry modes and their subsequent impact on decision effectiveness and international performance. Grounded in dual-process theories, the research develops hypotheses linking heuristics, analytic rationality, decision effectiveness, and international outcomes. Utilizing a quantitative survey approach, the findings reveal that integrating the availability heuristic with analytic rational decision-making enhances the quality of internationalization decisions, whereas combining analytic decision-making with the representativeness heuristic can diminish decision effectiveness. These results emphasize the critical role of balancing heuristic and analytical approaches in managerial decision-making for international entry, contributing to dual-process theories within the international business context and providing valuable insights into the cognitive strategies shaping entry mode selection and organizational performance.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.344
Teacher spread0.322 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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