Managerial mindset effects on international marketing strategy adaptation decisions
Bibliographic record
Abstract
This research investigates how managerial implicit theories—people's implicit beliefs about the malleability of human characteristics—affect international marketing strategy adaptation decisions among B2B exporting managers. Building on mindset theory and the international marketing literature, we hypothesize that managers with a growth mindset will opt for higher levels of marketing strategy adaptation while fixed-mindset managers, who believe in the immutability of human traits, will likely standardize across markets. Across two experimental studies that manipulate mindset, we test these hypotheses and their underlying mechanism and boundary conditions. The results of Study 1 show that mindset affects lifestyle adaptation intentions for individuals in general, thus establishing the baseline relationship. Study 2 finds that business-to-business international marketing managers exposed to a growth (fixed) mindset are indeed more likely to adapt (standardize) their international marketing strategy toward foreign markets. We further show that mindset affects ambiguity tolerance, which in turn affects adaptation decisions, and that the effect of mindset is dampened (strengthened) under low (high) psychic distance conditions. This research enriches the international marketing literature by showing a managerially relevant antecedent of international marketing strategy adaptation decisions and extends implicit theory by showing a behavioral outcome of mindset.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".