Intrinsic motivation for an international assignment
Bibliographic record
Abstract
Purpose This study aims to explore how the motivational construct of intrinsic motivation for an international assignment relates to variables of interest in international expatriation research. Design/methodology/approach Questionnaire data from 331 employed business school alumni of a high‐ranking Canadian MBA program was analyzed. The sample consisted of respondents from a wide variety of industries and occupations, with more than half of them in marketing, administration or engineering. Findings Higher intrinsic motivation for an international assignment was associated with greater willingness to accept an international assignment and to communicate in a foreign language. Externally driven motivation for an international assignment was associated with perceiving more difficulties associated with an international assignment. Intrinsic and extrinsic motivations for an international assignment were, however, associated with comparable reactions to organizational support. Originality/value Drawing from self‐determination theory, this study explores the distinction between authentic versus externally controlled motivations for an international assignment. It underscores the need to pay more attention to motivational constructs in selecting, coaching, and training individuals for international expatriation assignments. It extends a rich tradition of research in the area of motivation to the international assignment arena.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".