Knowledge exchange between expatriates and host country nationals: an expectancy value perspective
Bibliographic record
Abstract
Purpose Drawing on expectancy value theory (EVT), this paper examines knowledge exchange between expatriate and host country national (HCN) dyads to understand whether receivers' perceptions about senders' motivation to transfer knowledge and perceived value of the knowledge jointly affect receivers' motivation to learn and, in turn, facilitate their knowledge acquisition and sharing. Design/methodology/approach Latent moderated structural (LMS) equations were used to analyze data from 107 expatriate–HCN dyads working in the Asia Pacific region. Findings In general, whether senders are expatriates or HCNs, only when receivers perceive that (1) knowledge to be transferred is valuable and (2) senders are motivated to transfer, receivers are likely to be motivated to receive knowledge transferred from senders and, in turn, acquire and share knowledge with senders. Originality/value This study is one of the first in the expatriate and knowledge transfer literature to address the mixed findings between senders' motivation to transfer and receivers' knowledge acquisition and sharing by drawing on EVT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".