Expatriate Management of Emerging Market Multinational Enterprises: A Multiple Case Study Approach
Bibliographic record
Abstract
Expatriate management has evolved through the practices of developed economy multinational enterprises (DMNEs), with the aim of improving expatriate adaptability, cross-cultural adjustment, and performance. However, most of these studies focus on expatriates from developed countries and try to help DMNEs instead of emerging market MNEs (EMNEs). In a turbulent global economy, how EMNEs manage their expatriates when conducting business through their outward foreign direct investment (FDI) is understudied. This empirical study aims to address this research gap by utilising a qualitative approach and a multiple case study. It has conducted semi-structured interviews with expatriates, executives, and middle managers of Chinese MNEs in 2014. It contributes as one of the few to systematically examine expatriate related issues in the context of EMNEs with first-hand empirical evidence. The findings show that EMNEs are leapfrogging with their internationalisation and hence their expatriate policies are often ad hoc without systematic planning. Moreover, this study has contributed to practice, especially to EMNEs, regarding the way they need to improve their expatriate policies and practices.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".