Expatriate networking and knowledge sharing
Bibliographic record
Abstract
This thesis focuses on expatriates’ assignments. How have they realized knowledge exchange? What kind of networking ties have they been able to build while living in the host country? How have they been able to utilize what they learned after their return, and how did the expatriate experience change their later work career? The theoretical background section of the thesis consists of three main areas: socio-cultural perspective on learning, particularly regarding knowledge exchange and expertise development, expatriate research, and expatriates’ personal network ties (referred to also as “ego-centric networks”). Two surveys, before (n=104) and after (n=63) the assignment, were used in gathering the data. In addition, ego-centric network interviews (n=16) were conducted three times during the assignment, and an open-ended delayed email survey (n=11) was conducted. Consequently, a mixed method approach was applied. Ego-centric network data focused on social contact construction, whereas pre- and post-questionnaires targeted to analyze themes of general interest in expatriate and repatriate process, such as individual level attributes of participants, background information of company level practices, knowledge sharing aims, effect of local culture, and repatriation experiences. The delayed open-ended questionnaire was sent to the participants that took part in ego-centric network data gathering, twenty years after the research started. The aim of the delayed measure was to investigate later career development and the experienced effects of the expatriate period on their life after the assignment. The company, Nokia, where this research study was carried out, is a big international, Finnish-based company. The expatriates in the present study left for an international assignment between the years 2000 and 2001. Host countries were Brazil, Canada, China, Denmark, Germany, Hungary, Hong Kong, Italy, Japan, Malaysia, Singapore, South Korea, United Kingdom and United States. According to the results, expatriate assignment enabled the participants’ learning experiences which improves their personal characteristics and human capital. Learning and development outcomes seemed to be more personal than professional in nature. The results indicate firstly that the respondents showed high satisfaction in reaching the targets at work, secondly, cultural effects were even stronger than expected. As conclusion, the repatriate phase was a positive experience for the respondents. It was beneficial for them, both at work and in their personal life. The expatriates mainly agreed that they are willing to share their knowledge and expertise gained during the assignment, although everyone was not satisfied after returning to their home country. The transfer of knowledge after returning was not optimally organized. Every fifth respondent commented that the company was not interested in their new knowledge, or not supporting in searching for a new position. The findings of the delayed measure showed that effective networking during the assignment gave the best qualifications for successful work in international and global environments after the assignment.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".