Expatriate networking and knowledge sharing
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».