In the new era, China put forward "innovation-driven development" as a national development strategy. Technological development ultimately depends on talents to achieve. In order to accelerate the development of China’s science and technology, the government started a series of talents-introduction policies. When those talents returned to China, they had to overcome a variety of challenges to successfully gain scientific output.
Research is increasingly dependent on team to complete, and working in teams will form social networks. When those talents returned home, it was necessary to maintain contact with the former social network, but also to establish a new social network. Scientific Research must be done with continuity, but the mobility from their host countries to home countries caused changes to their social network. These changes will certainly affect their knowledge creation. Thus, the study of the relationship between social networks and the creation of knowledge was also essential.
In view of this, the present study took "Hundred Talents Program" of Chinese Academy of Sciences as an example, and then studied the impact of social networks and its changes on knowledge creation. We began with a study to explore whether social networks can affect knowledge creation. Then in the second study we focused on the specific mechanisms that social network influenced knowledge. In the second study, we specifically departed it in three issues, we firstly explored the relationship between structural and relational properties of social networks and knowledge creation; then, we were concerned that in the context of return mobility, whether the former social networks could predict their knowledge creation after returning; finally, we consider how changes in social networks impacted knowledge creation.
The dissertation found the self-report social network positively related with self-report knowledge creation and whether Outstanding Young was obtained. At the same time, network density and tie strength influenced knowledge creation from different aspects, specially, the network density negatively correlated with knowledge creation, and tie strength positively correlated with knowledge creation. In addition, in the context of return mobility, the network density before return could negatively predict knowledge creation after return, while the tie strength could not. Finally, the network changes influenced the knowledge creation, specially, the scientists with core network performed better than scientists without core network, and proportion of dropped ties negatively correlated with knowledge creation.
This study full explored the impact of social network and its changes on knowledge creation. The study not only explores the effects of structural property and relational property of social network on knowledge creation, but also studied the impact of former social network on latter knowledge creation in the context of return mobility. From a dynamic point, We also found network changes influenced knowledge creation. This study deepen our understanding of the relationship between social network and knowledge creation. In practice, this study could help policy makers to make talents introducing standard and gave advice to young talents on how to use social network to promote knowledge creation.