Abstract
Purpose - In this paper we focus on the process of knowledge transfer within social networks composed of a pool of experts, and new comers whose aim is primarily to acquire new knowledge, such as communities of practice. We wish to understand which communication system and which information about others’ knowledge should be provided to get to a better diffusion of knowledge. Design/methodology/approach - We use agent-based models and social network analysis and run many simulations in which we vary communication mode and information about others’ knowledge. Findings - Results emphasize the part played by new comers in the process of direct knowledge transfer. They constitute additional sources of knowledge and act as intermediaries. Results also show that in a process of indirect transfer of knowledge, they have only little influence on the process of individual learning. Practical implications - These results enable us to formulate some recommendations to facilitate knowledge transfer within a knowledge intensive community. Nonhierarchical structures of communication should be preferred and the participation of new comers in the activities of the community fully encouraged. Originality/value - This paper combines agent-bases modelling and social networks analysis to investigate the field of knowledge transfer and enables us to identify the key elements in the process of knowledge diffusion within a community of practice. It thus provides some solution to eventual congestion problems in the access to the knowledge held within the community.
Purpose - In this paper we focus on the process of knowledge transfer within social networks composed of a pool of experts, and new comers whose aim is primarily to acquire new knowledge, such as communities of practice. We wish to understand which communication system and which information about others’ knowledge should be provided to get to a better diffusion of knowledge. Design/methodology/approach - We use agent-based models and social network analysis and run many simulations in which we vary communication mode and information about others’ knowledge. Findings - Results emphasize the part played by new comers in the process of direct knowledge transfer. They constitute additional sources of knowledge and act as intermediaries. Results also show that in a process of indirect transfer of knowledge, they have only little influence on the process of individual learning. Practical implications - These results enable us to formulate some recommendations to facilitate knowledge transfer within a knowledge intensive community. Nonhierarchical structures of communication should be preferred and the participation of new comers in the activities of the community fully encouraged. Originality/value - This paper combines agent-bases modelling and social networks analysis to investigate the field of knowledge transfer and enables us to identify the key elements in the process of knowledge diffusion within a community of practice. It thus provides some solution to eventual congestion problems in the access to the knowledge held within the community.