Abstract
Purpose - The aim of this paper is to develop a metric that quantitatively measures the risk of knowledge drain associated with the departure of a member in communities of practice (CoP).Design/methodology/approach - This paper considers two possible cases in which departure of a member has a high risk of causing knowledge drain: when the member is a network leader, and when the member is an isolated expert. Network analysis is used to identify network influence of each member. The proposed metric is designed considering network influence and knowledge level of individual members, and applied to a case study using real-world data from an online CoP.Findings - This paper demonstrates that the proposed metric properly provides information about the members whose departure could cause serious damage to the CoP because of their strong influence or their inactivity in the network. The metric enables practitioners to identify critical members, and to enact precautions to reduce the vulnerability of the CoP.Originality/value - Compared to the threat of knowledge drain, few studies have attempted to measure the risk associated with departure of a member. This study has developed a metric to measure the risk of knowledge drain in a CoP. The approach and methods of this paper offer a foundation for designing assessment methods for knowledge networks and provide new insights into quantitative research in knowledge management.
Purpose - The aim of this paper is to develop a metric that quantitatively measures the risk of knowledge drain associated with the departure of a member in communities of practice (CoP).Design/methodology/approach - This paper considers two possible cases in which departure of a member has a high risk of causing knowledge drain: when the member is a network leader, and when the member is an isolated expert. Network analysis is used to identify network influence of each member. The proposed metric is designed considering network influence and knowledge level of individual members, and applied to a case study using real-world data from an online CoP.Findings - This paper demonstrates that the proposed metric properly provides information about the members whose departure could cause serious damage to the CoP because of their strong influence or their inactivity in the network. The metric enables practitioners to identify critical members, and to enact precautions to reduce the vulnerability of the CoP.Originality/value - Compared to the threat of knowledge drain, few studies have attempted to measure the risk associated with departure of a member. This study has developed a metric to measure the risk of knowledge drain in a CoP. The approach and methods of this paper offer a foundation for designing assessment methods for knowledge networks and provide new insights into quantitative research in knowledge management.