Limitations of network analysis for studying efficiency and effectiveness of knowledge sharing

To identify possible deficiencies in knowledge sharing several authors proposed to apply a network perspective. In this perspective, the knowledge transfer relations between people are studied. The proposition in these researches is that the position of an individual in a network or the specific clustering of people into groups serves as an indicator concerning the efficiency or effectiveness of knowledge sharing. However, previous research learned that a network perspective might not reveal all deficiencies as it mainly focuses on the tacit dimension of knowledge. In this research, we seek to validate one of the network approaches to study the tacit dimension of knowledge sharing, which is called Knowledge Network Analysis. To validate the Knowledge Network Analysis technique we conducted a case study, at an international product software supplier. A knowledge network analysis was conducted and the outcome of this analysis is compared with a qualitative study based on interviews and direct observations that focused on the tacit as well as the explicit dimension of knowledge. To analyze the qualitative data we developed a new model called Knowledge Sharing Environment Model (KSEM), which is capable of identifying and quantifying knowledge sharing bottlenecks. A total of eight bottlenecks identified by KNA were analyzed by means of the KSEM. Hence, six out of eight bottlenecks were validated. This case study demonstrates that Knowledge Network Analysis is a good tool for the identification of bottlenecks. However, it was suggested to combine the Knowledge Network Analysis with another research method such as the KSEM to validate and study the causes behind the identified bottlenecks.