دانلود رایگان مقاله انگلیسی تحلیل شبکه پیچیده برای مدیریت دانش و هوش سازمانی - اشپرینگر 2018

Abstract

The scope and focus of knowledge management has changed multiple times over the last decades, each shift revealing new challenges to management science. Recent change of perspective drawing from systems thinking is suggesting that knowledge is created through interaction between people. Complex network analysis is a rigorous method that can be used for evaluation of interaction patterns between employees. The literature suggests that specific interaction patterns are related to increased knowledge flow, innovativeness, and performance. Aim of this paper is to provide an overview of various approaches utilizing the complex network analysis in organizations and present suggestions that might support managerial decision-making processes related to knowledge management and organizational intelligence.

Conclusion

In this article, we present multiple approaches utilizing the complex network analysis in organization aimed on inspection of processes related to knowledge management. Based on that, we attempted to formulate suggestions that might be used as a support for managerial decisions and strategy making that would foster knowledge flow, innovativeness, and performance of a company. Innovativeness and performance of employees are based on quality of their interaction; therefore, complex network analysis is a highly suitable tool as it provides methods for inspecting the nature of interacting systems. Analyzing complex networks can provide understanding and insights about qualities and interaction patterns of cooperating employees that would be otherwise very hard to obtain. On the other hand, it is a quantitative method, reflecting upon certain aspects of reality and discarding others. Application of proposed suggestions has to be combined with respect to particular company and people that is the network representing. It is advisable to combine insights from network analysis with other quantitative or qualitative methods and expert decisions in order to achieve desired results. Throughout the text, it was suggested that connecting different parts of network should increase the knowledge flow. On the other hand, supporting the creation of new connections must make sense—it should link people or teams that would benefit from that contact. The architecture of connections matters therefore creating random or collective connections might not end up in the desired outcome (Cowan and Jonard 2004). This argument also supports the need for sensitive combination of network analysis, suitable qualitative methods, and qualified decisions.