Robustness analysis and simulation of knowledge networks based on knowledge flows

In this paper, we develop an analyzing and evaluating robustness model of knowledge networks to capture the nature of robustness in the knowledge networks. We adopt 5 types of removing strategies based on knowledge flows to compare the robustness of knowledge networks, then analyze the robustness of knowledge networks under global and local information conditions. Simulation method was used to get the result of robustness of knowledge networks based on different removing strategies, different information conditions, and different degree of knowledge networks.

[1]  Henry C. W. Lau,et al.  A knowledge-based system to support procurement decision , 2005, J. Knowl. Manag..

[2]  Yamir Moreno,et al.  Dynamics of rumor spreading in complex networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  David A. McEntire,et al.  Why vulnerability matters: Exploring the merit of an inclusive disaster reduction concept , 2005 .

[4]  Beom Jun Kim,et al.  Attack vulnerability of complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Massimo Marchiori,et al.  Error and attacktolerance of complex network s , 2004 .

[6]  Ken G. Smith,et al.  Knowledge Exchange and Combination: The Role of Human Resource Practices in the Performance of High-Technology Firms , 2006 .

[7]  C. Huntley,et al.  Ramping up the Organizational Learning Curve: Assessing the Impact of Deliberate Learning on Organizational Performance Under Gainsharing , 2005 .

[8]  Adilson E Motter.  Cascade control and defense in complex networks. , 2004, Physical review letters.

[9]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[10]  Yan-zhong Dang,et al.  Method to Analyze Robustness of Knowledge Network based on Weighted Supernetwork Model and Its Application , 2007 .

[11]  Jessica Mesmer-Magnus,et al.  Information sharing and team performance: a meta-analysis , 2012 .

[12]  John Lane,et al.  IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries , 1991 .

[13]  Yong Li,et al.  ATTACK VULNERABILITY OF COMPLEX NETWORKS BASED ON LOCAL INFORMATION , 2007 .

[14]  Leslie A. DeChurch,et al.  Information sharing and team performance: a meta-analysis. , 2009, The Journal of applied psychology.

[15]  Dang Yan-zhong,et al.  The Method to Analyze the Robustness of Knowledge Network based on the Weighted Supernetwork Model and Its Application , 2007 .

[16]  D. Thurston,et al.  Modeling Robust and Reliable Supply Chains , 2003 .

[17]  E. L. Nichols,et al.  ORGANIZATIONAL LEARNING AS A STRATEGIC RESOURCE IN SUPPLY MANAGEMENT , 2003 .

[18]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[19]  Stilianos Vidalis,et al.  Measuring vulnerabilities and their exploitation cycle , 2003, Inf. Secur. Tech. Rep..

[20]  Robert E. Spekman,et al.  Supply Chain Competency: Learning as a Key Component , 2002 .