Modelling and simulating knowledge diffusion in knowledge collaboration organisations using improved cellular automata

ABSTRACT Knowledge diffusion plays a vital role for the success of knowledge collaboration organisation (KCO). From the view of micro knowledge exchange activities, this paper aims to study the process and rule of knowledge diffusion in KCO. First, consulting the SEIR epidemic propagation model, this paper divides the individuals into different knowledge statuses, and depicts the process of knowledge diffusion. Considering the influence of individual heterogeneity and mobility on knowledge diffusion, this paper develops an improved cellular automata model with heterogeneity and mobility to study the knowledge diffusion in KCO. By using simulation method, we study the impacts of the distribution pattern of initial knowledge disseminator, knowledge accessibility among individuals, individual mobility and knowledge quitting rate on knowledge diffusion performance. The results reveal some valuable enlightenments about how to improve the knowledge diffusion performance in KCO, which are helpful to the managers to carry out knowledge management strategies and actions.

[1]  Luiz Antonio Joia,et al.  Relevant factors for tacit knowledge transfer within organisations , 2010, J. Knowl. Manag..

[2]  Gong Xiao-guang.  Tacit Knowledge Diffusion in Organizational Networks and the Analysis of Learning Strategies , 2009 .

[3]  Julia Nieves,et al.  Organizational knowledge and collaborative human resource practices as determinants of innovation , 2016 .

[4]  Stephen Wolfram,et al.  Cellular automata as models of complexity , 1984, Nature.

[5]  Anne-Marie Kermarrec,et al.  Epidemic information dissemination in distributed systems , 2004, Computer.

[6]  Jasjit Singh,et al.  Collaborative Networks as Determinants of Knowledge Diffusion Patterns , 2005, Manag. Sci..

[7]  Keng-Boon Ooi,et al.  Can competitive advantage be achieved through knowledge management? A case study on SMEs , 2016, Expert Syst. Appl..

[8]  S. Roper,et al.  Firms’ knowledge search and local knowledge externalities in innovation performance , 2017 .

[9]  M. Fritsch,et al.  The impact of network structure on knowledge transfer: an application of social network analysis in the context of regional innovation networks , 2010 .

[10]  Daniel A. Levinthal,et al.  ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION , 1990 .

[11]  Weidong Zhu,et al.  An integrated theoretical model for determinants of knowledge sharing behaviours , 2012, Kybernetes.

[12]  Donald E. Knuth,et al.  Breaking paragraphs into lines , 1981, Softw. Pract. Exp..

[13]  Mark S. Demarest.  Understanding knowledge management , 1997 .

[14]  Douglas L. MacLachlan,et al.  Absorptive and disseminative capacity: knowledge transfer in intra-organization networks , 2012, IEEE Engineering Management Review.

[15]  Zhao Xiao-yi.  A Research on the Model of Knowledge Transfer Based on System Dynamics in the Enterprise , 2008 .

[16]  Yu Yang,et al.  Measurement of knowledge diffusion efficiency for the weighted knowledge collaboration networks , 2017, Kybernetes.

[17]  Morten T. Hansen,et al.  The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits , 1999 .

[18]  Wu Hong-mei.  Multi-agent model of knowledge diffusion in network space , 2003 .

[19]  刘建国,et al.  Improved knowledge diffusion model based on the collaboration hypernetwork , 2015 .

[20]  Khalid Hattaf,et al.  Three-Dimensional Cellular Automaton for Modeling the Hepatitis B Virus Infection , 2014 .

[21]  Yongtae Park,et al.  Structural effects of R&D collaboration network on knowledge diffusion performance , 2009, Expert Syst. Appl..

[22]  Tua Haldin-Herrgård,et al.  Difficulties in diffusion of tacit knowledge in organizations , 2000 .

[23]  H. Balzter,et al.  Cellular automata models for vegetation dynamics , 1998 .

[24]  Bülent Özel.  Collaboration structure and knowledge diffusion in Turkish management academia , 2012, Scientometrics.

[25]  Ray Reagans,et al.  Network Structure and Knowledge Transfer: The Effects of Cohesion and Range , 2003 .

[26]  Fang Zhiping.  A Partner Selection Method for Knowledge Creation Team Based on Collaborative Effect , 2012 .

[27]  Ismael Rafols,et al.  Can epidemic models describe the diffusion of topics across disciplines? , 2009, J. Informetrics.

[28]  L. Liu,et al.  SIMULATION OF CONFLICT CONTAGION IN CUSTOMER COLLABORATIVE PRODUCT INNOVATION , 2015 .

[29]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[30]  D. I. Iudin,et al.  Infinity computations in cellular automaton forest-fire model , 2015, Commun. Nonlinear Sci. Numer. Simul..

[31]  Tan Xin-xi.  CA-based epidemic propagation model with inhomogeneity and mobility , 2013 .

[32]  D. Gilmour,et al.  How to Fix Knowledge Management , 2003 .

[33]  Chih-Ming Tsai,et al.  Integrating intra-firm and inter-firm knowledge diffusion into the knowledge diffusion model , 2008, Expert Syst. Appl..

[34]  Bulent Ozel.  Collaboration structure and knowledge diffusion in Turkish management academia , 2012 .

[35]  Md. Haider Ali Biswas,et al.  A SEIR model for control of infectious diseases with constraints , 2014 .

[36]  S. Zahra,et al.  Absorptive Capacity: A Review, Reconceptualization, and Extension , 2002 .

[37]  K. Eloranta.  Random walks in cellular automata , 1993 .

[38]  Alberto Carneiro,et al.  How does knowledge management influence innovation and competitiveness? , 2000, J. Knowl. Manag..

[39]  Mohd Sapiyan Bin Baba,et al.  Information security - Professional perceptions of knowledge-sharing intention under self-efficacy, trust, reciprocity, and shared-language , 2013, Comput. Educ..

[40]  Joon Koh,et al.  An Integrative Model for Knowledge Sharing in Communities-of-Practice , 2011, J. Knowl. Manag..

[41]  Anthony Wensley,et al.  Overcoming knowledge loss through the utilization of an unlearning context , 2015 .

[42]  Mariangela Guidolin,et al.  Modelling a dynamic market potential: A class of automata networks for diffusion of innovations , 2009 .