Network Structure and Knowledge Transfer

This study employs single layer perceptron model (SLPM) to explore how the topological structure of intra-organization networks affects knowledge transfer. The results demonstrate that in the process of knowledge transfer, both the disseminative capacity of knowledge senders and the absorptive capacity of knowledge receivers should be taken into consideration. While hierarchical networks can enable greater numbers of organizational units to acquire knowledge, they reduce the speed and efficiency of knowledge transfer, whereas scale-free networks can accelerate transfer of knowledge among units.

[1]  E. Hippel.  Sticky Information and the Locus of Problem Solving: Implications for Innovation , 1994 .

[2]  R. Palmer,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

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

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

[5]  B. Uzzi,et al.  Social Structure and Competition in Interfirm Networks: The Paradox of Embeddedness , 1997 .

[6]  J. Coleman.  Foundations of Social Theory , 1990 .

[7]  Linda Argote,et al.  Managing Knowledge in Organizations: An Integrative Framework and Review of Emerging Themes , 2003, Manag. Sci..

[8]  R. Burt.  The Social Structure of Competition , 2004 .

[9]  L. A. Goodman,et al.  The analysis of cross-classified data having ordered categories , 1985 .

[10]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[11]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[12]  K. Arrow.  The limits of organization , 1974 .

[13]  F. Heider.  The psychology of interpersonal relations , 1958 .

[14]  H. Simon.  Bounded Rationality and Organizational Learning , 1991 .

[15]  E. Rogers.  Diffusion of Innovations , 1962 .

[16]  A. Barabasi,et al.  Scale-free characteristics of random networks: the topology of the world-wide web , 2000 .

[17]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[18]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.