DocumentCode
2437886
Title
Notice of Retraction
Network and Organizational Learning: The Effect of Structure and Tie Strength
Author
Liefa Liao ; Kanliang Wang
Author_Institution
Dept. of Comput. Sci., JiangXi Univ. of Sci. & Technol., Ganzhou, China
fYear
2010
fDate
7-9 May 2010
Firstpage
1860
Lastpage
1863
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Using simulation research method, this research considers how different network configuration influences the organizational learning performance. As a complement to previous research that has focused on only one feature of network structure. We propose that network density and ties strength affect exploration and exploitation learning by influencing knowledge diffusion speed and knowledge diversity in network. The simulation result demonstrates that density network structure and strength ties positively relate to network exploitation learning, the density of a network is less positively related to long organizational learning performance when the network has high ties strength than when the network has low ties strength. We discuss the implications in the end.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Using simulation research method, this research considers how different network configuration influences the organizational learning performance. As a complement to previous research that has focused on only one feature of network structure. We propose that network density and ties strength affect exploration and exploitation learning by influencing knowledge diffusion speed and knowledge diversity in network. The simulation result demonstrates that density network structure and strength ties positively relate to network exploitation learning, the density of a network is less positively related to long organizational learning performance when the network has high ties strength than when the network has low ties strength. We discuss the implications in the end.
Keywords
knowledge management; organisational aspects; knowledge diffusion; knowledge diversity; network configuration; network density; network exploitation learning; network structure; organizational learning; tie strength; Adaptation model; Complexity theory; Economics; Knowledge engineering; Knowledge transfer; Organizations; Simulation; network structure; network ties strength; organizational learning; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3997-3
Type
conf
DOI
10.1109/ICEE.2010.470
Filename
5592744
Link To Document