@inproceedings{6f2baea1cf0a4a53b6d5b53407f0e65d,
title = "Network structure and knowledge transfer",
abstract = "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.",
keywords = "Hierarchical network, Knowledge transfer, Scale-free network",
author = "Fangcheng Tang",
year = "2007",
doi = "10.1007/978-3-540-72590-9\_25",
language = "英语",
isbn = "9783540725893",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 4",
pages = "170--173",
booktitle = "Computational Science - ICCS 2007 - 7th International Conference, Proceedings",
address = "德国",
edition = "PART 4",
note = "7th International Conference on Computational Science, ICCS 2007 ; Conference date: 27-05-2007 Through 30-05-2007",
}