networks, innovation, tacit knowledge, pipes, knowledge pool, knowledge filter
Innovation requires inventors to have both "new knowledge" and the ability to combine and configure knowledge (i.e. "combinatory knowledge") and such knowledge may flow through networks. We argue that both combinatory knowledge and new knowledge are accessed through collaboration networks, but that inventors' abilities to access such knowledge depends on its location in the network. Combinatory knowledge transfers from direct contacts, but not easily from indirect contacts. In contrast, new knowledge transfers from both direct and indirect contacts, but is far more likely to be new and useful when it comes from indirect contacts. Exploring knowledge flows in 69,476 patents and 89,930 unique inventors reveals evidence that combinatory knowledge from direct contracts and new knowledge from indirect contacts significantly affects innovative performance.
Original Publication Citation
Singh, H., Kryscynski, D., Li, X. & Gopal, R. 2016. Pipes, Pools and Filters: How collaboration networks affect innovative performance. Strategic Management Journal. 37 (8): 1649-1666.
BYU ScholarsArchive Citation
Singh, Harpeet; Kryscynski, David; Li, Xinxin; and Gopal, Ram, "Pipes, Pools and Filters: How Collaboration Networks Affect Innovative Performance" (2016). All Faculty Publications. 1981.
Marriott School of Management
© 2016 Wiley. This is the peer reviewed version of the following article: Singh, H., Kryscynski, D., Li, X. & Gopal, R. 2016. Pipes, Pools and Filters: How collaboration networks affect innovative performance. Strategic Management Journal. 37 (8): 1649-1666., which has been published in final form at http://doi.org/10.1002/smj.2419 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."
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Available for download on Wednesday, August 01, 2018