R. Cowan, N. Jonard, and M. Özman. Technological Forecasting and Social Change, 71 (5):
469-484(2004/6)
Abstract
In this paper, we model the impact of networks on knowledge growth
in an innovating industry. Specifically, we compare two mediums of
knowledge exchange: random interaction, and the case in which interaction
occurs on a fixed architecture. In a simulation study, we investigate
how the medium of knowledge exchange contributes to knowledge growth
under different scenarios related to the industry's innovative potential.
We measure innovative potential by considering the extent to which
knowledge can be codified, and the available technological opportunities.
Our results tend to support the conjecture that spatial clustering
generates higher long-run knowledge growth rates in industries characterized
by highly tacit knowledge, while the opposite is true when the degree
of codification is important.
%0 Journal Article
%1 Cowan2004/6
%A Cowan, Robin
%A Jonard, Nicolas
%A Özman, Müge
%D 2004/6
%J Technological Forecasting and Social Change
%K Clustering; Innovation; Knowledge Network Network; industry;
%N 5
%P 469-484
%T Knowledge dynamics in a network industry
%V 71
%X In this paper, we model the impact of networks on knowledge growth
in an innovating industry. Specifically, we compare two mediums of
knowledge exchange: random interaction, and the case in which interaction
occurs on a fixed architecture. In a simulation study, we investigate
how the medium of knowledge exchange contributes to knowledge growth
under different scenarios related to the industry's innovative potential.
We measure innovative potential by considering the extent to which
knowledge can be codified, and the available technological opportunities.
Our results tend to support the conjecture that spatial clustering
generates higher long-run knowledge growth rates in industries characterized
by highly tacit knowledge, while the opposite is true when the degree
of codification is important.
@article{Cowan2004/6,
abstract = {In this paper, we model the impact of networks on knowledge growth
in an innovating industry. Specifically, we compare two mediums of
knowledge exchange: random interaction, and the case in which interaction
occurs on a fixed architecture. In a simulation study, we investigate
how the medium of knowledge exchange contributes to knowledge growth
under different scenarios related to the industry's innovative potential.
We measure innovative potential by considering the extent to which
knowledge can be codified, and the available technological opportunities.
Our results tend to support the conjecture that spatial clustering
generates higher long-run knowledge growth rates in industries characterized
by highly tacit knowledge, while the opposite is true when the degree
of codification is important.},
added-at = {2008-08-31T18:03:07.000+0200},
author = {Cowan, Robin and Jonard, Nicolas and Özman, Müge},
biburl = {https://www.bibsonomy.org/bibtex/23964282e54d48c6c97f64addbae156ef/jomiralb},
description = {Old biblio},
interhash = {896d3848ca33364fabbfbaa789eb5357},
intrahash = {3964282e54d48c6c97f64addbae156ef},
journal = {Technological Forecasting and Social Change},
keywords = {Clustering; Innovation; Knowledge Network Network; industry;},
number = 5,
owner = {oriol},
pages = {469-484},
timestamp = {2008-08-31T18:03:11.000+0200},
title = {Knowledge dynamics in a network industry},
volume = 71,
year = {2004/6}
}