By Gianluca Carnabuci
Why do yes domain names of human wisdom enhance quicker than others? This thesis units out to reply to this query through elaborating upon the idea that new rules spring from hybridizations of present rules. over the years, such hybridizations shape a path-dependent community constitution of interconnected and interconnecting wisdom domain names. This thesis develops a network-analytic method of version this constitution and to enquire its results. according to all technological wisdom patented within the usa among 1975 and 1999, this thesis demonstrates that the community place a data area is embedded in at a given time limit impacts its next development clients in vital and predictable methods.
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Extra info for A Theory of Knowledge Growth
Second, there are 418 primary patent classes, which is a large yet manageable number of units. Following the literature on knowledge spillovers, I interpret patent citations as paper trails of hybridizations. Citations between patents form a directed, unweighted, acycilc network. This means that a tie from node i to node j implies the absence of a tie from j to i (previous patents cannot cite subsequent patents); and, that there is no difference in the strength of ties (a patent either cites Patent-based indicators and the analysis of knowledge growth 27 another patent or it does not).
6 Mean citations made and received by application year Source: adapted from Hall et al. 8 Mean citations made by technological area and application year Source: adapted from Hall et al. 9 show, respectively, the average number of citations made and received by technological categories. The figures reveal that the technological areas Chemicals & Mechanical tend to cite more while receiving fewer citations, especially if compared to the emerging areas of Computer & Communications and Drugs & Medical.
Although in general there is no reason to overlook the role of these ties, their presence sometimes obscures the strong-tie backbone structure of the network. This is certainly the case when networks are investigated by visual inspection, as I do in this section. 00061 % of all citation made. 52 Characterizing the network structure of US-patented knowledge To visualize the knowledge hybridization network I use NetDraw1 (Borgatti 2002), a freeware software downloadable from the Web2. NetDraw1 employs a spring-embedded drawing algorithm to represent network data in twodimensional Euclidian space: while nodes repel one another, network ties act as springs that draw connected nodes closer together.