By Gianluca Carnabuci
Why do definite domain names of human wisdom increase swifter than others? This thesis units out to respond to this query through elaborating upon the concept that new principles spring from hybridizations of present principles. through 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. in line with all technological wisdom patented within the usa among 1975 and 1999, this thesis demonstrates that the community place an information area is embedded in at a given time limit impacts its next development customers in very important and predictable methods.
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Extra info for A Theory of Knowledge Growth
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. The difference in citations received is striking: the average patent in the area of Computer & Communications receives up to 12 citations, while in Drugs & Medical the average number of citations received is 10 at its peak; in contrast, patents in the traditional areas of Mechanical, Chemical and Others never receive more than 6 citations.
Accordingly, knowledge indicators based on patent and citation counts are meaningful only when used comparatively, and to the degree that appropriate comparisons are made. As we have seen, the number of patents granted yearly has substantially increased over the 25 years described by the NBER data. As patents measure knowledge output, this growth may be indicative of an increase in the production of technological inventions. However, it may also reflect changes occurred in the patent-to-invention ratio.
Nowadays patent and citation data have become widely established indicators of knowledge output, knowledge hybridization, and knowledge domains. In order to instantiate the network model of knowledge growth I presented in Chapter 1, I employ patent data as indicators of all three concepts. A number of issues pertaining to the instantiation of the model must still be discussed with regard to the specific patent dataset analyzed. In the following chapter, I provide a statistical description of the data used throughout this thesis.