Abstract
This paper exploits recent contributions to the notions of modularity and autocatalytic sets to identify the functional and structural units that define the strongest systematic and self-sustaining channels of knowledge transfer and accumulation within the network of knowledge flows between technology fields. Our analysis reconstructs the architecture of the empirical knowledge pattern based on the United States Patent and Trademark Office (USPTO) patent citation data at the level of resolution of three-digit technology classes, for the period 1975–99.
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