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Technological novelty profile and invention's future impact, EPJ Data Science

Abstract

We consider inventions as novel combinations of existing technological capabilities. Patent data allow us to explicitly identify such combinatorial processes in invention activities (Youn et al. in J R Soc Interface 12:20150272, 2015). Unconsidered in the previous research, not every new combination is novel to the same extent. Some combinations are naturally anticipated based on patent activities in the past or mere random choices, and some appear to deviate exceptionally from existing invention pathways. We calculate a relative likelihood that each pair of classification codes is put together at random, and a deviation from the empirical observation so as to assess the overall novelty (or conventionality) that the patent brings forth at each year. An invention is considered as unconventional if a pair of codes therein is unlikely to be used together given the statistics in the past. Temporal evolution of the distribution indicates that the patenting activities become more conventional with occasional cross-over combinations. Our analyses show that patents introducing novelty on top of the conventional units would receive higher citations, and hence have higher impact.

Type

Article

Author(s)

Daniel Kim, Daniel Burkhardt Cerigo, Hyejin Youn

Date Published

2016

Citations

Kim, Daniel, Daniel Burkhardt Cerigo, and Hyejin Youn. 2016. Technological novelty profile and invention's future impact. EPJ Data Science. 5(8)

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