Technological novelty profile and invention's future impact
Daniel Kim, Daniel Burkhardt Cerigo, Hawoong Jeong, Hyejin Youn

TL;DR
This paper develops a method to quantify the novelty of technological combinations in patents, revealing that more unconventional patents tend to have higher future impact.
Contribution
It introduces a novel statistical approach to measure the degree of novelty in patent combinations and analyzes its evolution and impact.
Findings
Patents with higher novelty receive more citations.
Patent activities are becoming more conventional over time.
Unconventional combinations are linked to higher future impact.
Abstract
We consider inventions as novel combinations of existing technological capabilities. Patent data allow us to explicitly identify such combinatorial processes in invention activities. 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…
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