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 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.
Highlights
A new idea that advances science and technology is commonly recognised as an important source of wealth creation, economic growth, and societal change [, ]
In the case of inventive activities, Youn and co-workers availed themselves of technology codes, classified by United States Patent and Trademark Office (USPTO), as countable units to identify the underlying dynamics of inventions as combinatorial processes in a
We show inventions assemble technological units in a way to reinforce the already conventional pairs, thereby some components become increasingly entrenched within the inventive repertoire with increasing z-scores, such that they become a further building block for future combinations
Summary
A new idea that advances science and technology is commonly recognised as an important source of wealth creation, economic growth, and societal change [ , ]. It is of no surprise that understanding the dynamics of generation of new ideas sits at the centre of many disciplines [ – ]. The growing empirical literature in this respect is to identify the process of publication [ ], to utilise Google n-gram to characterise scientific evolution [ ], to delineate the boundary of science [ , ], and to predict the future impact of scientific papers [ , ] and authors [ , ]. In the case of inventive activities, Youn and co-workers availed themselves of technology codes, classified by United States Patent and Trademark Office (USPTO), as countable units to identify the underlying dynamics of inventions as combinatorial processes in a
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