A study on the correlation mechanism between knowledge convergence characteristics and short- and long-term patent impact
DOI:
https://doi.org/10.47989/ir31iConf64126Keywords:
Knowledge convergence, Patent impact, Patent citationAbstract
Introduction. This study aims to reveal the underlying mechanisms linking knowledge convergence characteristics in different technological domains with the short- and long-term impact of patents.
Method. Using a negative binomial regression model, it systematically examines the differentiated effects of scientific knowledge breadth, scientific knowledge depth, technological knowledge breadth, and technological knowledge depth on the short- and long-term impact of patents.
Analysis. This framework enables precise characterization of structural features in knowledge absorption and recombination and provides the basis for quantifying heterogeneous effects of knowledge convergence.
Results. The breadth of knowledge generally enhances patent influence and exhibits an inverted U-shaped relationship, suggesting that moderate diversity and integration increase patent value. In contrast, the effect of knowledge depth varies across fields and time scales: scientific depth in computer technology shows a long-term U-shaped pattern, depth in semiconductors has a positive long-term effect, while technological depth in biotechnology is largely negative.
Conclusion(s). The innovation cycles and knowledge application mechanisms in different fields determine the configuration patterns of knowledge breadth and depth: fast-iteration fields rely more on short-term diffusion driven by breadth, while long-cycle fields emphasize the long-term value of deep accumulation.
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