Determinants of AI-Related Patent Quality: Multidimensional Collaboration Structures and the Role of Scale Effects

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Key Points

To empirically analyze how the multidimensional characteristics of collaboration structures affect the patent quality index (PQI) of AI patents.
Analyzed 114,319 AI patent applications from KIPO between 2013-2023.
PQI was constructed from front citations, number of claims, and patent family size.
Excluded direct effects of collaboration institution types from statistical significance.
Collaborative patents had higher average quality than solo patents, but the effect was limited.
Collaboration scale consistently showed a positive effect on patent quality.
Structural diversity improved quality to a point, showing an inverted U-shaped relationship when excessive.

Analyzes the impact of collaboration structures on patent quality in AI, suggesting scale effects matter more than type.

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Choi et al. (2026) studied this question.

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