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The determinants of AI innovation across European firms

Igna, Ioana LU and Venturini, Francesco LU (2023) In Research Policy 52(2). p.1-15
Abstract
Using patent data for a panel sample of European companies between 1995 and 2016 we explore whether the inventive success in Artificial Intelligence (AI) is related to earlier firms’ innovation in the area of Information and Communication Technology (ICT), and identify which company characteristics and external factors shape this performance. We show that AI innovation presents strong dynamic returns (learning effects) and benefits from complementaries with knowledge earlier developed in the area of network and communication technologies, high-speed computing and data analysis, and more recently cognition and imaging. AI patent productivity increases with the scale of firm innovation, and is lower for companies with narrow technological... (More)
Using patent data for a panel sample of European companies between 1995 and 2016 we explore whether the inventive success in Artificial Intelligence (AI) is related to earlier firms’ innovation in the area of Information and Communication Technology (ICT), and identify which company characteristics and external factors shape this performance. We show that AI innovation presents strong dynamic returns (learning effects) and benefits from complementaries with knowledge earlier developed in the area of network and communication technologies, high-speed computing and data analysis, and more recently cognition and imaging. AI patent productivity increases with the scale of firm innovation, and is lower for companies with narrow technological competences. There is evidence of knowledge spillovers from ICT innovators to AI innovators, but this effect is confined to the frontier firms of the new technological field. Our findings suggest that, with the take-off of the new technology, the technological lead of top AI innovators has increased due to the accumulation of internal competences and the expanding knowledge base. These trends help explain the concentration process of the world’s data market. (Less)
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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
AI, ICT, Patenting, European firms, O31, O32, O34
in
Research Policy
volume
52
issue
2
article number
104661
pages
1 - 15
publisher
Elsevier
external identifiers
  • scopus:85142121721
ISSN
0048-7333
DOI
10.1016/j.respol.2022.104661
language
English
LU publication?
yes
id
a05eea9a-a228-4c40-a13f-22368ba3d50a
date added to LUP
2023-01-10 21:20:56
date last changed
2024-01-15 21:40:14
@article{a05eea9a-a228-4c40-a13f-22368ba3d50a,
  abstract     = {{Using patent data for a panel sample of European companies between 1995 and 2016 we explore whether the inventive success in Artificial Intelligence (AI) is related to earlier firms’ innovation in the area of Information and Communication Technology (ICT), and identify which company characteristics and external factors shape this performance. We show that AI innovation presents strong dynamic returns (learning effects) and benefits from complementaries with knowledge earlier developed in the area of network and communication technologies, high-speed computing and data analysis, and more recently cognition and imaging. AI patent productivity increases with the scale of firm innovation, and is lower for companies with narrow technological competences. There is evidence of knowledge spillovers from ICT innovators to AI innovators, but this effect is confined to the frontier firms of the new technological field. Our findings suggest that, with the take-off of the new technology, the technological lead of top AI innovators has increased due to the accumulation of internal competences and the expanding knowledge base. These trends help explain the concentration process of the world’s data market.}},
  author       = {{Igna, Ioana and Venturini, Francesco}},
  issn         = {{0048-7333}},
  keywords     = {{AI; ICT; Patenting; European firms; O31; O32; O34}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{1--15}},
  publisher    = {{Elsevier}},
  series       = {{Research Policy}},
  title        = {{The determinants of AI innovation across European firms}},
  url          = {{http://dx.doi.org/10.1016/j.respol.2022.104661}},
  doi          = {{10.1016/j.respol.2022.104661}},
  volume       = {{52}},
  year         = {{2023}},
}