Automation and related technologies: a mapping of the new knowledge base

Enrico Santarelli, Jacopo Staccioli and Marco Vivarelli ()

The Journal of Technology Transfer, 2023, vol. 48, issue 2, No 12, 779-813

Abstract: Abstract Using the entire population of USPTO patent applications published between 2002 and 2019, and leveraging on both patent classification and semantic analysis, this paper aims to map the current knowledge base centred on robotics and AI technologies. These technologies are investigated both as a whole and distinguishing core and related innovations, along a 4-level core-periphery architecture. Merging patent applications with the Orbis IP firm-level database allows us to put forward a twofold analysis based on industry of activity and geographic location. In a nutshell, results show that: (i) rather than representing a technological revolution, the new knowledge base is strictly linked to the previous technological paradigm; (ii) the new knowledge base is characterised by a considerable—but not impressively widespread—degree of pervasiveness; (iii) robotics and AI are strictly related, converging (particularly among the related technologies and in more recent times) and jointly shaping a new knowledge base that should be considered as a whole, rather than consisting of two separate GPTs; (iv) the US technological leadership turns out to be confirmed (although declining in relative terms in favour of Asian countries such as South Korea, China and, more recently, India).

Keywords: Robotics; Artificial intelligence; General purpose technology; Technological paradigm; Industry 4.0; Patents full-text (search for similar items in EconPapers)
JEL-codes: O33 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (7)

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Working Paper: Automation and Related Technologies: A Mapping of the New Knowledge Base (2022)
Working Paper: Automation and related technologies: A mapping of the new knowledge base (2022)
Working Paper: Automation and Related Technologies: A Mapping of the New Knowledge Base (2022)
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DOI: 10.1007/s10961-021-09914-w

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