Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/213832
Authors: 
Montobbio, Fabio
Staccioli, Jacopo
Virgillito, Maria Enrica
Vivarelli, Marco
Year of Publication: 
2020
Series/Report no.: 
GLO Discussion Paper 471
Abstract: 
This paper investigates the presence of explicit labour-saving heuristics within robotic patents. It analyses innovative actors engaged in robotic technology and their economic environment (identity, location, industry), and identifies the technological fields particularly exposed to labour-saving innovations. It exploits advanced natural language processing and probabilistic topic modelling techniques on the universe of patent applications at the USPTO between 2009 and 2018, matched with ORBIS (Bureau van Dijk) firm-level dataset. The results show that labour-saving patent holders comprise not only robots producers, but also adopters. Consequently, labour-saving robotic patents appear along the entire supply chain. The paper shows that labour-saving innovations challenge manual activities (e.g. in the logistics sector), activities entailing social intelligence (e.g. in the healthcare sector) and cognitive skills (e.g. learning and predicting).
Subjects: 
Robotic Patents
Labour-Saving Technology
Search Heuristics
Probabilistic Topic Models
JEL: 
O33
J24
C38
Document Type: 
Working Paper

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