Recent literature on the diffusion of robots mostly ignores the regional dimension. The contribution of this paper at the debate on Industry 4.0 is twofold. First, IFR (2017) data on acquisitions of industrial robots in the five largest European economies are rescaled at regional levels to draw a first picture of winners and losers in the European race for advanced manufacturing. Second, using an unsupervised machine learning approach to classify regions based on their composition of industries. The paper provides novel evidence of the relationship between industry mix and the regional capability of adopting robots in the industrial processes.

Industrial Pattern and Robot Adoption in European Regions

Aldo Geuna
2020

Abstract

Recent literature on the diffusion of robots mostly ignores the regional dimension. The contribution of this paper at the debate on Industry 4.0 is twofold. First, IFR (2017) data on acquisitions of industrial robots in the five largest European economies are rescaled at regional levels to draw a first picture of winners and losers in the European race for advanced manufacturing. Second, using an unsupervised machine learning approach to classify regions based on their composition of industries. The paper provides novel evidence of the relationship between industry mix and the regional capability of adopting robots in the industrial processes.
Department of Management, Università Ca' Foscari Venezia Working Paper
2/2020
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3655140
Robots, Industry 4.0, Innovation, Industry Mix, Self-Organizing Maps
Massimiliano Nuccio, Marco Guerzoni, Riccardo Cappelli; Aldo Geuna
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1797816
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