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HOW INDUSTRY 4.0 RESHAPES THE WORLD: RECOMMENDATIONS BASED ON COMPLEX GRAPH NETWORK ANALYSIS

Published online by Cambridge University Press:  27 July 2021

Rongyan Zhou  and
Julie Stal-Le Cardinal
Rongyan Zhou*
Affiliation:
Université Paris-Saclay, CentraleSupélec
Julie Stal-Le Cardinal
Affiliation:
Université Paris-Saclay, CentraleSupélec
*
Zhou, Rongyan, Université Paris-Saclay, CentraleSupélec, Industrial Engineering Research Department(LGI), France, [email protected]

Abstract

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Industry 4.0 is a great opportunity and a tremendous challenge for every role of society. Our study combines complex network and qualitative methods to analyze the Industry 4.0 macroeconomic issues and global supply chain, which enriches the qualitative analysis and machine learning in macroscopic and strategic research. Unsupervised complex graph network models are used to explore how industry 4.0 reshapes the world. Based on the in-degree and out-degree of the weighted and unweighted edges of each node, combined with the grouping results based on unsupervised learning, our study shows that the cooperation groups of Industry 4.0 are different from the previous traditional alliances. Macroeconomics issues also are studied. Finally, strong cohesive groups and recommendations for businessmen and policymakers are proposed.

Keywords

Industry 4.0Machine learningBusiness models and considerationsDecision makingBig data
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 1755 - 1764
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

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