Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis

Yaya Li, Yongtao Peng, Jianqiang Luo, Yihan Cheng and Eleonora Veglianti

PLOS ONE, 2019, vol. 14, issue 9, 1-14

Abstract: Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by ‘diversification’. The number of major industrial robot exporters in the world is increasing, and the import market is increasingly diversified. The export market structure is relatively tight, the centrality of the global industrial robot trade network shows a downward trend, and the dissimilarity of the ‘core-edge’ clusters decreases year by year. The trade status of ‘catch-up’ countries represented by China has rapidly increased. However, Japan, Germany, and Italy are still in the central position of the industrial robot trade. Moreover, trade of the ‘catch-up’ countries’ is dominated by imports, and exports of industrial robot products are insufficient. Finally, policy suggestions are provided according to the results.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0222785

DOI: 10.1371/journal.pone.0222785

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