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

Author

Listed:
  • Yaya Li
  • Yongtao Peng
  • Jianqiang Luo
  • Yihan Cheng
  • Eleonora Veglianti

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.

Suggested Citation

  • Yaya Li & Yongtao Peng & Jianqiang Luo & Yihan Cheng & Eleonora Veglianti, 2019. "Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-14, September.
    • Handle: RePEc:plo:pone00:0222785
    DOI: 10.1371/journal.pone.0222785
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    Cited by:

    1. Wu, Xuehui & Wu, Zhong & Hu, Jun, 2022. "Global competitiveness analysis of industrial robot technology innovations market layout using visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    2. Shu-Hao Chang, 2022. "Examining Key Technologies Among Academic Patents Through an Analysis of Standard-Essential Patents," SAGE Open, , vol. 12(3), pages 21582440221, July.

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