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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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    1. Fagiolo, Giorgio & Reyes, Javier & Schiavo, Stefano, 2008. "On the topological properties of the world trade web: A weighted network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3868-3873.
    2. Francesco Chiacchio & Georgios Petropoulos & David Pichler, 2018. "The impact of industrial robots on EU employment and wages- A local labour market approach," Working Papers 25186, Bruegel.
    3. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    4. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2014. "A dynamic analysis on global natural gas trade network," Applied Energy, Elsevier, vol. 132(C), pages 23-33.
    5. Koffi Dumor & Li Yao, 2019. "Estimating China’s Trade with Its Partner Countries within the Belt and Road Initiative Using Neural Network Analysis," Sustainability, MDPI, vol. 11(5), pages 1-22, March.
    6. Yun, JinHyo Joseph & Won, DongKyu & Jeong, EuiSeob & Park, KyungBae & Yang, JeongHo & Park, JiYoung, 2016. "The relationship between technology, business model, and market in autonomous car and intelligent robot industries," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 142-155.
    7. Yongli Li & Guanghe Liu & Paolo Pin, 2018. "Network-based risk measurements for interbank systems," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    8. Isabella Cingolani & Lelio Iapadre & Lucia Tajoli, 2018. "International production networks and the world trade structure," International Economics, CEPII research center, issue 153, pages 11-33.
    9. Lechevalier, Sébastien & Nishimura, Junichi & Storz, Cornelia, 2014. "Diversity in patterns of industry evolution: How an intrapreneurial regime contributed to the emergence of the service robot industry," Research Policy, Elsevier, vol. 43(10), pages 1716-1729.
    10. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    11. Xibo Wang & Jianping Ge & Wendong Wei & Hanshi Li & Chen Wu & Ge Zhu, 2016. "Spatial Dynamics of the Communities and the Role of Major Countries in the International Rare Earths Trade: A Complex Network Analysis," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-22, May.
    12. Li, Yongli & Luo, Peng & Fan, Zhi-ping & Chen, Kun & Liu, Jiaguo, 2017. "A utility-based link prediction method in social networks," European Journal of Operational Research, Elsevier, vol. 260(2), pages 693-705.
    13. Woo Jin Lee & Won Kyung Lee & So Young Sohn, 2016. "Patent Network Analysis and Quadratic Assignment Procedures to Identify the Convergence of Robot Technologies," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-16, October.
    14. Artuc,Erhan & Bastos,Paulo S. R. & Rijkers,Bob, 2018. "Robots, Tasks and Trade," Policy Research Working Paper Series 8674, The World Bank.
    15. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    16. Timothy Sturgeon & Johannes Van Biesebroeck & Gary Gereffi, 2008. "Value chains, networks and clusters: reframing the global automotive industry," Journal of Economic Geography, Oxford University Press, vol. 8(3), pages 297-321, May.
    17. Zhong, Weiqiong & An, Haizhong & Fang, Wei & Gao, Xiangyun & Dong, Di, 2016. "Features and evolution of international fossil fuel trade network based on value of emergy," Applied Energy, Elsevier, vol. 165(C), pages 868-877.
    18. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    19. Garlaschelli, Diego & Loffredo, Maria I., 2005. "Structure and evolution of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 138-144.
    20. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
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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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