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Global competitiveness analysis of industrial robot technology innovations market layout using visibility graph

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  • Wu, Xuehui
  • Wu, Zhong
  • Hu, Jun

Abstract

The competition degree and characteristics of the target markets based on a global vision provide references for market entrants and policymakers. This study describes a method for identifying the global technology innovations market layout competitiveness based on time series data analysis. We map the time series data from 30 countries or areas of the global industrial robot technology innovations market through retrieval strategy and data mining onto complex networks by visibility graph algorithm. We analyze the dynamic characteristics by the VGNs’ topological measures after the development trend overview and stage division analyses. We use cosine similarity to evaluate the differences and similarities between countries or areas. To further uncover the relationships among them, a similarity complex network is constructed by setting a link threshold. Seven community categories as sub-markets are found through community division. CN and US rank as the top two largest industrial robot innovation markets. Most European countries share the same community because of their similarity of economic development brought by geographical proximity except for several earlier developed economies such as DE, GB, FR, and IT. Some catching-up countries, for example, IN and PH, show potential similar dynamic trends respectively in their group for the sharing characteristics probably with the similar economic development type as the reason behind, whereas RU is distinct for its unique economy type.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122004502
    DOI: 10.1016/j.physa.2022.127672
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    References listed on IDEAS

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    1. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, vol. 36(1), pages 16-38, Spring.
    2. repec:fth:harver:1473 is not listed on IDEAS
    3. Telesca, Luciano & Lovallo, Michele & Ramirez-Rojas, Alejandro & Flores-Marquez, Leticia, 2013. "Investigating the time dynamics of seismicity by using the visibility graph approach: Application to seismicity of Mexican subduction zone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6571-6577.
    4. Georg Graetz & Guy Michaels, 2017. "Is Modern Technology Responsible for Jobless Recoveries?," American Economic Review, American Economic Association, vol. 107(5), pages 168-173, May.
    5. Michelle Alexopoulos & Jon Cohen, 2016. "The Medium Is the Measure: Technical Change and Employment, 1909—1949," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 792-810, October.
    6. Wang, Wenya & Li, Zhenfu & Cheng, Xin, 2019. "Evolution of the global coal trade network: A complex network analysis," Resources Policy, Elsevier, vol. 62(C), pages 496-506.
    7. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    8. Pierini, Jorge O. & Lovallo, Michele & Telesca, Luciano, 2012. "Visibility graph analysis of wind speed records measured in central Argentina," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5041-5048.
    9. Herman Emilia, 2018. "Innovation and entrepreneurship for competitiveness in the EU: an empirical analysis," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 12(1), pages 425-435, May.
    10. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    11. 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.
    12. 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.
    13. Goeldner, Moritz & Herstatt, Cornelius & Tietze, Frank, 2015. "The emergence of care robotics — A patent and publication analysis," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 115-131.
    14. Ju, Yonghan & Sohn, So Young, 2015. "Patent-based QFD framework development for identification of emerging technologies and related business models: A case of robot technology in Korea," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 44-64.
    15. Hu, Jun & Xia, Chengyi & Li, Huijia & Zhu, Peican & Xiong, Wenjun, 2020. "Properties and structural analyses of USA’s regional electricity market: A visibility graph network approach," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    Full references (including those not matched with items on IDEAS)

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