IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v603y2022ics0378437122004502.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122004502
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.127672?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Damioli, G. & Van Roy, V. & Vertesy, D. & Vivarelli, M., 2021. "May AI revolution be labour-friendly? Some micro evidence from the supply side," GLO Discussion Paper Series 823, Global Labor Organization (GLO).
    2. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2021. "Detecting the labour-friendly nature of AI product innovation," DISCE - Working Papers del Dipartimento di Politica Economica dipe0017, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy, 2021. "The impact of artificial intelligence on labor productivity," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 1-25, March.
    4. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2021. "Will the AI revolution be labour-friendly? Some micro evidence from the supply side," MERIT Working Papers 2021-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    6. Curci, Ylenia & Mongeau Ospina, Christian A., 2016. "Investigating biofuels through network analysis," Energy Policy, Elsevier, vol. 97(C), pages 60-72.
    7. Alex Bell & Raj Chetty & Xavier Jaravel & Neviana Petkova & John Van Reenen, 2019. "Who Becomes an Inventor in America? The Importance of Exposure to Innovation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(2), pages 647-713.
    8. Norbäck, Pehr-Johan & Persson, Lars & Svensson, Roger, 2017. "Verifying High Quality: Entry for Sale," Working Paper Series 1186, Research Institute of Industrial Economics.
    9. Pierpaolo Parrotta & Dario Pozzoli & Mariola Pytlikova, 2014. "The nexus between labor diversity and firm’s innovation," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(2), pages 303-364, April.
    10. Danilo Cascaldi-Garcia & Marija Vukotic, 2022. "Patent-Based News Shocks," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 51-66, March.
    11. Emanuele Bacchiocchi & Fabio Montobbio, 2010. "International Knowledge Diffusion and Home‐bias Effect: Do USPTO and EPO Patent Citations Tell the Same Story?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(3), pages 441-470, September.
    12. Yi Deng, 2003. "A Dynamic Stochastic Analysis of International Patent Application and Renewal Processes," Computing in Economics and Finance 2003 189, Society for Computational Economics.
    13. Tom Broekel & Lars Mewes, 2017. "Analyzing the impact of R&D policy on regional diversification," Papers in Evolutionary Economic Geography (PEEG) 1726, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2017.
    14. Viral V. Acharya & Krishnamurthy V. Subramanian, 2009. "Bankruptcy Codes and Innovation," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 4949-4988, December.
    15. Bryan Kelly & Dimitris Papanikolaou & Amit Seru & Matt Taddy, 2021. "Measuring Technological Innovation over the Long Run," American Economic Review: Insights, American Economic Association, vol. 3(3), pages 303-320, September.
    16. Dirk Czarnitzki & Cindy Lopes-Bento, 2014. "Innovation Subsidies: Does the Funding Source Matter for Innovation Intensity and Performance? Empirical Evidence from Germany," Industry and Innovation, Taylor & Francis Journals, vol. 21(5), pages 380-409, July.
    17. Sharon Belenzon & Tomer Berkovitz, 2010. "Innovation in Business Groups," Management Science, INFORMS, vol. 56(3), pages 519-535, March.
    18. Qiao Liu & Kit Pong Wong, 2011. "Intellectual Capital and Financing Decisions: Evidence from the U.S. Patent Data," Management Science, INFORMS, vol. 57(10), pages 1861-1878, October.
    19. David Autor & Anna Salomons, 2018. "Is Automation Labor Share–Displacing? Productivity Growth, Employment, and the Labor Share," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 49(1 (Spring), pages 1-87.
    20. Altuntas, Serkan & Dereli, Turkay & Kusiak, Andrew, 2015. "Analysis of patent documents with weighted association rules," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 249-262.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122004502. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.