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

Xuehui Wu, Zhong Wu and Jun Hu

Physica A: Statistical Mechanics and its Applications, 2022, vol. 603, issue C

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.

Keywords: Technology innovation; Visibility graph; Complex network; Cosine similarity; Community structure; Clustering (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122004502

DOI: 10.1016/j.physa.2022.127672

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