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Research on the impact of global innovation network on 3D printing industry performance

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Abstract

In this study, we attempted to fill a gap that literature has yet to investigate: the impact of global innovation network on industry performance. Based on 3D printing patent data, this paper builds a cooperative innovation network of 34 economies for six years. It represents the network characteristics of each economy through 204 network attribute indicators. The panel data model is used to study the relationship between global innovation network characteristics and the R&D efficiency and the income of the main business of the 3D printing industry. The input and output data for the R&D efficiency of the 3D printing industry is derived from the Wohlers Report. R&D efficiency indicator values are measured by the Malmquist Productivity Index model based on DEA. The research results show that the global innovation network centrality indicators, structural hole indicators and clustering coefficient indicators have significant correlation with industrial performance. The research conclusions will provide theoretical support for various economies to formulate global innovation strategies and policies of 3D printing industry.

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Authors and Affiliations

  1. Tsinghua University, Beijing, 100081, China

    Xu Bai & Jinxi Wu

  2. University of Chinese Academy of Sciences, Beijing, China

    Yun Liu

  3. Beijing Institute of Technology, Beijing, China

    Yihan Xu

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  1. Xu Bai
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  2. Jinxi Wu
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  3. Yun Liu
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Correspondence to Xu Bai.

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Bai, X., Wu, J., Liu, Y. et al. Research on the impact of global innovation network on 3D printing industry performance. Scientometrics 124, 1015–1051 (2020). https://doi.org/10.1007/s11192-020-03534-1

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