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An Empirical Study on the Impact of Collaborative R&D Networks on Enterprise Innovation Performance Based on the Mediating Effect of Technology Standard Setting

Author

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  • Hong Jiang

    (School of Management, Jilin University, Changchun 130022, China)

  • Sipeng Gao

    (School of Management, Jilin University, Changchun 130022, China)

  • Yang Song

    (School of Management, Jilin University, Changchun 130022, China)

  • Kuang Sheng

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310063, China)

  • Gehan A. J. Amaratunga

    (Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK)

Abstract

Against the background of economic globalization, high-technology enterprises need to focus on the characteristics of corporate collaboration R&D networks and Standard-Setting. In this paper, theoretical research on corporate collaboration R&D network characteristics, technology standard-setting capability, and technology innovation performance is carried out, and a theoretical model and hypotheses are constructed. We apply Structural Equation Modeling (SEM) to conduct an empirical analysis based on national data surveys of 12 industries. The conclusions are as follows: (1) Corporate collaboration R&D networks and technology standard-setting capability have a positive and significant impact on technology innovation performance; (2) Technology’s standard-setting capability has been identified to play a full intermediary role in the relationship between the breadth of connections and innovation efficiency. This paper provides a practical reference for enterprises to assess the value of collaborative R&D networks and improve their technology standard-setting capability for enhanced economic efficiency.

Suggested Citation

  • Hong Jiang & Sipeng Gao & Yang Song & Kuang Sheng & Gehan A. J. Amaratunga, 2019. "An Empirical Study on the Impact of Collaborative R&D Networks on Enterprise Innovation Performance Based on the Mediating Effect of Technology Standard Setting," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7249-:d:298944
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    2. Hung-Wen Lin & Kun-Ben Lin & Jing-Bo Huang & Shu-Heng Chen, 2021. "Timely Loss Recognition Helps Nothing," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    3. Sung Hyo Hong, 2021. "Determinants of Selection of R&D Cooperation Partners: Insights from Korea," Sustainability, MDPI, vol. 13(17), pages 1-11, August.
    4. Eun Sun Kim & Kuk Jin Bae & Jeongeun Byun, 2020. "The History and Evolution: A Big Data Analysis of the National Innovation Systems in South Korea," Sustainability, MDPI, vol. 12(3), pages 1-20, February.

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