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Big Data Analytics for Venture Capital Application：Towards Innovation Performance Improvement

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  • Sun, Wenqi
  • Zhao, Yuanjun
  • Sun, Lu

Abstract

By using the panel date of Chinese enterprises, this paper analyzes the influence of venture capital on innovation performance. In this paper, the number of patent application and the patent quality(invention patent applications, number of effective patents, IPC number of international patent classification, and patent claims) are used to measure the innovation performance of enterprises, and the regression results show that the innovation performance is significantly promoted by the venture capital; for industries with higher dependence on external financing and high technology intensity and areas with better protection of property rights, venture capital promotes innovation performance more significantly. In this paper, it further distinguishes the characteristics of venture capital institutions, and finds that the promotion effect of non-state-owned venture capital on innovation performance is significantly greater than that of state-owned venture capital; the venture capital institutions with high reputation and high network capital play a more significant role in promoting innovation performance.

Suggested Citation

  • Sun, Wenqi & Zhao, Yuanjun & Sun, Lu, 2020. "Big Data Analytics for Venture Capital Application：Towards Innovation Performance Improvement," International Journal of Information Management, Elsevier, vol. 50(C), pages 557-565.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:557-565
    DOI: 10.1016/j.ijinfomgt.2018.11.017
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    Citations

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    Cited by:

    1. Wang, Xue & Fan, Li-Wei & Zhang, Hongyan, 2023. "Policies for enhancing patent quality: Evidence from renewable energy technology in China," Energy Policy, Elsevier, vol. 180(C).
    2. Bing Feng & Kaiyang Sun & Ziqi Zhong & Min Chen, 2021. "The Internal Connection Analysis of Information Sharing and Investment Performance in the Venture Capital Network Community," IJERPH, MDPI, vol. 18(22), pages 1-16, November.
    3. Gu, Jing & Zhang, Fujuan & Xu, Xun & Xue, Chaokai, 2023. "Stay or switch? The impact of venture capitalists' movement across network communities on enterprises’ innovation performance," Technovation, Elsevier, vol. 125(C).
    4. Fu, Shaoyan & Liu, Dehai & Huang, Fuqiang, 2024. "Synergistic effect of government policy and market mechanism on the innovation of new energy vehicle enterprises," Energy, Elsevier, vol. 295(C).
    5. Pu, Xiaohong & Zeng, Ming & Zhang, Weike, 2023. "Corporate sustainable development driven by high-quality innovation: Does fiscal decentralization really matter?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 273-289.
    6. Hötte, Kerstin & Jee, Su Jung, 2022. "Knowledge for a warmer world: A patent analysis of climate change adaptation technologies," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    7. Lyu, Chaofeng & Xie, Zhe & Li, Zhi, 2022. "Market supervision, innovation offsets and energy efficiency: Evidence from environmental pollution liability insurance in China," Energy Policy, Elsevier, vol. 171(C).
    8. Lin, Boqiang & Xie, Yongjing, 2024. "The role of venture capital in determining the total factor productivity of renewable energy enterprises: In the context of government subsidy reduction," Energy Economics, Elsevier, vol. 132(C).

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