IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v192y2023ics0040162523002524.html
   My bibliography  Save this article

Big data application, factor allocation, and green innovation in Chinese manufacturing enterprises

Author

Listed:
  • Gao, Qiang
  • Cheng, Changming
  • Sun, Guanglin

Abstract

Green innovation is key to promoting the manufacturing industry's green development and transformation. One way to promote green innovation in manufacturing enterprises can be the deep integration of big data. Using data on listed Chinese manufacturing enterprises from 2014 to 2019, we examine the impacts of big data on green innovation and the mechanisms underlying this relationship. Using a panel fixed effects regression model, we find that big data significantly and positively affects green innovation. Internal mechanism analyses reveal that big data improves the manufacturing industry's green innovation by improving the factor allocation efficiency for both labor and capital. The heterogeneity analysis indicates that the promotional effect of big data on green innovation is more prominent in private enterprises than in state-owned enterprises. The government should formulate big data application policies, and provide incentives for the deep integration of big data in manufacturing enterprises to accelerate green innovation.

Suggested Citation

  • Gao, Qiang & Cheng, Changming & Sun, Guanglin, 2023. "Big data application, factor allocation, and green innovation in Chinese manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:tefoso:v:192:y:2023:i:c:s0040162523002524
    DOI: 10.1016/j.techfore.2023.122567
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523002524
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122567?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Hongda & Zhao, Haifeng & Li, Shiyuan, 2023. "Future social change of manufacturing and service industries: Service-oriented manufacturing under the integration of innovation-flows drive," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Li, Jinning & Kong, Tao & Gu, Liangliang, 2024. "The impact of climate policy uncertainty on green innovation in Chinese agricultural enterprises," Finance Research Letters, Elsevier, vol. 62(PA).
    3. Sun, Guanglin & Fang, Jiming & Li, Ting & Ai, Yongfang, 2024. "Effects of climate policy uncertainty on green innovation in Chinese enterprises," International Review of Financial Analysis, Elsevier, vol. 91(C).
    4. Xu, Chao & Sun, Guanglin & Kong, Tao, 2024. "The impact of digital transformation on enterprise green innovation," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 1-12.
    5. Panpan Liu & Guanghui Han & Haichao Yang & Xiaobo Li, 2024. "A Sustainable Development Study on Innovation Factor Allocation Efficiency and Spatial Correlation Based on Regions along the Belt and Road in China," Sustainability, MDPI, vol. 16(7), pages 1-22, April.
    6. Sun, Guanglin & Fang, Jiming & Li, Jinning & Wang, Xiaolin, 2024. "Research on the impact of the integration of digital economy and real economy on enterprise green innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    7. Zhiqiang Liu & Yaping Zhao & Caiyun Guo & Ziwei Xin, 2024. "Research on the Impact of Digital-Real Integration on Logistics Industrial Transformation and Upgrading under Green Economy," Sustainability, MDPI, vol. 16(14), pages 1-26, July.
    8. Li, Yiping & Zheng, Lanxing & Xie, Chang & Fang, Jiming, 2024. "Big data development and enterprise ESG performance: Empirical evidence from China," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 742-755.
    9. Sun, Jianhua & Hou, Shaobo & Deng, Yuxia & Li, Huaicheng, 2024. "New media environment, green technological innovation and corporate productivity: Evidence from listed companies in China," Energy Economics, Elsevier, vol. 131(C).
    10. Wang, Bo & Gong, Siyu & Yang, Yang, 2024. "Unveiling the relation between digital technology and low-carbon innovation: Carbon emission trading policy as an antecedent," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    11. Zhao, Guoqing & Xie, Xiaotian & Wang, Yi & Liu, Shaofeng & Jones, Paul & Lopez, Carmen, 2024. "Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    12. Di Luan & Hongjun Cao & Tongkun Qu, 2023. "How Does Corporate Green Innovation Strategy Translate into Green Innovation Performance Based on Chain Mediation?," Sustainability, MDPI, vol. 15(16), pages 1-20, August.
    13. Hongyi Mao & Jiang Lu, 2023. "Big Data Management Capabilities and Green Innovation: A Dynamic Capabilities View," Sustainability, MDPI, vol. 15(19), pages 1-27, October.
    14. Wanying Rao & Pingfeng Liu, 2024. "Can Digital Innovation Improve Green Total Factor Productivity: Evidence from Digital Patents of China," Sustainability, MDPI, vol. 16(10), pages 1-21, May.
    15. Liu, Feng & Wang, Rongping & Fang, Mingjie, 2024. "Mapping green innovation with machine learning: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Honghe Li & Xiaotian Du & Xiang-Wu Yan & Ning Xu, 2024. "Digital Transformation and Urban Green Development: Evidence from China’s Data Factor Marketization," Sustainability, MDPI, vol. 16(11), pages 1-21, May.
    17. Guangya Zhou & Helian Xu & Chuanzeng Jiang & Shiqi Deng & Liming Chen & Zhi Zhang, 2024. "Has the Digital Economy Improved the Urban Land Green Use Efficiency? Evidence from the National Big Data Comprehensive Pilot Zone Policy," Land, MDPI, vol. 13(7), pages 1-25, June.

    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:tefoso:v:192:y:2023:i:c:s0040162523002524. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.sciencedirect.com/science/journal/00401625 .

    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.