IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-052-7_35.html

Research on the Impact of Digital Economy on the Upgrading of Industrial Structure

In: Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022)

Author

Listed:
  • TuoChen Li

    (Harbin Engineering University, School of Economics and Management)

  • Yue Yu

    (Harbin Engineering University, School of Economics and Management)

Abstract

Based on panel data of three major Urban agglomerations in China from 2011 to 2019, this paper adopts the entropy weight method to measure the comprehensive level of digital economy. On this basis, this paper establishes the econometric model to conduct empirical research on the direct impact, transmission mechanism of digital economy on urban industrial structure. The results show that the development of digital economy can promote the upgrading of industrial structure, among which technological innovation plays a positive mediating role.

Suggested Citation

  • TuoChen Li & Yue Yu, 2022. "Research on the Impact of Digital Economy on the Upgrading of Industrial Structure," Advances in Economics, Business and Management Research, in: Faruk Balli & Au Yong Hui Nee & Sikandar Ali Qalati (ed.), Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022), pages 305-311, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-052-7_35
    DOI: 10.2991/978-94-6463-052-7_35
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Yanyan Li & Ziyue Zhu & Shanxing Gao, 2025. "Research on the Impact of Regional Digitalization on Innovation Performance and Its Boundary Conditions: An Empirical Study Based on Chinese Provincial Panel Data," SAGE Open, , vol. 15(2), pages 21582440241, April.
    2. Fang Liu & Chen Liang, 2026. "Exploring the Potential of Digitization in Disrupting Class Stratification," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 17(2), pages 4743-4773, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:advbcp:978-94-6463-052-7_35. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.