IDEAS home Printed from https://ideas.repec.org/a/mes/emfitr/v60y2024i8p1691-1715.html
   My bibliography  Save this article

Do Industrial Robots Improve Export Product Quality of Multi-Product Enterprises? Evidence in China

Author

Listed:
  • Jing Lu
  • Taoxuan Wang
  • Yiming Yuan
  • Hangyu Chen

Abstract

Based on an endogenous quality selection model, we investigate the effect of industrial robots on the export product quality of China’s multi-product enterprises. The main finding is that there is a nonlinear “inverted U-shaped” relationship between industrial robot applications and export quality. Industrial robots mainly affect export quality through the “productivity improvement effect” and “innovation inhibition effect.” The influence channels exhibit heterogeneity, contingent on industries, growth stages, and import orders. We further find that the entry of new products, improvement in the quality of existing products, and reallocation of internal resources within the enterprise account for product quality change in general.

Suggested Citation

  • Jing Lu & Taoxuan Wang & Yiming Yuan & Hangyu Chen, 2024. "Do Industrial Robots Improve Export Product Quality of Multi-Product Enterprises? Evidence in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 60(8), pages 1691-1715, June.
  • Handle: RePEc:mes:emfitr:v:60:y:2024:i:8:p:1691-1715
    DOI: 10.1080/1540496X.2023.2278652
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1540496X.2023.2278652
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1540496X.2023.2278652?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. Jiayu Ou & Zhiqiang Zheng & Xiaojing Ou & Naili Zhang, 2024. "Smart City Construction, Artificial Intelligence Development, and the Quality of Export Products: A Study Based on Micro-Level Data of Chinese Enterprises," Sustainability, MDPI, vol. 16(19), pages 1-25, October.
    2. Renhao Chen & Helian Xu, 2024. "Supply Chain Relationships, Resilience, and Export Product Quality: Analysis Based on Supply Chain Concentration," Sustainability, MDPI, vol. 16(20), pages 1-22, October.

    More about this item

    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:mes:emfitr:v:60:y:2024:i:8:p:1691-1715. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/MREE20 .

    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.