IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v200y2024ics0040162523008120.html
   My bibliography  Save this article

The innovation model and upgrade path of digitalization driven tourism industry: Longitudinal case study of OCT

Author

Listed:
  • Liu, Qian
  • Gao, Jian
  • Li, Shijie

Abstract

Unlike the progressive growth of developed countries that have transitioned from large-scale tourism to intelligent tourism, China's tourism sector exhibits characteristics of short-term leapfrog strategic change. However, existing research lacks a sufficient theoretical explanation of how China's tourism industry can achieve this leapfrog strategic change. Based on a longitudinal case study, this study finds that digital supplementation and intelligent innovation constitute two key stages in Chinese enterprises' leap-forward strategic change from large-scale park tourism to intelligent tourism from 2012 to 2020. Digitalization is an important path for Chinese enterprises to realize transformation and upgrading, mainly through digital acceleration and reconstruction learning mechanisms, to drive the double leap in strategic change and tourism industry model innovation. In the context of a mismatch between digital technology and managerial skills, this study provides a theoretical model for firms to implement a leap-forward strategic change in intelligent tourism. It not only supports strategic change theory and organizational learning but also provides management illumination for digital rural construction, national tourism intelligence policy development, and enterprise intelligent tourism reform practice.

Suggested Citation

  • Liu, Qian & Gao, Jian & Li, Shijie, 2024. "The innovation model and upgrade path of digitalization driven tourism industry: Longitudinal case study of OCT," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
  • Handle: RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523008120
    DOI: 10.1016/j.techfore.2023.123127
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523008120
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2023.123127?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.

    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:200:y:2024:i:c:s0040162523008120. 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.