IDEAS home Printed from https://ideas.repec.org/a/wsi/cjuesx/v10y2022i04ns2345748122500245.html
   My bibliography  Save this article

The Impact of Artificial Intelligence (AI) on the Low-Carbon Economy: A Prospective Study on the Long-Term Rental Housing Market in Guangxi, China

Author

Listed:
  • Dandan LI

    (School of Management, Universiti Sains Malaysia, 11800 Penang, Malaysia2Business School of Guilin University of Technology, No. 12 Jiangan Road, Guilin 541000, China)

  • Nik Hadiyan Nik AZMAN

    (School of Management, Universiti Sains Malaysia, 11800 Penang, Malaysia)

Abstract

In recent years, the tourism economy of Guangxi Zhuang Autonomous Region (hereinafter referred to as “Guangxi†), China, has been caught in the contradiction between infrastructure construction and natural environmental protection. By combing Guangxi’s tourism economy with its development path of smart long-term rental housing, this paper finds that the long-term rental market in Guangxi based on artificial intelligence (AI) technology can solve the development contradiction through accurate construction planning to improve efficiency. The long-term rental housing market in Guangxi has entered a low-carbon economy period since pilot programs were launched for the policy of managing public rental housing with AI and information technologies. From the perspective of AI, facts have proved that AI has the ability to re-adjust the competition order of an industry, which not only realizes the low-carbon development of the rental market, but also promotes the industrial upgrading of the tourist industry.

Suggested Citation

  • Dandan LI & Nik Hadiyan Nik AZMAN, 2022. "The Impact of Artificial Intelligence (AI) on the Low-Carbon Economy: A Prospective Study on the Long-Term Rental Housing Market in Guangxi, China," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 1-14, December.
  • Handle: RePEc:wsi:cjuesx:v:10:y:2022:i:04:n:s2345748122500245
    DOI: 10.1142/S2345748122500245
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2345748122500245
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S2345748122500245?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:wsi:cjuesx:v:10:y:2022:i:04:n:s2345748122500245. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/cjues/cjues.shtml .

    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.