IDEAS home Printed from https://ideas.repec.org/a/taf/jgsmks/v32y2022i3p434-451.html
   My bibliography  Save this article

A systematic literature review of AI in the sharing economy

Author

Listed:
  • Ying Chen
  • Catherine Prentice
  • Scott Weaven
  • Aaron Hsiao

Abstract

Although artificial intelligence (AI) has been adopted in sharing economy platforms, few studies have investigated this phenomenon in this context. Consequently, there is no thorough overview of how AI has been used in the sharing economy. To address this research gap, a systematic literature review was performed for this paper. This method can be useful for the exploration of new and emerging trends within disciplines and allows boundaries to be mapped on what is known thereby identifying gaps on what is yet to be known. After screening, 28 English journal articles were selected in a qualitative synthesis. Results show AI can help the sharing economy platforms by enhancing trust, matching assets, and understanding participants’ preferences and attitudes. Based on these findings, potential directions are established. The current study will contribute to both the sharing economy and AI literature, and the results may help practitioners and academia to achieve a greater understanding of this topic.

Suggested Citation

  • Ying Chen & Catherine Prentice & Scott Weaven & Aaron Hsiao, 2022. "A systematic literature review of AI in the sharing economy," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 32(3), pages 434-451, July.
    • Handle: RePEc:taf:jgsmks:v:32:y:2022:i:3:p:434-451
    DOI: 10.1080/21639159.2020.1808850
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/21639159.2020.1808850
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/21639159.2020.1808850?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. Muhammad Salman Pathan & Edana Richardson & Edgar Galvan & Peter Mooney, 2023. "The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland," Sustainability, MDPI, vol. 15(12), pages 1-18, June.

    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:taf:jgsmks:v:32:y:2022:i:3:p:434-451. 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/RGAM20 .

    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.