IDEAS home Printed from https://ideas.repec.org/a/taf/jgsmks/v32y2022i3p415-433.html
   My bibliography  Save this article

Online knowledge sharing capability of young employees: An empirical study

Author

Listed:
  • Tuyet-Mai Nguyen
  • Marie-Louise Fry

Abstract

Along with the development of information technology and artificial intelligence, online knowledge sharing has become an essential organizational resource. Online knowledge sharing can contribute to the success of organizations through effective knowledge management which is often enhanced by using artificial intelligence techniques. Young employees often make up the largest segment in organizations, but they tend to start their early career with temporary contracts which impact their likelihood to hide or hoard organizational knowledge. This study examines knowledge self-efficacy, perceived ease of use, organizational rewards, and top management support affecting the online knowledge sharing capability of young employees. A survey was conducted in Vietnam, targeting young employees aged 18–30 in three key industries. Results indicate that knowledge self-efficacy, perceived ease of use, and top management support significantly influence young employees’ online knowledge sharing. Interestingly, organizational rewards were found to only impact lurkers’ online knowledge sharing and work effectively if employees have either high perceived ease of use or top management support.

Suggested Citation

  • Tuyet-Mai Nguyen & Marie-Louise Fry, 2022. "Online knowledge sharing capability of young employees: An empirical study," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 32(3), pages 415-433, July.
    • Handle: RePEc:taf:jgsmks:v:32:y:2022:i:3:p:415-433
    DOI: 10.1080/21639159.2020.1808849
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/21639159.2020.1808849
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/21639159.2020.1808849?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. Ting Nie & Yanli Gui & Yiying Huang, 2024. "Online sharing behaviors driven by need for approval: the choice of individuals with low social intelligence and high gratitude?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.

    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:415-433. 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.