IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v200y2025ics0148296325004205.html
   My bibliography  Save this article

How sentiment volatility of influencer product recommendation posts affects customer engagement

Author

Listed:
  • Zhang, Mingli
  • Xie, Kesheng
  • Cai, Shensheng
  • Wang, Yu

Abstract

Social media influencers’ involvement in product promotion is a popular trend. The effectiveness of their product recommendation posts largely depends on customer engagement. Influencers organize sentences of different sentiment valence in a specific sequence when offering products’ basic information, sharing usage experiences, and providing product evaluations in the product recommendation posts, resulting in dynamic changes in sentence sentiment valence, that is, sentiment volatility. Drawing on narrative transportation theory, an investigation—combining an analysis of 12,849 influencer product recommendation posts on the Xiaohongshu platform (Study 1) and a further controlled experiment (Study 2) — reveals that sentiment volatility negatively affects customer engagement and this effect is driven by narrative transportation. Additionally, Study 1 indicates that the influencer type (micro- vs. macro-influencers) and product type (search vs. experience goods) have moderating effects. Our study advances sentiment research in influencer marketing and offers practical insights into narrative sentiment strategies for influencers’ product recommendations.

Suggested Citation

  • Zhang, Mingli & Xie, Kesheng & Cai, Shensheng & Wang, Yu, 2025. "How sentiment volatility of influencer product recommendation posts affects customer engagement," Journal of Business Research, Elsevier, vol. 200(C).
  • Handle: RePEc:eee:jbrese:v:200:y:2025:i:c:s0148296325004205
    DOI: 10.1016/j.jbusres.2025.115597
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325004205
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2025.115597?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:eee:jbrese:v:200:y:2025:i:c:s0148296325004205. 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.elsevier.com/locate/jbusres .

    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.