IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v81y2024ics0969698924002844.html
   My bibliography  Save this article

Online shopping: How can algorithm performance expectancy enhance impulse buying?

Author

Listed:
  • Gallin, Steffie
  • Portes, Audrey

Abstract

Building on the literature on trust and Persuasion Knowledge Theory, this study examines the mediating role of trust in the relationship between algorithm performance expectancy and impulse buying in online retailing. Furthermore, it examines how impulse buying among online shoppers is influenced by the number of product recommendations displayed on a retailer's website (a small vs. large number of recommendations), along with the presence or absence of recommendation ratings. A survey-based study and an experiment indicated that consumer trust in algorithm-driven product recommendations correlates with heightened impulse buying of a recommended product, particularly when a large number of recommendations are presented. However, the presence (vs. absence) of recommendation ratings had no impact on impulse buying. This study extends literature on the impact of product recommendation design. This contributes to a deeper understanding of how product recommendation formats influence consumer behavior and offers insights for retailers regarding the strategic presentation of personalized product recommendations to enhance impulse buying.

Suggested Citation

  • Gallin, Steffie & Portes, Audrey, 2024. "Online shopping: How can algorithm performance expectancy enhance impulse buying?," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
  • Handle: RePEc:eee:joreco:v:81:y:2024:i:c:s0969698924002844
    DOI: 10.1016/j.jretconser.2024.103988
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698924002844
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jretconser.2024.103988?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:joreco:v:81:y:2024:i:c:s0969698924002844. 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: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.