IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04692534.html
   My bibliography  Save this paper

Would an AI chatbot persuade you : An empirical answer from the elaboration likelihood model

Author

Listed:
  • Qian Chen

    (HZAU - Huazhong Agricultural University [Wuhan])

  • Changqin Yin

    (Wuhan Polytechnic University)

  • Yeming Gong

    (EM - EMLyon Business School)

Abstract

Purpose This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context. Design/methodology/approach Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users. Findings The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively. Originality/value This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

Suggested Citation

  • Qian Chen & Changqin Yin & Yeming Gong, 2023. "Would an AI chatbot persuade you : An empirical answer from the elaboration likelihood model," Post-Print hal-04692534, HAL.
  • Handle: RePEc:hal:journl:hal-04692534
    DOI: 10.1108/ITP-10-2021-0764
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:hal:journl:hal-04692534. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.