IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v44y2025i12p2913-2928.html
   My bibliography  Save this article

Examining the persuasiveness of text and voice agents: prosody aligned with information structure increases human-likeness, perceived personalisation and brand attitude

Author

Listed:
  • Hilde Voorveld
  • Andreas Panteli
  • Yoni Schirris
  • Carolin Ischen
  • Evangelos Kanoulas
  • Tom Lentz

Abstract

To give product and brand recommendations, marketers make use of conversational agents which increasingly communicate via voice rather than text. Existing research comparing the persuasiveness of text and voice agents showed mixed results. The quality of the speech synthesis employed may strongly influence consumers’ responses. This study investigates to what extent a voice agent with pragmatically aligned prosody is more persuasive (i.e. yields a more positive brand attitude) than an agent with a standard voice or text, and whether perceived human-likeness and perceived personalisation provide an underlying mechanism to explain these differences. In an experiment (n = 212), participants interacted with a conversational agent that recommended a camera. Results showed that a voice agent using prosody aligned to the information state of the user is more persuasive than a text agent. This effect is mediated by perceived human-likeness and perceived personalisation. Hence, aligned prosody can make synthetic speech meet a certain quality threshold to be perceived as more human-like. Theoretically, this study helps to unravel why conversational agents with human-like features are more persuasive.

Suggested Citation

  • Hilde Voorveld & Andreas Panteli & Yoni Schirris & Carolin Ischen & Evangelos Kanoulas & Tom Lentz, 2025. "Examining the persuasiveness of text and voice agents: prosody aligned with information structure increases human-likeness, perceived personalisation and brand attitude," Behaviour and Information Technology, Taylor & Francis Journals, vol. 44(12), pages 2913-2928, July.
  • Handle: RePEc:taf:tbitxx:v:44:y:2025:i:12:p:2913-2928
    DOI: 10.1080/0144929X.2024.2420871
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2024.2420871
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2024.2420871?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

    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:tbitxx:v:44:y:2025:i:12:p:2913-2928. 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/tbit .

    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.