IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-032-13388-5_20.html

Exploring the Nexus Among AI-Generated Advertising Bias, Deepfake Technology, and Consumer Trust: The Moderating Role of Technological Literacy

In: Embracing Technological Agility in Accounting and Business – Vol. 3

Author

Listed:
  • Frank Frimpong Opuni

    (Accra Technical University)

  • Joshua Doe

    (University of Media Arts and Communication)

  • Irene Akaab

    (Accra Technical University)

  • Hayford Amegbe

    (International University of Rabat)

  • Kwabena Asamoah Asiedu

    (Accra Technical University)

Abstract

This study examines how algorithmic bias (AB), deepfake technology (DT), and AI-generated advertising bias (AIAB) influence consumer trust in digital messages, with a focus on the mediating roles of perception of authenticity (POA) and cognitive response (CR), and the moderating role of technological literacy (TL) in Ghana’s digital advertising context. Using a hybrid PLS-SEM and artificial neural network (ANN) approach, data from 510 e-commerce users revealed that AB and DT reduce POA, while AIAB negatively affects CR. Both POA and CR positively influence trust in messages, and TL weakens the negative effects of DT and AIAB, indicating that digitally literate consumers are more discerning. The study contributes to theory by contextualizing algorithmic influence in Sub-Saharan Africa and highlights policy implications for promoting digital literacy and algorithmic transparency

Suggested Citation

  • Frank Frimpong Opuni & Joshua Doe & Irene Akaab & Hayford Amegbe & Kwabena Asamoah Asiedu, 2026. "Exploring the Nexus Among AI-Generated Advertising Bias, Deepfake Technology, and Consumer Trust: The Moderating Role of Technological Literacy," Springer Proceedings in Business and Economics, in: Tankiso Moloi (ed.), Embracing Technological Agility in Accounting and Business – Vol. 3, pages 287-303, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-13388-5_20
    DOI: 10.1007/978-3-032-13388-5_20
    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
    for a similarly titled item that would be available.

    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:spr:prbchp:978-3-032-13388-5_20. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.