Published Online:November 2025
Product Name:The IUP Journal of Marketing Management
Product Type:Article
Product Code:IJMM011125
DOI:10.71329/IUPJMM/2025.24.4.5-38
Author Name:Md Saifullah Khalid
Availability:YES
Subject/Domain:Management
Download Format:PDF
Pages:5-38
The study develops a theoretical model to understand how perceptions of authenticity, consumer decision biases, trust, risk perception, technology acceptance, emotional responses, and media literacy levels interact within the context of deepfakes. Using a cross-sectional methodology in Jharkhand, India, data was obtained from Internet users aged 18 years and above through online and offline surveys. The questionnaire was based on established measures found in the literature. Analysis of 419 valid responses revealed that perceptions of authenticity did not significantly influence consumer decision biases or trust in deepfake content. Consumer decision biases were, however, significantly impacted by trust in deepfake content, and a strong relationship was found between risk perception and trust in deepfake content. Technology acceptance, emotional responses, and media literacy levels did not significantly affect decision biases or trust in relation to deepfake content. The results highlighted the need for adaptable regulations, media literacy education, and technological solutions to mitigate the possible harm that deepfakes may cause in the digital sphere
Deepfake technology, leveraging AI to produce convincing but invented images and videos, holds substantial implications for consumer behavior. While Tong et al. (2020) provided an overview of its development and applications, Kwok and Koh (2021) highlighted its prospective benefits. However, there is still reason for concern over malevolent use, such as production of harmful fake videos (Campbell et al., 2022; Rahman et al., 2022).