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Cognitive and affective reactions to virtual facial representations in cosmetic advertising: a comparison of idealized and naturalistic features
File(s)
electronics-14-03677.pdf (2.29 MB)
Published version
Author(s)
Xu, Lu
Zou, Yixin
Tian, Hannuo
Childs, Peter
Xiaoying, Tang
Type
Journal Article
Abstract
The rise of virtual models in the digital age presents a new frontier for cosmetic advertising. Nevertheless, the comparative effectiveness of “idealized” versus “naturalistic” facial features in these models remains a topic of debate and an area of development. This study examines the impact of “idealized” and “naturalistic” facial features in virtual models on consumers’ cognitive and affective responses. Using eye-tracking and a structural equation model, we analyzed visual attention patterns and the roles of affective resonance, trustworthiness, likability, and expertise perception. The results indicate that non-homogeneous or defective naturalistic features increase visual attention and purchase intention, with consumers focusing on imperfections such as freckles. In contrast, idealized facial features mainly draw attention to areas such as the eyes and nose. Mediation analysis reveals that likability and affective resonance are primary influences on purchase intention, while expertise perception and trustworthiness are secondary. This experiment suggests that consumers prioritize socio-emotional connections over professional authority when evaluating naturalistic designs. Our findings provide a framework for virtual model design, helping brands balance aesthetics with psychological optimization, and offer insights into the interplay between visual stimuli and human cognitive and emotional processes in decision-making.
Date Issued
2025-09-01
Date Acceptance
2025-09-10
Citation
Electronics, 2025, 14 (18)
URI
URL
DOI
ISSN
2079-9292
Publisher
MDPI AG
Journal / Book Title
Electronics
Volume
14
Issue
18
Copyright Statement
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
3677
Date Publish Online
2025-09-17