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Human–Computer Interaction in Marketing: Emerging Interfaces, Cognitive Engagement, and Child–Computer...
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Human–Computer Interaction in Marketing: Emerging Interfaces, Cognitive Engagement, and Child–Computer Interaction

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 1760

Special Issue Editors

Dr. Stefanos Balaskas

E-Mail Website
Guest Editor
Department of Management Science and Technology, University of Patras, Pátrai, Greece
Interests: neuromarketing; human–computer interaction; eye tracking; child–computer interaction; behavioral data analysis; structural equation modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Birgitta Dresp-Langley

E-Mail Website
Guest Editor
Centre National de la Recherche Scientifique (CNRS), ICube Lab UMR 7357 CNRS, Université de Strasbourg, F-67081 Strasbourg, France
Interests: cognitive neuroscience; brain; cognitive psychology; behavior; perceptual learning and memory; neural networks; consciousness; philosophy of artificial intelligence; principles of unsupervised learning; computing and philosophy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The intersection between human–computer interaction (HCI) and marketing presents a dynamic field of study with increasing relevance in both academic and applied contexts. As digital environments grow more interactive, personalized, and persuasive, understanding how users engage with marketing content—both cognitively and behaviorally—becomes essential.

This Special Issue seeks to explore cutting-edge research at the crossroads of HCI and marketing, with a special emphasis on emerging interfaces, cognitive engagement, and the evolving field of child–computer interaction in marketing contexts. Topics may include user experience and interface design, persuasive technologies, eye-tracking studies, emotional and attentional responses, and ethical considerations in interactive systems that target adults or children.

We invite interdisciplinary contributions from scholars working in the fields of HCI, digital marketing, communication, and education technology.

Topics of interest include, but are not limited to, the following:

  • Eye-tracking and attention in digital marketing;
  • UX/UI evaluation for persuasive systems and apps;
  • Child–computer interaction and advertising literacy;
  • Emotional and cognitive engagement in HCI;
  • Ethical and privacy issues in interactive marketing;
  • Neuromarketing and biometric data applications;
  • Augmented/virtual reality in brand interaction;
  • Personalized recommendations and AI-driven interfaces;
  • Behavioral and psychometric analyses of digital consumers.

We look forward to your valuable contributions to this Special Issue.

Dr. Stefanos Balaskas
Prof. Dr. Birgitta Dresp-Langley
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human–computer interaction
  • neuromarketing
  • eye tracking
  • digital advertising
  • user experience
  • child–computer interaction
  • persuasive technology
  • behavioral data analysis
  • ethical design

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Published Papers (2 papers)

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Research

28 pages, 6595 KB  
Article
Identifying Individual Information Processing Styles During Advertisement Viewing Through EEG-Driven Classifiers
by Antiopi Panteli, Eirini Kalaitzi and Christos A. Fidas
Information 2025, 16(9), 757; https://doi.org/10.3390/info16090757 - 1 Sep 2025
Viewed by 575
Abstract
Neuromarketing studies the brain function as a response to marketing stimuli. A large amount of neuromarketing research uses data from electroencephalography (EEG) recordings as a response of individuals’ brains to marketing stimuli, aiming to identify the factors that influence consumer behaviour that they [...] Read more.
Neuromarketing studies the brain function as a response to marketing stimuli. A large amount of neuromarketing research uses data from electroencephalography (EEG) recordings as a response of individuals’ brains to marketing stimuli, aiming to identify the factors that influence consumer behaviour that they cannot articulate or are reluctant to reveal. Evidence suggests that individuals’ processing styles affect their reaction to marketing stimuli. In this study, we propose and evaluate a predictive model that classifies consumers as verbalizers or visualizers based on EEG signals recorded during exposure to verbal, visual, and mixed advertisements. Participants (N = 22) were categorized into verbalizers and visualizers using the Style of Processing (SOP) scale and underwent EEG recording while viewing ads. The EEG signals were preprocessed and the five EEG frequency bands were extracted. We employed three classification models for every set of ads: SVM, Decision Tree, and kNN. While all three classifiers performed around the same, with accuracy between 86 and 93%, during cross-validation SVM proved to be the more effective model, with kNN and Decision Tree showing sensitivity to data imbalances. Additionally, we conducted independent t-tests to look for statistically significant differences between the two classes. The t-tests implicated the Theta frequency band. Therefore, these findings highlight the potential of leveraging EEG-based technology to effectively predict a consumer’s processing style for advertisements and offers practical applications in fields such as interactive content designs and user-experience personalization. Full article
(This article belongs to the Special Issue Human–Computer Interaction in Marketing: Emerging Interfaces, Cognitive Engagement, and Child–Computer Interaction)
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16 pages, 2093 KB  
Article
Neuromarketing and Health Marketing Synergies: A Protection Motivation Theory Approach to Breast Cancer Screening Advertising
by Dimitra Skandali, Ioanna Yfantidou and Georgios Tsourvakas
Information 2025, 16(9), 715; https://doi.org/10.3390/info16090715 - 22 Aug 2025
Viewed by 714
Abstract
This study investigates the psychological and emotional mechanisms underlying women’s reactions to breast cancer awareness advertisements through the dual lens of Protection Motivation Theory (PMT) and neuromarketing methods, addressing a gap in empirical research on the integration of biometric and cognitive approaches in [...] Read more.
This study investigates the psychological and emotional mechanisms underlying women’s reactions to breast cancer awareness advertisements through the dual lens of Protection Motivation Theory (PMT) and neuromarketing methods, addressing a gap in empirical research on the integration of biometric and cognitive approaches in health marketing. Utilizing a lab-based experiment with 78 women aged 40 and older, we integrated Facial Expression Analysis using Noldus FaceReader 9.0 with semi-structured post-exposure interviews. Six manipulated health messages were embedded within a 15 min audiovisual sequence, with each message displayed for 5 s. Quantitative analysis revealed that Ads 2 and 5 elicited the highest mean fear scores (0.45 and 0.42) and surprise scores (0.35 and 0.33), while Ad 4 generated the highest happiness score (0.31) linked to coping appraisal. Emotional expressions—including fear, sadness, surprise, and neutrality—were recorded in real time and analyzed quantitatively. The facial analysis data were triangulated with thematic insights from interviews, targeting perceptions of threat severity, vulnerability, response efficacy, and self-efficacy. The findings confirm that fear-based appeals are only effective when paired with actionable coping strategies, providing empirical support for PMT’s dual-process model. By applying mixed-methods analysis to the evaluation of health messages, this study makes three contributions: (1) it extends PMT by validating the emotional–cognitive integration framework through biometric–qualitative convergence; (2) it offers practical sequencing principles for combining threat and coping cues; and (3) it proposes cross-modal methodology guidelines for future health campaigns. Full article
(This article belongs to the Special Issue Human–Computer Interaction in Marketing: Emerging Interfaces, Cognitive Engagement, and Child–Computer Interaction)
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