Search Results (87)

This study aims to investigate the relationship between consumer neuroscience and neuromarketing using a multivariate methodology. Tools such as Principal Component Analysis (PCA) and deep learning neural networks were employed to interpret consumer responses to functional products. To this end, EEG signals were collected, recorded, and analyzed from 83 participants aged 20 to 29 to identify significant neural markers related to food consumption decisions. Key factors influencing decision making were identified, including low beta and gamma frequency bands. Participants’ levels of attention and reflection also played a role. The findings validate the effectiveness of the proposed method, demonstrating its applicability in various fields requiring accurate and reliable classification. Furthermore, some possible applications of this topic are mentioned in the food industry section, with the aim of enabling them to develop personalized nutritional strategies based on the results obtained from the brain activity of consumers. Full article

This study evaluates whether an AI-built DeFi website case can match professionally developed DeFi platforms in digital marketing performance, innovation-related strategic behavior, and entrepreneurial impact. Using a multi-method design, we compare five established DeFi websites (Aave, Lido, Curve, MakerDAO, Uniswap) against one AI-built interface (Nexus Protocol). The analysis is designed as a five-platform benchmarking study of established professional DeFi websites, complemented by one AI-built case (Nexus Protocol) used as an illustrative comparison rather than a representative class of AI-built interface. The objectives are to (i) test differences in traffic composition and acquisition strategies, (ii) quantify how engagement signals predict authority and branded traffic, (iii) examine cognitive processing and trust-cue attention via eye tracking, and (iv) model emergent engagement and authority dynamics using agent-based simulation (ABM). Web analytics (March–October 2025) show significant variation in traffic composition across professional platforms (ANOVA F = 3.41, p = 0.0205), while regression models indicate that time on site and pages per visit positively predict Authority Score (R² = 0.61) and Branded Traffic (R² = 0.55), with bounce rate exerting an adverse effect. PCA and k-means clustering identify three strategic archetypes (innovation-driven, balanced-growth, efficiency-focused). Eye-tracking results show that professional interfaces generate tighter fixation clusters and shorter scan paths, indicating higher cognitive efficiency. In contrast, fixation on key UI elements and trust cues is comparable across interface types. ABM outputs further suggest that reduced engagement depth in the AI-built interface yields weaker long-run branded-traffic and authority trajectories. Overall, the study provides an integrated evaluation framework and evidence-based implications for AI-driven interface design in high-trust fintech environments. Full article

Virtual reality (VR) provides immersive environments that resemble real-world consumption settings, enabling realistic analysis of consumer responses to advertisements. Therefore, VR has been increasingly adopted in marketing. Visual attention is a key indicator of advertising effectiveness, and neuromarketing approaches using eye-tracking are widely used to overcome the limitations of self-report measures by providing objective insights into attentional processes. However, most previous studies have focused on static retail environments, leaving a research gap in understanding advertising effectiveness in dynamic road traffic contexts. Guided by selective attention theory, this study addresses this gap by integrating VR and eye-tracking to examine how advertisement placement under different traffic conditions influences visual attention and recall. A real-time eye-tracking measurement system was developed, and fixation duration, fixation count, and recall were used as evaluation metrics. The results showed significant differences across advertisement placement types. Advertisements positioned in front of buildings during stops elicited the highest levels of visual attention and recall, indicating that attention is greater when users are stationary than when riding. These findings indicate that cognitive resources shift from traffic-related tasks to advertisements as cognitive load decreases, highlighting the effectiveness of integrating VR and eye-tracking to objectively evaluate advertising outcomes in dynamic environments. Full article

This study investigates how neuromarketing practices intersect with consumer privacy regulation in California, with particular attention to the 2024 Senate Bill 1223 (SB 1223), which amends the CCPA/CPRA to explicitly define “neural data.” By examining corporate strategies and regulatory frameworks, the paper evaluates how firms navigate the tension between innovation, ethics, and consumer protection. A qualitative, multiple-case study approach was adopted, focusing on Coca-Cola, Frito-Lay, and Hyundai. Data were collected from corporate privacy policies, industry publications, and legislative documents, triangulated through doctrinal legal analysis and cross-case synthesis. The analysis reveals that, while companies comply with disclosure, consent, and oversight requirements under the CCPA/CPRA, such compliance remains largely procedural, with transparency often being technical rather than consumer-friendly, consent being insufficiently informed, and protections for vulnerable groups being inconsistently enforced. SB 1223’s recent definition of neural data directly encompasses techniques such as EEG, fMRI, eye-tracking, and biometrics, underscoring the urgent need for firms to treat neuromarketing as a category of regulated practice rather than discretionary innovation. The study is limited by its reliance on publicly available documentation and by the recency of SB 1223, which precludes observation of mature compliance patterns. Future research should explore consumer perceptions, track evolving regulatory responses, and extend the analysis across various sectors, including healthcare, education, and non-profits. This study contributes to theory by extending stakeholder theory to neural data governance and by conceptualizing neuromarketing as a governance-intensive strategic capability situated at the frontier of consumer rights and technological innovation. It contributes to practice by demonstrating how firms can transform compliance with emerging neural data regulations into a strategic capability that strengthens consumer trust, ethical legitimacy, and brand equity. Full article

The reuse of by-products from plant processing as feed for animals aligns with the principles of a circular economy. Feeding dairy ruminants agro-industrial by-products often alters the chemical composition and sensory characteristics of dairy items. A dual approach—classic with neuro-sensory techniques—was utilized to evaluate the effect of prickly pear by-products on the diets of dairy ewes. Fresh Pecorino cheeses made from the milk of two groups of sheep fed with and without prickly pear by-product silage were analyzed for chemical composition and volatile organic compounds (VOCs). Furthermore, a neurosensory approach with consumers was used, combining electroencephalography (EEG) and temporal dominance of sensations techniques (TDS). Prickly pear silage in sheep diets did not alter the chemical composition of fresh cheese, but it did modify its fatty acids, with a significant increase in SFA (+2.60%) and PUFA (+0.33%), with a better n-6/n-3 ratio (−0.35%) due to higher omega-3 fatty acid content (+0.23%). The identification of VOCs revealed an increase in caproic acid (+27.27%) and n-caprylic acid (+6.47%) and a greater presence of sweet notes in the prickly pear-based cheeses, which exhibited a different aromatic complexity compared with the control cheeses. Even with a neuromarketing approach, sweetness remained the predominant sensation. Full article

This study introduces a machine learning–driven extended reality (XR) interaction framework that leverages electroencephalography (EEG) for decoding consumer intentions in immersive decision-making tasks, demonstrated through functional food purchasing within a simulated autonomous vehicle setting. Recognizing inherent limitations in traditional “Preference vs. Non-Preference” EEG paradigms for immersive product evaluation, we propose a novel and robust “Rest vs. Intention” classification approach that significantly enhances cognitive signal contrast and improves interpretability. Eight healthy adults participated in immersive XR product evaluations within a simulated autonomous driving environment using the Microsoft HoloLens 2 headset (Microsoft Corp., Redmond, WA, USA). Participants assessed 3D-rendered multivitamin supplements systematically varied in intrinsic (ingredient, origin) and extrinsic (color, formulation) attributes. Event-related potentials (ERPs) were extracted from 64-channel EEG recordings, specifically targeting five neurocognitive components: N1 (perceptual attention), P2 (stimulus salience), N2 (conflict monitoring), P3 (decision evaluation), and LPP (motivational relevance). Four ensemble classifiers (Extra Trees, LightGBM, Random Forest, XGBoost) were trained to discriminate cognitive states under both paradigms. The ‘Rest vs. Intention’ approach achieved high cross-validated classification accuracy (up to 97.3% in this sample), and area under the curve (AUC > 0.97) SHAP-based interpretability identified dominant contributions from the N1, P2, and N2 components, aligning with neurophysiological processes of attentional allocation and cognitive control. These findings provide preliminary evidence of the viability of ERP-based intention decoding within a simulated autonomous-vehicle setting. Our framework serves as an exploratory proof-of-concept foundation for future development of real-time, BCI-enabled in-transit commerce systems, while underscoring the need for larger-scale validation in authentic AV environments and raising important considerations for ethics and privacy in neuromarketing applications. Full article

Augmented Reality (AR) is a technology adopted by brands to innovate packaging and improve communication with consumers. Companies integrate AR features into their packaging, choosing between different approaches. However, it is still unclear how different AR typologies can influence consumers’ perceptions during the interaction. For this purpose, this exploratory study aims to analyze the differences between two types of AR—static vs. immersive—applied to packaging, evaluating their impact and effectiveness on consumers. A within-subjects design, on a sample of 20 participants, was employed using neuroscientific techniques (electroencephalography, heart rate, and skin conductance) to explore the cognitive and emotional engagement based on the AR interaction, as well as self-report measures (Augmented Reality Immersion, Perceived Informativeness and Authenticity). Neurophysiological findings indicated that the immersive AR application elicited a greater emotional and partially cognitive engagement, as well as a higher perceived immersion, according to self-reports. The study’s findings offer a deeper understanding of how consumers’ perceptions can change in response to different types of AR content. Although AR is not yet widely accessible as a marketing tool for brands, its growing technological feasibility makes it relevant to know its potential effects on consumers. Thus, this study will offer useful insights for companies to direct their investments toward AR applications in marketing campaigns. Full article

Sustainable tourism requires balancing environmental protection, social equity, and economic viability, yet its effective promotion depends on communication strategies that genuinely capture travelers’ attention. Despite growing emphasis on ecological responsibility in marketing, little is known about how sustainability-related content in tourism advertising is actually perceived. This study addresses this gap by examining visual attention to eco-oriented elements in promotional materials through eye-tracking technology. The research aimed to identify whether ecological certifications, slogans, and related cues attract attention and influence consumer choices, and to assess how these processes are moderated by individual ecological awareness. An experimental design was conducted with 23 young adults (aged 18–22) who viewed three tourism offers differing in their degree of sustainability messaging. Eye movements were recorded with the Gazepoint GP3 HD eye-tracker, focusing on predefined Areas of Interest (AOIs), including ecological certificates, pricing, and imagery. Heatmaps and fixation metrics were complemented by a post-exposure questionnaire. The results indicate that visually dominant components such as destination images and pricing consistently attracted the most attention, while sustainability cues were noticed but rarely prioritized. Participants with higher ecological awareness actively sought and recalled these elements, highlighting the moderating role of intrinsic motivation. The study contributes to both sustainable tourism and neuromarketing research by demonstrating how ecological values interact with perceptual behavior. Practically, it shows that eye-tracking can guide the optimal placement and design of sustainability cues in advertising. The exploratory nature and small, homogeneous sample are acknowledged as limitations, but they provide a valuable foundation for future large-scale studies. Full article

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 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

As digital marketing becomes more targeted and interactive, it is more critical to understand how young audiences perceive and react to compelling content. This research examines the extent to which consumer responses are affected by neuromarketing knowledge, interest, and screen-based advert exposure for middle school kids. Based on responses from 244 Greek adolescents aged 12–15 years, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to investigate direct and mediated influences on purchase intentions with advertisement skepticism and persuasion knowledge as mediating factors. Results indicate that exposure and recognition have a significant influence on intentions both by means of cognitive as well as attitudinal processes, while interest only increases skepticism but not interaction. Multi-group analysis yielded significant differences according to age and experience, referring to the development path of advertising literacy. The results provide strong cues to educators, policymakers, and marketers who want to develop media-critical competencies among adolescents in an ever-shaping digital age. Full article

Rural agricultural markets face unique challenges, yet neuromarketing applications in this sector are understudied. This systematic review investigates how neuroscience has been applied to shape marketing narratives for rural agricultural producers. The objectives were to catalog relevant studies, identify key themes using inductive thematic synthesis, and derive practical implications for rural marketing strategy and future research. We systematically searched English-language, peer-reviewed studies published between 2016 and 2024 across multiple academic databases, following PRISMA guidelines. Two independent reviewers screened the records, resulting in the inclusion of 20 studies. Key data from each study were extracted and synthesized using an inductive thematic analysis approach. The synthesis revealed several recurrent findings. First, in terms of social and community context, farmers showed greater trust and engagement with familiar local buyers than with distant corporations, indicating that local relationships strongly influence producer behavior. Second, regarding product and narrative attributes, marketing narratives that emphasized local provenance, organic or sustainable production, and ethical values such as animal welfare and environmental sustainability resonated strongly with rural consumers. Third, sensory and emotional cues particularly visual elements and storytelling techniques including color, imagery, and packaging design consistently enhanced consumer attention and engagement. Overall, these neuroscience-informed themes suggest that marketing narratives emphasizing authenticity, trust-building, and community values can effectively strengthen rural agricultural marketing. This review provides neuroscience-informed interpretations of key rural marketing challenges, drawing on dual-process theory and consumer decision models for applying neuromarketing insights in this context. Practically, rural producers can leverage these findings by designing marketing messages and packaging that highlight local identity and ethical values, thereby building consumer trust and loyalty. The review also highlights gaps such as the need for more field-based neuromarketing studies and suggests directions for future research, offering guidance for both scholars and practitioners working at the intersection of neuroscience and rural consumer behavior. Full article

In recent years, virtual anchors have become vital in live marketing due to their anthropomorphic features and interactive advantages. However, are anthropomorphic virtual anchors the best option? This study employs neuromarketing tools to examine the impact of virtual anchor appearance on consumer purchase intention, investigating the mediating role of emotional response and the moderating role of product type. The findings reveal the following: (1) the anthropomorphism level of virtual anchors is significantly positively correlated with purchase intention; (2) anthropomorphism exhibits a positive U-shaped relationship with emotional response, while inhuman images rapidly trigger emotional arousal, but this does not directly translate into purchase behavior; (3) for hedonic products, high anthropomorphism significantly increases purchase intention, whereas utilitarian products are more likely to be purchased when anthropomorphism is low. These findings provide a theoretical foundation for virtual anchor design, address the empirical gap regarding the interaction between anthropomorphism and product type, and offer scientific guidance for digital marketing strategies. Full article

This study examines the influence of dynamic and verbal elements in logo design on consumer behaviour in the luxury retail sector using advanced neuroscience technology (Predict v.1.0) and traditional cognitive survey methods. AI-powered eye tracking (n = 255,000), EEG technology (n = 45,000), implicit testing (n = 9000), and memory testing (n = 7000) were used to predict human behaviour. Qualitative cognitive surveys (n = 297), saliency map analysis, and emotional response evaluation were employed to analyse three distinct logo designs. The results indicate that logos with prominent dynamic elements, particularly visually distinct icons, demonstrate superior performance in capturing and maintaining viewer attention compared with static designs. A strong correlation was found between cognitive demand and engagement, suggesting that dynamic elements enhance emotional connections and brand recall. However, the effectiveness of dynamic features varied, with more pronounced elements yielding better results for industry associations and premium market alignment. This study, combining advanced neuroscience technology with traditional cognitive survey methods, makes significant contributions to the field and opens up new avenues for research and application. The findings provide valuable insights for luxury brand managers in optimising logo designs to enhance emotional connection and brand perception and improve academia by providing powerful tools for understanding and predicting human responses to visual stimuli. Full article

This study compared the efficacy of AI neuroscience tools versus traditional design methods in enhancing viewer engagement with political campaign materials from the Harris–Trump presidential campaigns. Utilising a mixed-methods approach, we integrated quantitative analysis employing AI’s eye-tracking consumer behaviour metrics (Predict, trained on 180,000 screenings) with an AI-LLM neuroscience-based marketing assistant (CoPilot), with 67,429 areas of interest (AOIs). The original flyer, from an Al Jazeera article, served as the baseline. Professional graphic designers created three redesigned versions, and one was done using recommendations from CoPilot. Metrics including total attention, engagement, start attention, end attention, and percentage seen were evaluated across 13–14 areas of interest (AOIs) for each design. Results indicated that human-enhanced Design 1 with AI eye-tracking achieved superior overall performance across multiple metrics. While the AI-enhanced Design 3 demonstrated strengths in optimising specific AOIs, it did not consistently outperform human-touched designs, particularly in text-heavy areas. The study underscores the complex interplay between neuroscience AI algorithms and human-centred design in political campaign branding, offering valuable insights for future research in neuromarketing and design communication strategies. Python, Pandas, Matplotlib, Seaborn, Spearman correlation, and the Kruskal–Wallis H-test were employed for data analysis and visualisation. Full article