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Systematic Review

Frontiers in Communication ·

Volume 11 - 2026 | https://doi.org/10.3389/fcomm.2026.1893894

Emotional design and advertising: a systematic review of the literature on consumer behavior

  • Luis Miguel Viñan-Carrasco1*corresponding author
  • Wilson Xavier Castro-Ortiz2
  • Pablo Xavier Rosas-Chávez2
  • Raúl Guillermo Zambrano-Pontón2
  • Shawnny Daniela Dillon-Abarca1
  1. 1Facultad de Ciencias de la Educación, Humanas y Tecnologías, Universidad Nacional de Chimborazo Riobamba, Riobamba, Ecuador
  2. 2Facultad de Ciencias Políticas y Administrativas, Universidad Nacional de Chimborazo Riobamba, Riobamba, Ecuador
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Abstract

Emotional design integrates sensory, functional, social, and symbolic elements to elicit affective responses that may influence consumer perception, attitudes, and behavior. This study aimed to analyze the relationship between emotional design, advertising, and consumer behavior based on recent scientific literature. A systematic literature review was conducted following the PRISMA guidelines. Searches were performed in Scopus and Web of Science, and 66 primary studies published during the last ten years were included. The reviewed evidence shows that emotional design strategies incorporate perceptual stimuli, user experiences, and meaning-making processes. Color, shape, texture, packaging, and multisensory stimuli contribute to attraction, attention, and perceived quality, while usability, ergonomics, interactivity, and demonstrations enhance the user experience. Storytelling, cultural identity, sustainability, and personalization contribute to meaning construction and strengthen consumer-brand connections. The literature also identifies positive, negative, and complex emotions, including pleasure, trust, fear, guilt, nostalgia, attachment, and identification, which are associated with purchase intention, satisfaction, loyalty, repurchase, and other consumer responses. The findings indicate that emotional design operates across sensory, experiential, social, and symbolic dimensions, extending its influence beyond immediate purchase decisions toward longer-term consumer-brand relationships. However, the methodological diversity of the reviewed studies highlights the need for more integrated approaches combining subjective, physiological, and digital measures to evaluate emotional and behavioral responses. https://doi.org/10.17605/OSF.IO/QR9YN

Keywords

1 Introduction

Currently, the design of products, brands, and consumer experiences is oriented toward a human-centered perspective, where functionality coexists with the perception, experience, and meaning that users attribute to objects. In this context, product choice is related not only to its physical and technical attributes but also to the affective responses it evokes through its appearance and the experience it provides. Given that a gap still exists between designers' intentions and consumers' emotional perceptions, understanding these affective responses has become a relevant challenge for developing proposals more aligned with user expectations (Lin and Wei, 2017).

Within this framework, emotional design emerges as an approach that seeks to go beyond functionality to promote an affective connection between the user and the product. From this perspective, the theory of emotional processing at three levels visceral, behavioral, and reflective explains how different cognitive dimensions intervene in the user experience and in the generation of meaningful emotional responses (Yao, 2024). In addition, it has been noted that consumers value not only the functionality and reliability of products but also affective attributes such as texture, shape, color, and style, as these influence the impressions and feelings objects generate. Consequently, affective design aims to understand the emotional relationship between consumers and products, as well as to identify the perceptual design elements linked to these affective qualities, although their measurement is more complex than evaluating functionality or usability (Chan et al., 2020). Similarly, both designers and researchers recognize that the emotional dimension plays a decisive role in consumer choices and purchase decisions, although accurately identifying these emotions remains difficult due to their multidimensional nature and the challenges users face in clearly expressing them (Vaidya and Kalita, 2022).

In the field of commercial communication, emotion has also become a central component. Unlike rational approaches focused on price, quality, or objective product features, emotional appeals rely on the affective and experiential dimensions of consumption. Their purpose is not limited to eliciting positive emotions such as love, humor, pride, or joy but also includes negative emotions such as fear, guilt, or shame when aiming to induce corrective, preventive, or avoidance behaviors (Lee and Heere, 2018).

In this sense, emotional advertising is characterized by its ability to capture attention, remain in consumers' memory, and strengthen the bond with the brand, influencing attitudes, engagement, and purchase intention. At the same time, these campaigns contribute to building loyalty, reinforcing values, and associating the brand with dimensions such as self-confidence, status, or beauty, while also encouraging deeper reflections about the product or brand, thus supporting market sustainability and value creation (Pol et al., 2024; Vrtana and Krizanova, 2023). Moreover, emotionally driven marketing highlights the symbolic, personal, and affective dimensions of brands through creative, visual, and textual resources, and attitudes toward advertisements can mediate the formation of favorable brand attitudes, even before a rational evaluation of the product (Bou Saada et al., 2022).

The literature has also shown that purchase decisions are strongly influenced by emotional experiences triggered by sensory and aesthetic stimuli. Factors such as color, scent, music, and other multisensory cues can modify perceived attractiveness, consumer attitudes, and consumption experiences, even in digital environments, intensifying emotional responses and encouraging purchasing behavior (Wu and Chen, 2024). Similarly, in sectors such as fashion and personal accessories, design elements like color, shape, and texture are strategically used to evoke specific emotional responses. It has also been observed that negative emotions can delay or inhibit purchases with a strength comparable to or even greater than the ability of positive emotions to stimulate them (Yang et al., 2025). This reinforces the idea that emotional design constitutes an increasingly relevant differentiation strategy, while also imposing new demands for creativity, innovation, and the ability to translate emotions into impactful products and experiences, leading to the development of methods and tools associated with emotion-centered design (Zhang, 2026).

Regarding the state of the art, previous reviews have provided important contributions to understanding the field. Liu et al. (2024) identified four key research themes communication, triggers, experience, and consumer behavior and concluded that packaging directly influences perceived value, emotional connections with the brand, and responses such as purchase, loyalty, and satisfaction. Vaidya and Kalita (2022), highlighted the growing relevance of emotional design as a differentiation strategy and organized the evidence around emotional terminology, factors influencing consumer emotional responses before purchase, product emotion theories, and evaluation methods. Likewise, López et al. (2021a), focusing on emotional design methodologies such as Kansei engineering, analyzed how different approaches translate desired emotions into concrete design parameters and proposed guidelines for their application across various product types.

To better identify the contribution of the present systematic review, previous review studies related to emotional design and consumer behavior were compared according to their scope, main contributions, and remaining research gaps. Table 1 summarizes the aspects addressed by these studies and highlights the limitations that justify the need for an integrated analysis of emotional design strategies, emotional responses, consumer behavior outcomes, and evaluation methods.

Table 1. Summary of previous systematic reviews related to emotional design and consumer behavior.

Review studyMain focusMain contributionsRemaining gaps identified
Liu et al. (2024)Emotional design of packaging through bibliometric analysisIdentified major research themes related to communication, emotional triggers, user experience, and consumer responses. Highlighted the role of packaging in perceived value, brand connection, purchase intention, loyalty, and satisfaction.Focused mainly on packaging design and bibliometric mapping, without integrating broader emotional design strategies, advertising contexts, emotional categories, and measurement approaches.
Vaidya and Kalita (2022)Emotional design as a differentiation strategy in products and consumer experiencesOrganized evidence around emotional terminology, factors influencing emotional responses before purchase, product emotion theories, and evaluation methods.Did not provide a systematic integration of how emotional design strategies are applied in advertising or how emotions translate into specific consumer behaviors.
López et al. (2021a)Emotional design methodologies, particularly Kansei EngineeringAnalyzed approaches that translate desired emotions into design parameters and proposed guidelines for applying emotional design methods across products.Focused mainly on design methodologies and product development processes, with limited consideration of advertising strategies, brand relationships, and behavioral consequences.

Despite these contributions, the literature remains fragmented regarding the strategies used, the types of emotions activated, their influence on consumer behavior, and the methods used to measure these responses in design, advertising, and consumption contexts. Therefore, conducting a systematic review that integrates these components is relevant to better understand how emotional design operates in the relationship between products, advertising, and consumer behavior. In this sense, the objective of this study is to analyze, based on scientific literature, the main emotional design strategies used and related aspects, addressing the following research questions:

  • RQ1. What are the main emotional design strategies used in advertising?
  • RQ2. What types of emotions are most frequently employed in advertising campaigns?
  • RQ3. How do emotional advertising strategies influence consumer behavior?
  • RQ4. What methods are used to measure emotional responses in advertising contexts?

1.1 Theoretical framework

Norman (2004) popularized the concept of emotional design, understood as the ability of objects to elicit affective responses that influence how people perceive, use, and evaluate them. According to this author, the experience with everyday objects can be understood through three levels of processing: visceral, behavioral, and reflective. The visceral level is associated with the immediate reaction generated by the appearance of an object, particularly through attributes such as color, shape, texture, and style, which produce rapid impressions of liking or disliking. The behavioral level is linked to the experience of use, functionality, and usability, such that a product that is easy to understand, efficient, and satisfying to use tends to generate a favorable emotional evaluation during interaction. The reflective level, in turn, relates to the meaning the object acquires for the user, as it may be associated with memories, identity, status, values, or self-expression. In this way, emotional design shows that the relationship between people and objects is determined not only by utility but also by the product's capacity to generate immediate impact, satisfying experiences, and lasting symbolic meanings.

Complementing Norman's approach, Desmet and Hekkert (2007) proposed that product experience emerges from the interaction between aesthetic perception, emotional responses, and the meanings that individuals attribute to products. From this perspective, products are not evaluated exclusively through their functional characteristics but also through the emotions and experiences they generate during interaction. Similarly, Desmet (2003) argued that product-related emotions arise from the relationship between product characteristics and users’ concerns, expectations, and personal experiences, highlighting that the same design element may generate different emotional responses depending on the individual and contextual factors involved.

Jordan (2000) proposes that design can be guided by different strategies aimed at generating pleasure in users, organized into four dimensions: physio-pleasure, socio-pleasure, psycho-pleasure, and ideo-pleasure. Physio-pleasure strategies focus on sensory and bodily stimulation through elements such as color, shape, texture, or sound, which influence immediate user responses. Psycho-pleasure strategies relate to the user experience, considering aspects such as ease of use, efficiency, understanding, and a sense of control. Socio-pleasure strategies are linked to social interaction, belonging, and connection with others, where the product acts as a mediator of relationships and social recognition. Ideo-pleasure strategies address deeper dimensions related to values, identity, and personal meaning, allowing products to represent users' beliefs, lifestyles, or aspirations. This framework allows emotional design to be understood as a set of strategies operating at different levels of the consumer experience.

From the perspective of user experience, emotional design extends beyond usability by incorporating subjective perceptions, affective responses, and personal meanings developed during interaction. Hassenzahl and Tractinsky (2006) emphasized that user experience involves both pragmatic and hedonic dimensions, where emotional aspects influence how individuals evaluate products and technologies. Therefore, emotional design contributes to creating experiences that are meaningful and engaging, strengthening the relationship between users, products, and brands.

Consumer behavior can be understood as a broad construct that encompasses not only purchase decisions but also various relational and attitudinal responses toward a brand. In this regard, Ghorbanzadeh (2020) shows that when consumers develop a deep emotional connection with a brand, they tend to exhibit behaviors such as purchase intention, willingness to pay a premium price, loyalty, and positive word of mouth. This relationship is further strengthened by variables such as brand identification and trust, which foster a more solid and sustainable affective bond.

From a broader marketing perspective, emotional connections between consumers and brands are influenced by experiential and symbolic aspects of consumption. Holbrook and Hirschman (1982) highlighted that consumption involves not only functional evaluation but also emotions, fantasies, meanings, and experiences associated with products and brands. Thus, advertising and design strategies may influence consumer responses by connecting products with personal values, memories, identities, and aspirations.

In the context of consumer behavior, emotions can be understood through the hierarchical model proposed by Laros and Steenkamp (2005), who suggest that affective responses are organized into two general dimensions: positive affect and negative affect. Positive affect includes emotions such as joy, satisfaction, enthusiasm, and pleasure, associated with favorable experiences that influence consumer evaluation and preference. Negative affect, on the other hand, includes emotions such as fear, guilt, shame, or sadness, which may lead to rejection, avoidance, or alert states in response to certain stimuli. From these broad dimensions, the authors identify a more specific level of emotions that captures more elaborated affective responses, such as pride, nostalgia, or attachment, which reflect more complex emotional experiences linked to identity, memory, and the relationship with products or brands. This approach allows the emotional analysis of consumer behavior to be structured from general categories toward deeper affective manifestations.

Additionally, Bagozzi et al. (1999) highlighted that emotions play a central role in marketing decisions because they influence consumer evaluations, intentions, and behaviors. Emotional responses can mediate the relationship between perceptions and actions, explaining why affective factors are relevant in processes such as preference formation, brand attachment, and purchase decisions. Therefore, understanding emotional design requires integrating both the characteristics of the stimulus and the psychological processes through which consumers interpret and respond to products, advertisements, and brands.

2 Materials and methods

For the development of this study, a systematic literature review was conducted following the PRISMA guidelines (Page et al., 2021), with the aim of organizing the process of identification, screening, eligibility, and inclusion of studies in a transparent manner. This approach enabled the structured search, selection, and synthesis of evidence related to emotional design and its influence on consumer behavior. The complete process of search, screening, and study selection is available in the Supplementary Material and in the OSF registry indicated at the end of the study.

2.1 Eligibility criteria and information sources

The search was conducted in the Scopus and Web of Science databases, due to their coverage of peer-reviewed scientific literature in areas related to design, advertising, marketing, and consumer behavior. Search terms were applied to the title, abstract, and keywords fields in order to retrieve studies directly related to the topic of analysis.

Publications from the last ten years were considered, without language restrictions, to include recent evidence and broaden the scope of results. Records corresponding to books, errata, and retractions were excluded, as well as documents that, after reviewing the title, abstract, or full text, were not directly related to the objective of the review. This delimitation allowed the refinement of the sample, retaining only studies relevant to the analysis.

2.2 Search strategy

The search process was conducted iteratively. Initially, a query was performed in the Scopus database using keywords aligned with the objectives of the study. Subsequently, the retrieved records were subjected to exploratory analysis in RStudio (version 4.4.2), which allowed the identification of thematic trends, relationships among terms, and co-occurrence networks.

Based on this analysis, the search strategy was refined by incorporating more precise and relevant terms for the topic. The filters defined in the eligibility criteria were then applied, limiting document retrieval to those containing the key terms in the predefined fields (see Table 2). The final search strategy was applied uniformly across the selected databases on April 8, 2026, to ensure consistency in the process and comparability of the results obtained.

Table 2. Search strings and results obtained.

DatabaseSearch stringTotal
Scopus[TITLE-ABS-KEY (“emotional design” OR “emotional advertising” OR “affective design”) AND TITLE-ABS-KEY (“consumer behavior” OR “consumer behaviour” OR “consumer response” OR “purchase intention” OR “purchase decision” OR “brand perception” OR “brand attitude” OR “consumer engagement” OR “customer satisfaction”)) AND PUBYEAR > 2015 AND PUBYEAR < 2027 AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE, “cp”) OR LIMIT-TO (DOCTYPE, “ch”) OR LIMIT-TO (DOCTYPE, “re”))80
Web of Science[TS = (“emotional design” OR “emotional advertising” OR “affective design”)] AND TS = (“consumer behavior” OR “consumer behaviour” OR “consumer response” OR “purchase intention” OR “purchase decision” OR “brand perception” OR “brand attitude” OR “consumer engagement” OR “customer satisfaction”)42
Total122

2.3 Study selection process

The study selection process was carried out in accordance with the stages proposed by PRISMA, with the aim of systematically organizing the refinement of the identified records. In the identification phase, a total of 122 records were retrieved from two databases: Scopus (n = 80) and Web of Science (n = 42). Subsequently, 37 duplicate records were removed, resulting in 85 unique studies for the screening phase (see Figure 1).

PRISMA flowchart.
Figure 1. PRISMA flowchart.

During the screening stage, titles, abstracts, and keywords were reviewed to verify the thematic relevance of the studies in relation to the research objectives. In this phase, 3 records were excluded for not being related to the study topic, leaving 82 documents for the next stage. Full texts were then sought; however, 7 studies could not be retrieved, reducing the sample to 75 articles for eligibility assessment.

In the eligibility phase, a detailed review of the full texts was conducted, considering their content, alignment with the research questions, and potential risk of bias. As a result, 9 studies were excluded, mainly due to methodological limitations or lack of relevant contribution to the analysis. Finally, 66 studies were included in the review, forming the basis for the results and discussion of this study.

2.4 Bias risk assessment

The risk of bias assessment was conducted through a three-stage review process, with active participation of the authors to ensure a double review of each study. In the first stage, titles, abstracts, and keywords were screened. Each record was evaluated by one author and subsequently reviewed by a second author. In cases of disagreement, a third author acted as a reviewer to reach consensus.

In the second stage, the selected studies were assessed using the QuADS tool, which evaluates methodological and reporting quality based on 13 criteria, including theoretical underpinning, clarity of objectives, study design, sampling, data collection and analysis, consideration of relevant stakeholders, and discussion of limitations. This assessment was also reviewed by more than one author to reduce individual bias and enhance consistency in the process.

Based on the total scores obtained, studies were classified according to their risk of bias: scores between 1 and 13 points were considered as high risk of bias, reflecting lower methodological quality; scores between 14 and 26 points were classified as moderate risk of bias, indicating an intermediate level of methodological quality; and scores between 27 and 39 points were considered as low risk of bias, representing higher methodological quality.

The assessment showed variability among the evaluated studies. Of the 75 studies assessed, 45 (60.0%) presented high methodological quality and a low risk of bias, 22 (29.3%) showed moderate methodological quality and a moderate risk of bias, and 8 (10.7%) were classified as having low methodological quality and a high risk of bias (see Figure 2). For the subsequent selection process, only studies classified as having high and moderate methodological quality were considered eligible for inclusion in the systematic review, whereas studies with low methodological quality were excluded due to their high risk of bias. The detailed assessment of each study according to the QuADS criteria is available in the Supplementary Material.

QuADS quality level to bias risk assessment.
Figure 2. QuADS quality level to bias risk assessment.

In the third stage, a full-text review of the included studies was conducted. At this stage, studies were excluded if, despite meeting general methodological criteria, they did not directly address the research questions. The complete details of this process are available in the Supplementary Material.

2.5 Synthesis methods

The synthesis was conducted through a thematic analysis approach combining deductive and inductive procedures. The initial coding framework was established based on the theoretical foundations of emotional design and the research questions of the study. Specifically, emotional design strategies were classified according to Jordan's (2000) four dimensions of pleasure: physio-pleasure, psycho-pleasure, socio-pleasure, ideo-pleasure and cross-cutting strategies. Likewise, the emotions identified in the literature were organized according to recurring categories reported in previous studies, including positive emotions, negative emotions, complex or relational emotions, and cross-cutting emotional states.

Based on this initial framework, the information extracted from each included study was organized in a Microsoft Excel matrix containing authors, publication year, country, and main findings. Subsequently, the coded information was analyzed to identify recurring patterns, similarities, and differences among studies. Emerging subthemes were incorporated during the synthesis process when relevant findings did not fit completely within the predefined categories. The final synthesis was structured according to the research questions, addressing emotional design strategies, emotions elicited by advertising, their influence on consumer behavior, and methods used to evaluate emotional responses.

3 Results

3.1 Bibliometric data

The distribution of studies by year shows a progressive evolution in scientific production on emotional design. Between 2016 and 2017, the number of studies was limited (1 and 3 studies, respectively), followed by an increase in 2018 (8 studies), suggesting an initial rise in interest in the topic. Between 2019 and 2020, production remained stable, with 3 studies per year, before increasing again from 2021 (8 studies) and 2022 (9 studies), reaching its highest point in 2024 (10 studies). In the most recent years, 2023, 2025, and 2026, production remained relatively consistent, with 7 studies in each year, indicating consolidation of the field (see Figure 3). Overall, these data reflect a growing academic interest in emotional design, particularly in recent years.

Distribution of studies by year.
Figure 3. Distribution of studies by year.

The geographical distribution shows a notable concentration in Asian countries (see Figure 4), with China as the most represented context (26 studies), followed by Taiwan (6), South Korea (3), India (3), and Indonesia (3). In Europe, Spain stands out (5), while in the Americas, contributions were identified from the United States (3), Brazil (2), and Peru (2). The high presence of studies from China may be related to the rapid growth of its digital and consumer markets, the development of industries linked to e-commerce, innovation in product design, and strong competition among brands. It should be noted that the geographical distribution does not correspond to the total number of included studies (n = 66), as some articles involved authors affiliated with institutions from multiple countries. Therefore, a single study could be represented in more than one country, allowing the analysis to capture international collaboration patterns.

Distribution of studies by country.
Figure 4. Distribution of studies by country.

3.2 Emotional design strategies used in advertising

To organize the emotional design strategies identified in the literature, Jordan's framework (2000) was adopted, which distinguishes four dimensions of pleasure in design: physio-pleasure, socio-pleasure, psycho-pleasure, and ideo-pleasure (see Table 3). This classification made it possible to group the strategies according to whether their predominant emotional effect was related to sensory stimulation, user experience, social interaction, or the symbolic meaning of the product or brand.

Table 3. Strategies used in emotional design.

Jordan's dimensionUnified strategyAssociated elements identified in the literature
Physio-pleasureVisual and aesthetic appealPhysical appearance, visual aesthetics, style, symmetry, visual originality, attractive design, brightness, saturation Das et al., 2025; Dewi et al., 2018, 2021; Lin and Wei, 2017; Xiao et al., 2026; Yu et al., 2022; Zhang et al., 2021).
Sensory and multisensory designColor, shape, texture, illustrations, lettering, graphics, music, scents, integration of sight, hearing, smell, taste, and touch (Bou Saada et al., 2022; Chan et al., 2020; Correia and Simões, 2022; Li and Xue, 2023; Liu, 2026; Tang, 2025; Yao, 2024)
Materiality and finishHigh-quality materials, transparency, color combinations, contrast, hue, purity, visual and tactile finishes (Ghorbanzadeh et al., 2020; Wang et al., 2024; Wang and Cho, 2018).
Psycho-pleasureUsability and clarity of useEase of use, intuitiveness, clarity, ease of learning, visual organization, navigability, easy-to-understand design (Guo et al., 2024; Liu et al., 2021, 2024; Wang and Han, 2022; Wu et al., 2026).
Ergonomics and comfortErgonomic comfort, visual ergonomics, operability, comfortable user experience (Guo et al., 2024; Lin and Wei, 2017; Ong et al., 2025; Yu et al., 2022).
Functionality and performancePracticality, functionality, safety, reliability, quality, efficiency, time reduction (Tang, 2025; Wang and Han, 2022; Yao, 2024; Yen, 2018).
Durability and controlMaintainability, adaptability, flexible design, high durability, repairability, sense of control or mastery (Agost and Vergara, 2020; Aguiar et al., 2023; Seva, 2022).
Purchase and service experienceFair pricing, good customer service, after-sales service, customer training, long-term relationship systems (Ghorbanzadeh et al., 2020; Ong et al., 2025).
Socio-pleasureEmotional closeness and belongingFamily situations, images of people celebrating, sense of community, belonging, group affiliation, social connection (Aguiar et al., 2023; Bou Saada et al., 2022; Lee and Heere, 2018; Masita et al., 2022).
Social validation and reference figuresCelebrities, familiar figures, social cues, support for social and cultural activities (Ghorbanzadeh et al., 2020; Pol et al., 2024; Rocha-Vilca et al., 2024; Vrtana and Krizanova, 2023).
Ideo-pleasureIdentity and self-expressionUniqueness, originality, modernity, luxury, product personality, self-expression, status, self-perception (Wang and Cho, 2018; Seva, 2022; Yu et al., 2022; Das et al., 2025; de las Heras et al., 2025; Tang, 2025).
Cultural and symbolic meaningCultural narratives, packaging identity, local culture, culturally relevant motifs, brand symbols and values (Cheng and Kim, 2026; Liu, 2026; Wu et al., 2026).
Sustainability and ecological valuesSustainable design, eco-friendly attributes, eco-labels, environmental communication, emotionally durable design (Cabrera-Flores et al., 2025; Kang and Nagasawa, 2023; Liu et al., 2024; Seva, 2022; Wu et al., 2026).
Cross-cutting strategiesStorytelling and emotional appealsNarratives, emotional slogans, inspirational messages, positive and negative appeals, humor, resilience (Bou Saada et al., 2022; Fardi, 2021; Lee and Heere, 2018; Lopes and Veiga, 2019; Pol et al., 2024; Rocha-Vilca et al., 2024; Vrtana and Krizanova, 2023; Wu et al., 2026; Wu and Chen, 2024)
Interactivity and immersionProduct demonstrations, interactive packaging, augmented reality, QR codes, transformable structures, gamification (Liu, 2026; Wang et al., 2025; Yin and Liu, 2026; Zhang, 2026)
Personalization and co-creationCustomization, user-driven personalization, emotional generative design, co-design (Agost and Vergara, 2020; Fels et al., 2017; Liu et al., 2024; Ma et al., 2022).
Methods for translating emotions into designKansei Engineering, Kano model, Citarasa Engineering, data mining, semantic analysis, sentiment análisis (Green and Chattaraman, 2019; Guo et al., 2023; Jiang et al., 2018; Jin et al., 2022; Kwong et al., 2016; Lee, 2023; López et al., 2021a, b; Seva, 2022; Wang and Chin, 2017; Xie et al., 2024).

The classification shows that emotional design strategies are distributed across different levels of experience, ranging from immediate sensory stimulation to the construction of meaning and symbolic value. Strategies linked to physio-pleasure are oriented toward generating rapid responses through the senses, where aesthetics, color, shape, and multisensory stimuli act as triggers of attraction and attention. These resources are particularly relevant in contexts where first impressions influence the evaluation of a product or digital environment.

In turn, strategies associated with psycho-pleasure reflect the importance of user experience in shaping emotional responses. Aspects such as usability, functionality, ergonomics, and perceived quality contribute to a satisfactory experience in which the consumer values efficiency, comfort, and control during interaction. This suggests that emotional design depends not only on visual appeal but also on how effectively the product responds to users' practical needs.

Regarding socio-pleasure, the identified strategies indicate that the social dimension influences how consumers relate to products or brands. Elements that evoke closeness, familiarity, or belonging, as well as the use of social reference figures, help strengthen emotional connections and foster a sense of identification with others. This dimension highlights the role of social context in the consumption experience.

In the case of ideo-pleasure, the grouped strategies reveal that design also operates at a deeper level, associated with identity, values, and symbolic meaning. Elements such as sustainability, culture, self-expression, and status allow products to go beyond functionality and become vehicles of personal and social representation. From an integrated perspective, the presence of cross-cutting strategies such as storytelling, interactivity, and personalization indicates that emotional design operates holistically, combining multiple dimensions to influence perception and the consumer–product relationship.

3.3 Emotions elicited in advertising campaigns

The emotions identified in the reviewed literature reveal that emotional design and advertising rely on a broad spectrum of affective responses that extend beyond the generation of immediate positive reactions. These emotions range from pleasure and trust to fear, guilt, nostalgia, attachment, and identification, reflecting the multidimensional nature of consumer emotional experiences. To facilitate their analysis, the identified emotions were organized according to their primary classification, subcategory, and emotional characteristics reported in the literature, while also being interpreted through Norman's three levels of emotional processing (visceral, behavioral, and reflective). Table 4 presents this classification.

Table 4. Emotions used in emotional design.

Main classificationSubcategoryEmotions identified in the literatureInterpretation according to Norman
Positive emotionsHedonic/pleasure-relatedJoy, happiness, pleasure, enjoyment, delight, humor, fun, charm, liveliness (Casales-Garcia et al., 2024; Cheng and Kim, 2026; Correia and Simões, 2022; Guo et al., 2018; Pol et al., 2024; Rocha-Vilca et al., 2024; Vrtana and Krizanova, 2023; Wang et al., 2025; Wang and Han, 2022; Wu and Chen, 2024; Yen, 2018; Zhang et al., 2021)Primarily visceral
Well-being and calmCalmness, relaxation, comfort, ease, security, warmth, pleasantness (Lin and Wei, 2017; Wang and Chin, 2017; Zhang et al., 2021; Correia and Simões, 2022; Wang and Han, 2022; Guo et al., 2024).Primarily behavioral
Personal and social valuationPride, prestige, elegance, sophistication, honor, popularity (Correia and Simões, 2022; Dewi et al., 2018; Lee, 2023; Pol et al., 2024; Rocha-Vilca et al., 2024; Wang et al., 2024).Primarily reflective
Positive bondingAffection, love, friendship, empathy, trust, emotional connection, emotional resonance (Bou Saada et al., 2022; Madadi et al., 2024; Masita et al., 2022; Pol et al., 2024; Seva, 2022; Wang et al., 2025; Xu et al., 2026)Behavioral and reflective
Negative emotionsThreat or alertFear, disgust, pain, sadness, depression (Pol et al., 2024; Seva, 2022; Vrtana and Krizanova, 2023; Yang et al., 2025)Visceral and reflective
Moral or social sanctionGuilt, shame, bitterness (Lee and Heere, 2018; Pol et al., 2024; Seva, 2022; Vrtana and Krizanova, 2023).Primarily reflective
Rejection or discomfortBoredom, displeasure, indifference (Bandyopadhyay et al., 2023; Yang et al., 2025).Visceral and behavioral
Complex or relational emotionsMemory and meaningNostalgia, belonging, patriotism, spiritual feeling, inspiration (Aguiar et al., 2023; Lee and Heere, 2018; Pol et al., 2024; Seva, 2022; Wang and Cho, 2018; Xie et al., 2024; Yao, 2024)Primarily reflective
Attachment and brand relationshipEmotional attachment, brand passion, love, obsession, identification, affective loyalty (Bou Saada et al., 2022; Fels et al., 2017; Ghorbanzadeh et al., 2020; Wu et al., 2026; Yao, 2024).Primarily reflective
Self-realization and identitySelf-expression, group affiliation, sense of control or mastery, lifestyle adaptation (Agost and Vergara, 2020; Aguiar et al., 2023).Behavioral and reflective
Cross-cutting statesEmotional activationExcitement, enthusiasm, vitality, emotional activation, pleasant arousal (Cheng and Kim, 2026; Chung and Lee, 2019; Lee and Heere, 2018; Wang and Cho, 2018; Wang et al., 2025; Wu and Chen, 2024).Primarily visceral

The classification shows that positive emotions occupy a prominent place in the literature, particularly those associated with pleasure, well-being, trust, and favorable evaluation of the product or brand. These emotions operate at different levels: some generate immediate responses to visual or sensory stimuli, others relate to comfort and satisfaction during the user experience, and others are linked to recognition, prestige, or social connection.

Negative emotions also appear as part of the identified emotional strategies. In some cases, they are associated with alertness, rejection, or discomfort; in others, they involve more reflective responses such as guilt, shame, or social sanction. This suggests that their function is not always unfavorable, as they can be used in specific advertising contexts to attract attention, raise awareness, or motivate particular behaviors.

Complex or relational emotions reflect a deeper dimension of the consumer's emotional experience. Emotions such as nostalgia, belonging, attachment, identification, or brand passion are related to memory, identity, and relationship building. These responses are generally situated at a more reflective level, as they involve personal or symbolic interpretations of the product, brand, or advertising message.

Cross-cutting states, such as emotional activation and valence, help to understand the intensity and direction of affective responses. Activation is expressed through emotions such as enthusiasm, vitality, or excitement, while valence distinguishes whether the experience is oriented toward positive, negative, or neutral outcomes. This perspective complements the classification, as the same strategy may generate different responses depending on the stimulus, context, and consumer experience.

3.4 Influence of emotional advertising strategies on consumer behavior

According to the reviewed literature, emotional design consistently and significantly influences consumer behavior, particularly in variables such as purchase intention, repurchase, product preference, satisfaction, loyalty, brand attachment, and positive word of mouth (Bhutto et al., 2021; Bou Saada et al., 2022; Ghorbanzadeh et al., 2020; Lee and Heere, 2018; Liu, 2026; Masita et al., 2022; Pol et al., 2024; Wu and Chen, 2024; Xu et al., 2026; Yu et al., 2022; Zhang, 2026) (see Figure 5). Overall, studies agree that emotional stimuli incorporated into design, advertising, packaging, interfaces, or user experience tend to strengthen consumer responses, leading to more favorable product evaluations and a greater willingness to purchase (Casales-Garcia et al., 2024; Rocha-Vilca et al., 2024; Vaidya and Kalita, 2021; Wang and Cho, 2018; Xiao et al., 2026; Yin and Liu, 2026). More specifically, visual attractiveness, perceived ease of use, interactive functionality, packaging design, personalization, and multisensory elements are associated with higher levels of interest, memorability, visual attention, perceived quality, and purchase intention (Dewi et al., 2018; Li and Xue, 2023; Xiao et al., 2026; Xu et al., 2026; Yao, 2024).

Influence of emotional design on consumer behavior.
Figure 5. Influence of emotional design on consumer behavior.

Likewise, the literature highlights that positive emotions play a central role in this process. Feelings such as happiness, pleasure, hope, satisfaction, and enjoyment strengthen attitudes toward the brand, improve perceived quality, and reduce indecision, thereby accelerating the transition from stimulus perception to purchase intention (Guo et al., 2018; Kwong et al., 2016; Masita et al., 2022; Wang and Han, 2022; Wu and Chen, 2024). Several studies show that emotional advertising and emotional marketing not only increase purchase intention but also enhance consumer engagement, involvement with the advertisement, brand preference, and continued product use (Liu, 2026; Pol et al., 2024; Seva, 2022; Xiao et al., 2026; Yen, 2018). In the same vein, emotional value, affective resonance, and emotional connection with the brand are reported to reinforce loyalty, attachment, and consumers' willingness to recommend the brand or even pay a premium price (Bou Saada et al., 2022; Ghorbanzadeh et al., 2020; Vrtana and Krizanova, 2023).

Another recurring finding is that emotional design influences not only immediate transactional decisions but also broader relational behaviors. The literature indicates that a positive emotional experience strengthens trust in the brand, improves its image, and consolidates long-term bonds between consumers and products (Das et al., 2025; Ong et al., 2025; Vrtana and Krizanova, 2023; Yin and Liu, 2026). This effect is reflected in outcomes such as increased loyalty, repeat purchases, positive word of mouth, and a willingness to maintain a sustained relationship with the brand. Furthermore, in specific contexts such as sustainable, cultural, or experiential products, emotional design also promotes symbolic identification with the product, enhancing perceptions of authenticity, belonging, status, environmental awareness, or cultural value, thereby further extending its influence on consumer behavior (Cabrera-Flores et al., 2025; Ghorbanzadeh et al., 2020; Kang and Nagasawa, 2023; Wang and Cho, 2018; Yao, 2024; Zhang et al., 2021).

However, the literature also warns that the impact of emotional design is not always positive. Some studies indicate that negative emotions elicited by certain design elements may lead to avoidance, rejection, or a lasting unfavorable impression of the brand or product (Vaidya and Kalita, 2021; Yang et al., 2025). Similarly, emotional advertising may induce impulsive or less rational purchasing, particularly when it intensifies affective attachment or the symbolic appeal of the product (Vrtana and Krizanova, 2023). Overall, the reviewed findings suggest that emotional design acts as a determining factor in consumer behavior, as it shapes how individuals perceive, evaluate, feel, and ultimately decide in relation to products, brands, and consumption experiences.

3.5 Methods for evaluating emotional responses and consumer behavior

According to the reviewed literature, the measurement of emotions and consumer behavior has been addressed through a wide range of methods. The most commonly used are self-report techniques, particularly structured questionnaires and surveys, often administered online and accompanied by Likert scales or semantic differential scales (Bhutto et al., 2021; Dewi et al., 2018; Fardi, 2021; Guo et al., 2023; Lee and Heere, 2018; Lopes and Veiga, 2019; Ong et al., 2025; Pol et al., 2024; Wang et al., 2025; Yen, 2018; Zhang, 2026). These instruments allow the capture of perceptions, attitudes, satisfaction levels, purchase intention, and self-reported emotional responses, which explains their widespread use in marketing and emotional design research.

At the same time, the literature highlights the use of psychophysiological methods aimed at measuring emotional responses more objectively. Among the most frequently used are electroencephalography (EEG), galvanic skin response (GSR), electromyography (EMG), eye-tracking, and facial recognition (Guo et al., 2018; Vaidya and Kalita, 2022; Wu and Chen, 2024; Xiao et al., 2026; Xie et al., 2024; Xu et al., 2026; Yang et al., 2025). These techniques enable the recording of automatic consumer reactions, such as attention levels, emotional arousal, and brain activity in response to visual or advertising stimuli. Indicators such as fixation duration, eye movements, and changes in skin conductance provide insights into the intensity and nature of emotional responses.

Mixed methodological approaches are also identified, integrating qualitative and quantitative techniques such as semi-structured interviews, focus groups, participant observation, and ideation sessions (Jin et al., 2022; Liu et al., 2021; Rocha-Vilca et al., 2024; Tang, 2025). These strategies allow a deeper understanding of the consumer's subjective experience, exploring the emotional meaning of products and their relationship with brands. Tools such as the Kano model, customer satisfaction scales (CSAT), and Kansei Engineering facilitate the linkage between user emotions and design attributes (Jin et al., 2022; Kang and Nagasawa, 2023; Li and Xue, 2023; Liu et al., 2021; López et al., 2021a; Wang et al., 2018), helping translate affective perceptions into concrete product features.

Recent literature shows an increasing use of data-driven and machine learning-based techniques to evaluate emotional and behavioral responses. These include text mining, sentiment analysis of product reviews, the use of affective lexicons, and artificial intelligence models such as neural networks (Chan et al., 2020; Chang and Lee, 2018; Jin et al., 2022; Kwong et al., 2016; Wang et al., 2018, 2024; Wang and Chin, 2017). These tools allow the processing of large volumes of data from digital environments, enabling the identification of emotional patterns, satisfaction levels, and behavioral trends in real-world consumption contexts.

4 Discussion

The results of the review show that emotional design emerges as a relevant factor in influencing consumer behavior, particularly in purchase intention and product perception. In this regard, the findings are consistent with those reported by Yao (2024), who indicates that the incorporation of emotional elements in design increases purchase intention and improves the aesthetic and creative evaluation of products. This aligns with the results obtained, where sensory and aesthetic strategies appear as some of the most frequently used resources, suggesting that the visual and emotional dimension not only captures attention but also influences the final purchase decision.

Additionally, the results indicate that strategies based on positive emotions, such as affection, closeness, and well-being, are commonly used in advertising. This finding is consistent with Masita et al. (2022), who highlight that positive emotional content enhances brand attitude, memorability, and perceived quality. However, the literature also shows the strategic use of negative emotions, introducing a more complex dimension to the analysis. In particular, the use of fear, guilt, or shame identified in some studies confirms that these emotions can function as persuasive mechanisms in specific contexts, especially in health-related or personal care products (Fardi, 2021; Lee and Heere, 2018). This suggests that the effectiveness of emotional design does not rely solely on generating positive feelings, but also on activating responses aligned with the objective of the message.

Regarding the identified strategies, the results reveal a strong presence of sensory, functional, and symbolic elements. In this sense, packaging, color, and shape play a key role in generating expectations and emotional responses, which is consistent with Casales-García et al. (2024), who state that these attributes directly influence perceived quality and purchase intention. At the same time, the use of color as an emotional element reinforces its role as a generator of symbolic associations, as described by Correia and Simões (2022), showing that consumer responses may vary depending on the intensity and cultural context of the stimulus.

Another relevant aspect identified in the results is the impact of experiential strategies, such as product demonstrations, interactivity, and immersion. These strategies not only convey information but also generate higher levels of emotional activation and consumer engagement, which is consistent with Wang et al. (2025), who show that immersive experiences increase purchase intention by strengthening the emotional connection with the product. This finding reinforces the idea that emotional design extends beyond visual aspects and encompasses the entire interaction experience.

Furthermore, the results show that complex emotions, such as attachment, identification, and loyalty, play a significant role in long-term consumer–brand relationships. This is consistent with Yin and Liu (2026), who indicate that trust and brand image, built through positive experiences, are key determinants of consumer loyalty. In parallel, strategies related to values, sustainability, and identity reflect a shift in consumer preferences, particularly among younger audiences, which aligns with Cabrera-Flores et al. (2025), who report a growing orientation toward responsible and ecological consumption.

Regarding evaluation methods, the results reveal a diversity of approaches, ranging from traditional techniques to neuroscientific methods. The use of tools such as EEG, GSR, and eye-tracking, as described by Xu et al. (2026), indicates progress toward more objective measurements of emotional responses. This suggests a trend toward integrating multidimensional methods to better understand the relationship between emotion, design, and consumer behavior.

4.1 Limitations of the study

One limitation of this study is the high methodological, thematic, and contextual diversity of the reviewed evidence, as the analyzed studies address emotional design in products, advertising, packaging, fashion, digital environments, and consumption experiences. This heterogeneity makes it difficult to establish direct comparisons between findings. In addition, there is a significant geographical concentration in China and other Asian countries, so the results should be interpreted considering possible cultural differences in how consumers perceive and express emotions. Another limitation is related to the variety of methods used to measure emotional responses, as some studies rely on self-reports while others use physiological or computational techniques, which may lead to differences in interpretation.

4.2 Future research

Future studies could further explore comparative analyses across regions and cultures to better understand how consumer emotional responses vary under similar design or advertising strategies. It would also be relevant to develop empirical studies that integrate mixed methods, combining questionnaires, interviews, eye-tracking, EEG, GSR, and sentiment analysis to capture emotional and behavioral responses more comprehensively. Additionally, further research is recommended on the role of negative and complex emotions, such as fear, guilt, nostalgia, or attachment, as they may significantly influence purchase intention, loyalty, and the symbolic relationship with brands.

An additional avenue for future research involves examining the influence of emotional design throughout the complete consumer decision journey, including pre-purchase processes such as information search and product evaluation, as well as post-purchase behaviors such as brand switching, complaint behavior, product disposal, and consumer advocacy. These perspectives would contribute to a more comprehensive understanding of how emotional responses shape consumer relationships beyond purchase intention and brand loyalty.

5 Conclusions

The review identified that emotional design strategies are structured around sensory stimuli, user experiences, social connections, and symbolic meanings. Among the most relevant findings are the use of color, shape, texture, usability, interactivity, storytelling, personalization, and sustainability. This shows that emotional design goes beyond visual appeal, integrating perception, functionality, experience, and values.

Regarding the emotions employed, the literature indicates a combination of positive, negative, and complex emotions. Positive emotions, such as pleasure, joy, satisfaction, and trust, enhance product attractiveness and evaluation, while negative emotions, such as fear, guilt, or shame, can function as persuasive tools in specific contexts. Additionally, emotions such as nostalgia, attachment, belonging, and identification reflect deeper connections between the consumer, the product, and the brand.

These emotional elements directly influence consumer behavior, particularly purchase intention, repurchase, satisfaction, loyalty, positive word of mouth, willingness to pay more, and brand perception. The literature suggests that emotions shape how consumers evaluate, remember, and relate to products, positioning emotional design as a strategic tool to strengthen both immediate decisions and long-term relationships.

Regarding the evaluation of these responses, studies employ a wide range of methods, from questionnaires, surveys, and Likert scales to psychophysiological techniques such as EEG, GSR, eye-tracking, and facial recognition. Computational approaches, including text mining, sentiment analysis, and artificial intelligence, are also identified. This methodological diversity reflects a growing field, although there is still a need for greater integration between subjective, physiological, and digital measurements.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcomm.2026.1893894/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Joseph Lobo, Bulacan State University, Philippines

Reviewed by: Florin Nechita, Transilvania University of Brașov, Romania

Gaurav Vaidya, Indian Institute of Technology Jodhpur, India

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Data availability

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author contributions

LV-C: Conceptualization, Formal analysis, Funding acquisition, Investigation, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing. WC-O: Conceptualization, Data curation, Funding acquisition, Investigation, Project administration, Validation, Writing – original draft, Writing – review & editing. PR-C: Funding acquisition, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. RZ-P: Funding acquisition, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing. SD-A: Funding acquisition, Investigation, Software, Validation, Writing – original draft, Writing – review & editing.

References

  1. Agost M.-J., Vergara M. (2020). Principles of affective design in consumers’ response to sustainability design strategies. Sustainability 12, 1 – 21. doi:10.3390/su122410573
  2. Aguiar M. F., Costa J. M. H., Pigosso D. C. A. (2023). “ How are emotional attachment strategies currently employed in product-service system cases? A systematic review underscoring drivers and hindrances,” in Proc. Des. Soc., ed. Otto K. (Cambridge: Cambridge University Press), 3, 2095 – 2104. doi:10.1017/pds.2023.210
  3. Bagozzi R. P., Gopinath M., Nyer P. U. (1999). The role of emotions in marketing. J. Acad. Mark. Sci. 27, 184 – 206. doi:10.1177/0092070399272005
  4. Bandyopadhyay A., Septianto F., Nallaperuma K., Lang B. (2023). Emotional cues’ effects on grotesque advertising. Australas. Mark. J 31, 124 – 134. doi:10.1177/18393349211056373
  5. Bhutto N. A., Gilal F. G., Gilal R. G. (2021). Towards a new model for purchase intention of smartphones: theoretical extension and analysis. Int. J. Technol. Policy Manag. 21, 302 – 316. doi:10.1504/IJTPM.2021.119700
  6. Bou Saada R., Bou-Hamad I., Harajli D. (2022). Influence of emotional marketing on consumer behavior towards food and beverage brands during the COVID-19 pandemic: a study from Lebanon. J. Mark. Commun. 29, 822 – 839. doi:10.1080/13527266.2022.2088600
  7. Cabrera-Flores A. J., Minchola-Angulo M. C., Pacora-Gonzales S. E., Pozo-Cardenas N. B., Reategui-Vega O. A. M., Valderrama-Puscan M. W. (2025). “ Green marketing and consumer behavior to promote eco-friendly products,” in Proc. LACCEI int. Multi-Conf. Eng. Educ. Technol., eds. Larrondo Petrie M.M., Texier J., Rivas Matta R.A. (Cartagena: Latin American and Caribbean Consortium of Engineering Institutions, 1 – 10. doi:10.18687/LEIRD2025.1.1.281
  8. Casales-Garcia V., De Las Heras A., Luque A., Gonzalez-Abril L. (2024). Sustainable emotional design based on industry 4.0 for industrial nougat packaging. Sustainability 16, 1378. doi:10.3390/su16041378
  9. Chan K. Y., Kwong C. K., Wongthongtham P., Jiang H., Fung C. K. Y., Abu-Salih B. (2020). Affective design using machine learning: a survey and its prospect of conjoining big data. Int J Computer Integr Manuf. 33, 645 – 669. doi:10.1080/0951192X.2018.1526412
  10. Chang D., Lee C. (2018). A product affective properties identification approach based on web mining in a crowdsourcing environment. J. Eng. Des. 29, 449 – 483. doi:10.1080/09544828.2018.1463514
  11. Cheng W., Kim S. I. (2026). Brand perception and purchase intention of tea packaging design among generation Z in China: an empirical SEM analysis. Arch. Des. Res. 39, 225 – 242. doi:10.15187/adr.2026.02.39.1.225
  12. Chung S., Lee S. Y. (2019). Visual CSR messages and the effects of emotional valence and arousal on perceived CSR motives, attitude, and behavioral intentions. Commun. Res 46, 926 – 947. doi:10.1177/0093650216689161
  13. Correia J. S., Simões D. (2022). Are colors emotional triggers in digital branding? Smart Innov. Syst. Technol. 279, 617 – 630. doi:10.1007/978-981-16-9268-0_52
  14. Das M., Moons I., Du Bois E., Van Rooy D. (2025). “ Exploring the sensory impact in second-hand clothing shopping through visceral, behavioural, and reflective design,” in Proc. Des. Soc., ed. di Milano P. (Cambridge: Cambridge University Press), 5, 1763 – 1772. doi:10.1017/pds.2025.10190
  15. De Las Heras A., Zamora-Polo F., Ferramosca A., Luque A. (2025). Emotional design engineering for packaging of olive oil using machine learning techniques. Cogent Eng. 12, 2555340. doi:10.1080/23311916.2025.2555340
  16. Desmet P. (2003). A multilayered model of product emotions. Des. J. 6, 4 – 13. doi:10.2752/146069203789355480
  17. Desmet P., Hekkert P. (2007). Framework of product experience. Int. J. Des. 1, 57 – 66. Available online at: (Accessed April 20, 2026).
  18. Dewi D. S., Sudiarno A., Saputra H., Dewi R. S. (2018). “ The effect of emotional design and online customer review on customer repeat purchase intention in online stores,” in IOP Conf. Ser. Mater. Sci. Eng., eds. Kurniati N., Dewi R. S., Karningsih P. D., Arvitrida N. I., Hartanto D., Dewi D. S. (Surabaya: Institute of Physics Publishing), 012052. doi:10.1088/1757-899X/337/1/012052
  19. Dewi D. S., Sudiarno A., Dewi R. S., Aritonang J. (2021). Understanding the effects of satisfaction and trust on e-repeat purchase intention: an ergonomic approach., in Proc. Int. Conf. Ind. Eng. Oper. Manage., (São Paulo: IEOM Society), 1968 – 1974. Available online at: (Accessed April 16, 2026).
  20. Fardi M. (2021). Investigate the role of advertising appealing in brand attitude and customer behavior. Humanid. Inov. 8, 293 – 305. Available online at: (Accessed April 21, 2026)
  21. Fels A., Falk B., Schmitt R. (2017). “ User-driven customization and customer loyalty: a survey,” in Procedia CIRP, eds. Tiwari A., Shehab E., Roy R., Tomiyama T., Lockett H., Salonitis K. (Amsterdam: Elsevier B.V.), 60, 410 – 415. doi:10.1016/j.procir.2017.02.013
  22. Ghorbanzadeh D., Saeednia H., Rahehagh A. (2020). Antecedents and consequences of brand passion among young smartphone consumers: evidence of Iran. Cogent Bus. Manag. 7, 1712766. doi:10.1080/23311975.2020.1712766
  23. Green A., Chattaraman V. (2019). “ Creating an affective design typology for basketball shoes using kansei engineering methods,” in Adv. Intell. Sys. Comput., ed. Fukuda S. (Cham: Springer Verlag), 774, 355 – 361. doi:10.1007/978-3-319-94944-4_38
  24. Guo F., Tian X., Hu M., Zhang Z. (2024). Affective design of smart TV navigation interface considering the diversity of user needs. Int. J. Hum.–Comput. Interact. 40, 3092 – 3111. doi:10.1080/10447318.2023.2179217
  25. Guo F., Wang X.-S., Liu W.-L., Ding Y. (2018). Affective preference measurement of product appearance based on event-related potentials. Cogn. Technol. Work 20, 299 – 308. doi:10.1007/s10111-018-0463-5
  26. Guo J., Zhang W., Li H., Xia T. (2023). Analysis of the visual sentiment of composition elements in yoga pant patterns. J. Silk 60, 107 – 115. doi:10.3969/j.issn.1001-7003.2023.07.014
  27. Hassenzahl M., Tractinsky N. (2006). User experience—a research agenda. Behav. Inf. Technol. 25, 91 – 97. doi:10.1080/01449290500330331
  28. Holbrook M. B., Hirschman E. C. (1982). The experiential aspects of consumption: consumer fantasies, feelings, and fun. J. Consum. Res. 9, 132 – 140. doi:10.1086/208906
  29. Jiang H., Kwong C. K., Park W. Y., Yu K. M. (2018). A multi-objective PSO approach of mining association rules for affective design based on online customer reviews. J. Eng. Des. 29, 381 – 403. doi:10.1080/09544828.2018.1475629
  30. Jin J., Jia D., Chen K. (2022). Mining online reviews with a kansei-integrated kano model for innovative product design. Int. J. Prod. Res. 60, 6708 – 6727. doi:10.1080/00207543.2021.1949641
  31. Jordan P. W. (2000). Designing Pleasurable Products: An Introduction to the New Human Factors. London: CRC Press. doi:10.4324/9780203305683
  32. Kang X., Nagasawa S. (2023). Integrating continuous fuzzy kano model and fuzzy quality function deployment to the sustainable design of hybrid electric vehicle. J. Adv. Mech. Des. Syst. Manuf. 17, JAMDSM0019. doi:10.1299/jamdsm.2023jamdsm0019
  33. Kwong C. K., Jiang H., Luo X. G. (2016). AI-based methodology of integrating affective design, engineering, and marketing for defining design specifications of new products. Eng. Appl. Artif. Intell. 47, 49 – 60. doi:10.1016/j.engappai.2015.04.001
  34. Laros F. J. M., Steenkamp J.-B. E. M. (2005). Emotions in consumer behavior: a hierarchical approach. J. Bus. Res. 58, 1437 – 1445. doi:10.1016/j.jbusres.2003.09.013
  35. Lee A.-S. (2023). Investigation of relationship between kansei design elements of Taiwanese wooden furniture and consumer demand by fuzzy theory †. Eng. Proc. 38, 64. doi:10.3390/engproc2023038064
  36. Lee S., Heere B. (2018). Exploring the relative effectiveness of emotional, rational, and combination advertising appeals on sport consumer behavior. Sport Mark. Q. 27, 82 – 92. doi:10.32731/smq.272.062018.02
  37. Li Y., Xue L. (2023). “ Children’s toy design process based on the kano-AHP-FBS model: case of multisensory educational toys,” in Proc. - Int. Conf. Cult.-Oriented Sci. Technol., CoST, (Hoboken, NJ: Institute of Electrical and Electronics Engineers Inc.), 311 – 316. doi:10.1109/CoST60524.2023.00070
  38. Lin Y.-C., Wei C.-C. (2017). A hybrid consumer-oriented model for product affective design: an aspect of visual ergonomics. Hum Fact Ergon Manuf. 27, 17 – 29. doi:10.1002/hfm.20403
  39. Liu C., Samsudin M. R., Zou Y. (2024). Emotional design of packaging: a bibliometric analysis. Stud. Media Commun. 12, 172 – 188. doi:10.11114/smc.v12i2.6698
  40. Liu L., Zhang A., Zhang L., Xu J. (2021). “ Research on emotional design of intelligent sleep products for the elderly based on kano model and customer satisfaction and dissatisfaction coefficients,” in Proc. - Int. Conf. Intell. Des., ICID, (Piscataway, NJ: Institute of Electrical and Electronics Engineers Inc.), 528 – 531. doi:10.1109/ICID54526.2021.00110
  41. Liu Y. (2026). Innovative application of emotional design in interactive advertising empowered by AR technology. Aust. J. Electr. Electron. Eng. 1 – 15. doi:10.1080/1448837X.2026.2615549
  42. Lopes E. L., Veiga R. T. (2019). Increasing purchasing intention of eco-efficient products: the role of the advertising communication strategy and the branding strategy. J. Brand Manag. 26, 550 – 566. doi:10.1057/s41262-019-00150-0
  43. López Ó, Murillo C., González A. (2021a). “ State of the art analysis of emotional design methodologies and their demonstrated results,” in Lect. Notes Networks Syst., eds. Shin C. S., Di Bucchianico G., Fukuda S., Ghim Y., Montagna G., Carvalho C. (Berlin: Springer Science and Business Media Deutschland GmbH), 260, 943 – 951. doi:10.1007/978-3-030-80829-7_115
  44. López Ó, Murillo C., Gónzalez A. (2021b). Systematic literature reviews in Kansei engineering for product design—a comparative study from 1995 to 2020†. Sensors 21, 6532. doi:10.3390/s21196532
  45. Ma N., Kim J., Lee J. H. (2022). Exploring personalized fashion design process using an emotional data visualization method. Fash. Text. 9, 44. doi:10.1186/s40691-022-00321-9
  46. Madadi R., Torres I. M., Zúñiga MÁ (2024). The semiotics of emojis in advertising: an integrated quantitative and qualitative examination of emotional versus functional ad dynamics. Psychol. Mark. 41, 1223 – 1241. doi:10.1002/mar.21972
  47. Masita T. E., Adi P. H., Adawiyah W. R., Wihuda F. (2022). The role of consumer hope, positive emotional advertising, and multi-context numbers in developing purchase intention and word of mouth of eco-efficient product. Ekon. Pregl. 73, 390 – 414. doi:10.32910/ep.73.3.3
  48. Norman D. A. (2004). Emotional Design. Perché Amiamo (o Odiamo) gli Oggetti della Vita Quotidiana. Milan: Apogeo Editore. Available online at: (Accessed April 22, 2026).
  49. Ong A. K. S., Diaz J. F. T., Abella J. K. A. L., Alayra R. J. N., Calimag B. C. R., Callo B. C. B. (2025). Translating sustainable purchase intention to actual action through the incorporation of affecting design factors among products. Cogent Bus. Manag. 12, 2583272. doi:10.1080/23311975.2025.2583272
  50. Page M. J., Moher D., Bossuyt P. M., Boutron I., Hoffmann T. C., Mulrow C. D. (2021). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. Br. Med. J. 372, n160. doi:10.1136/bmj.n160
  51. Pol N., Kazim S., Swaroop K. R., Bhakat R. S., Gade S., Jaheer Mukthar K. P. (2024). Emotional appeal in television advertising and its impact on buying behaviour. Stud. Syst. Decis. Control 489, 425 – 440. doi:10.1007/978-3-031-36895-0_34
  52. Rocha-Vilca L., Sánchez-Flores M., Gallardo-Echenique E. (2024). “ Emotions in advertising and their connection to consumers,” in Smart Innov. Syst. Technol., eds. Reis J. L., Santos J. P. M. D., Zelený J., Gavurová B. (Cham: Springer Science and Business Media Deutschland GmbH), 386, 315 – 325. doi:10.1007/978-981-97-1552-7_21
  53. Seva R. R. (2022). Hidden power of affective products and environments. Work 73, S5 – S14. doi:10.3233/WOR-211187
  54. Tang D. (2025). “ The combination of miao culture and womenswear: exploring the consumer’s want based on the emotional design,” in ISMSIT - Int. Symp. Multidiscip. Stud. Innov. Technol., Proc., (Istanbul: Institute of Electrical and Electronics Engineers Inc.), 1 – 5. doi:10.1109/ISMSIT67332.2025.11268069
  55. Vaidya G., Kalita P. C. (2021). Understanding emotions and their role in the design of products: an integrative review. Arch. Des. Res. 34, 5 – 21. doi:10.15187/adr.2021.08.34.3.5
  56. Vaidya G., Kalita P. C. (2022). Emotion assessment methods in the field of product design: a review. Des. Princ. Pract. 16, 1 – 19. doi:10.18848/2325-128X/CGP/v16i02/1-19
  57. Vrtana D., Krizanova A. (2023). The power of emotional advertising appeals: examining their influence on consumer purchasing behavior and brand–customer relationship. Sustainability 15, 13337. doi:10.3390/su151813337
  58. Wang C.-H., Chin H.-T. (2017). Integrating affective features with engineering features to seek the optimal product varieties with respect to the niche segments. Adv. Eng. Inf. 33, 350 – 359. doi:10.1016/j.aei.2016.10.002
  59. Wang F., Cho J. H. (2018). Color Emotional Expression in Cultural and Creative Product Design. Amsterdam: Atlantis Press. 88 – 91. doi:10.2991/iserss-18.2018.24
  60. Wang N., Shi D., Li Z., Chen P., Ren X. (2024). Investigating emotional design of the intelligent cockpit based on visual sequence data and improved LSTM. Adv. Eng. Inf. 61, 102557. doi:10.1016/j.aei.2024.102557
  61. Wang S.-M., Han C. (2022). “ An analysis of gender differences in the innovative function design of supermarket self-service checkout kiosk,” in HCI in Business, Government and Organizations, eds. Fui-Hoon Nah F., Siau K. (Cham: Springer International Publishing), 13327, 337 – 349. doi:10.1007/978-3-031-05544-7_26
  62. Wang W. M., Li Z., Tian Z. G., Wang J. W., Cheng M. N. (2018). Extracting and summarizing affective features and responses from online product descriptions and reviews: a Kansei text mining approach. Eng Appl Artif Intell. 73, 149 – 162. doi:10.1016/j.engappai.2018.05.005
  63. Wang Y., Guo R., Song M. (2025). Direct selling or on-the-spot “cooking”? the impact of sales interaction on consumers’ purchase intentions for food souvenirs. Curr. Issues Tour. 1 – 20. doi:10.1080/13683500.2025.2495102
  64. Wu Y.-L., Chen P.-C. (2024). Neurophysiology of sensory imagery: an effort to improve online advertising effectiveness through science laboratory experimentation. Inf Manag. 61, 103708. doi:10.1016/j.im.2022.103708
  65. Wu Y., Hou W., Zou Y., Dong X., Liu X., Sun X. (2026). “ Research on emotion-driven brand design strategies based on semantic analysis and quality function deployment,” in Proc SPIE Int Soc Opt Eng, eds. Jain L. C., Jain L. C., Wu Q., Shi F., Balas V. E. (Bellingham, Washington: SPIE), 140185P. doi:10.1117/12.3088801
  66. Xiao Y., Fang J., Zhang H., Li Q., Zhang Y. (2026). Construction and analysis of a packaging design preference model using eye-tracking degree of preference. Sci. Rep. 16, 6080. doi:10.1038/s41598-026-36905-4
  67. Xie N., Wang J., Fan J., Chen D. (2024). “ A product design strategy that comprehensively considers consumer behavior and psychological emotional needs,” in Lect. Notes Comput. Sci., eds. Marcus A., Rosenzweig E., Soares M.M. (Cham: Springer Science and Business Media Deutschland GmbH), 14714, 314 – 329. doi:10.1007/978-3-031-61356-2_21
  68. Xu Z., Liu S., Zhang S., Yang Y. (2026). Decoding consumer responses to anthropomorphic products using electroencephalography, skin conductance, and eye-tracking. J. Retail. Consum. Serv. 89, 104618. doi:10.1016/j.jretconser.2025.104618
  69. Yang C.-Y., Wang C.-Y., Pao C.-L. (2025). The impact of negative emotions on product purchase decisions: a study of watch design. BMC. Psychol. 13, 447. doi:10.1186/s40359-025-02775-0
  70. Yao Y. (2024). Emotional design and consumer purchase intention of digital cultural creative products under the background of artificial intelligence. Int. J. Instr. Cases 8, 346 – 366. Available online at:
  71. Yen H.-Y. (2018). “ Constructing and analyzing a measurement model of product emotional design,” in Lect. Notes Comput. Sci., ed. Rau P. P. (Cham: Springer Verlag), 10911, 449 – 459. doi:10.1007/978-3-319-92141-9_35
  72. Yin S., Liu J. (2026). “ A study on how interactive packaging design influences brand attitude through consumer experience,” in Proc. Int. Conf. Comput. Technol., Digit. Media Commun., ICCDC, (New York, NY: Association for Computing Machinery, Inc.), 367 – 373. doi:10.1145/3783669.3783725
  73. Yu L., Feng X., Wang J., Kong W., Chen W. (2022). Research on the mechanism of emotional design in Chinese cultural and creative products. Herit. Sci. 10, 119. doi:10.1186/s40494-022-00751-0
  74. Zhang X. (2026). Smart home product creation under emotional design principles and consumer perceptions. Int. J. Hum.-Comput. Interact. 42, 1084 – 1094. doi:10.1080/10447318.2025.2518351
  75. Zhang Y., Zhang Y., Gao J. (2021). “ The influence of the aesthetic design of Taobao APP on users’ emotional experience,” in Lect. Notes Comput. Sci., ed. Duffy V. G. (Cham: Springer Science and Business Media Deutschland GmbH), 12778, 403 – 414. doi:10.1007/978-3-030-77820-0_30

Citation

Viñan-Carrasco, L. M., et al. (2026). Emotional design and advertising: a systematic review of the literature on consumer behavior. Frontiers in Communication, Volume 11. https://doi.org/
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11 - 2026

Copyright

© 2026 Viñan-Carrasco, Castro-Ortiz, Rosas-Chávez, Zambrano-Pontón and Dillon-Abarca.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Luis Miguel Viñan-Carrasco

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