The impact of negative emotions on product purchase decisions: a study of watch design

Abstract

This study examines how emotional valence (positive and negative) impacts consumer purchasing decisions through wristwatch design, using visual geometric elements. By employing ERPs (Event-Related Potentials) neurophysiological measurements, the study objectively evaluates consumer emotional responses to design elements. Results show that negative emotional elements, such as sharp shapes, elicit higher LPC (Late Positive Complex) amplitudes, indicating stronger emotional reactions than positive elements. Positive design elements, like soft shapes and harmonious colors, significantly enhance consumer purchase intentions. However, negative emotions, such as those triggered by harsh materials or strong color contrasts, are more memorable and can reduce consumer interest in the brand over time. Designers are advised to prioritize shapes and materials that evoke positive emotions while being cautious with negative design elements, which may provoke stronger but adverse reactions. The study suggests strategies for optimizing emotional design, emphasizing emotional memory management and long-term brand perception to boost consumer loyalty and product desirability.

Introduction

In recent years, the design of consumer products has increasingly been driven by customer preferences, with a growing emphasis on the emotional connection between users and products. As technological advancements become less distinct across competing brands, companies are shifting focus from functional differentiation to emotional engagement through product design [1]. Modern consumers no longer purchase products solely for their utility; instead, they seek emotional fulfillment through the product’s image and aesthetic appeal. This shift marks a transformation in consumer behavior where purchasing decisions are influenced by emotional experiences, as the product serves as both a functional tool and an emotional trigger [2, 3]. For instance, in industries like fashion or personal accessories, emotional responses to design play a critical role in purchase decisions [4, 5]. Consequently, designers today integrate elements such as color, shape, and texture to evoke desired emotional responses, often leveraging principles of beauty and harmony [6].

Recent studies emphasize that emotions, especially negative emotions, have a profound impact on purchase decisions, as they can deter or delay purchasing even more effectively than positive emotions can encourage it [7, 8]. While consumers often respond to attractive designs with a sense of pleasure, negative emotions triggered by unfavorable design elements can be equally powerful. Understanding how negative emotions influence purchasing decisions is crucial in industries such as watch design, where aesthetic appeal and emotional resonance are critical to brand differentiation. Negative emotional responses, such as discomfort or displeasure with a product’s appearance, can create lasting adverse impressions, significantly affecting consumer loyalty and brand perception [9, 10].

Traditional tools for evaluating consumer emotions, such as surveys and Likert scales, are limited by subjective biases, such as the respondents’ interpretations of the questions or their ability to express emotional reactions accurately [9, 11, 12]. Recent advancements in neurophysiological measurements, such as electroencephalography (EEG) and galvanic skin response (GSR), provide more objective insights into consumers’ emotional states. These methods allow researchers to capture real-time brain activity and physiological responses to stimuli, offering a more accurate representation of the emotional impact of product designs. For instance, EEG measures brainwave reactions associated with recognition, decision-making, and emotional evaluation, providing a more nuanced understanding of how negative design elements may evoke adverse emotional responses [13]. These physiological indicators are particularly useful for identifying negative emotions that may not be consciously acknowledged by consumers, yet strongly influence purchasing behavior [14].

Emotion dimension measurement

The measurement of emotions in consumer research often relies on the two dimensions of valence and arousal [8, 15] (Fig. 1). Valence refers to the degree of positive or negative emotional response, while arousal measures the intensity of the emotion, from calmness to excitement. Together, these dimensions help categorize emotional experiences on a spectrum, ranging from pleasant, high-arousal emotions (such as excitement) to unpleasant, low-arousal emotions (such as sadness or indifference). Research has shown that consumers’ emotional reactions to product designs are influenced by visual stimuli, such as color, shape, and form [16,17,18]. For example, angular shapes, such as triangles, tend to evoke more negative emotions compared to softer, more rounded forms [19].

Fig. 1

Dimension of affect: horizontal axis is valance; vertical axis is arousal [8]

Fig. 2

Basic types of watch frame and watch surface shape

In the context of product design, negative emotional responses can be triggered by incongruent or unsettling design elements. Products that evoke unpleasant emotions, even subtly, can lead to reduced consumer interest or rejection. As negative emotions can have a stronger impact than positive ones, understanding their role in consumer behavior is critical for designers seeking to mitigate potential aversion to their products [20, 21]. Negative emotional triggers, such as an uncomfortable or jarring design, can overwhelm the product’s positive features, leading to a negative overall perception [14, 22].

Relevant research on ERP and emotions

The use of Event-Related Potentials (ERP) in emotion research has been instrumental in understanding how consumers react to product design at a neurological level. ERP studies have identified specific components, such as the Early Posterior Negativity (EPN) and Late Positive Component (LPC), which reflect the brain’s emotional and attentional responses to visual stimuli [23,24,25]. EPN is associated with early attentional processing of emotional stimuli, while LPC reflects sustained attention to emotionally charged images [26]. These components are particularly useful in studying the effects of negative emotions, as they can reveal how quickly and intensely consumers react to negative design elements [27].

Negative emotional stimuli, such as threatening or displeasing images, tend to elicit stronger and more prolonged ERP responses compared to neutral or positive stimuli [28,29,30]. This suggests that negative emotions not only capture consumers’ attention more effectively but also have a more lasting impact on their perception and decision-making processes [31]. Understanding these neurological responses allows designers to better predict how consumers will react to certain product features and adjust designs to avoid negative emotional triggers.

The LPC has been widely used in research to evaluate the significance of emotional stimuli, particularly in the context of negative emotions [32]. Studies have consistently shown that negative stimuli, such as unsettling or unattractive designs, produce stronger LPC amplitudes than neutral or positive stimuli [33]. This phenomenon, known as the “negativity bias,” suggests that consumers devote more cognitive resources to processing negative information, making it more influential in their decision-making processes [34]. In product design, this bias can be detrimental if negative emotional reactions outweigh positive aspects of the product, leading to rejection or dissatisfaction [35].

Research has also shown that while positive emotions can enhance the appeal of a product, negative emotions are often more memorable and have a greater impact on consumers’ long-term perceptions [36]. For instance, a watch design that evokes feelings of discomfort or displeasure due to its shape, color, or material may be more likely to be remembered and avoided, even if it possesses other desirable features [37]. As such, understanding how to mitigate negative emotional responses in product design is critical for ensuring consumer satisfaction and loyalty.

Purpose of the research

This research aims to investigate how negative emotions, triggered by specific design elements, influence consumers’ purchase decisions. Using watches as a case study, this research will explore the emotional responses elicited by various design features, such as shape, color, and material. To systematically analyze these effects, the study will employ ERP measurements to objectively assess the emotional reactions of consumers to these design elements [38]. Based on the theoretical framework and preliminary findings, this study hypothesizes that unfavorable watch design features will elicit stronger neural responses (e.g., increased LPC amplitudes), reflecting heightened emotional and cognitive processing, which may in turn influence consumers’ purchase intention. The ultimate goal is to provide designers with actionable insights on how to avoid negative emotional triggers and enhance the overall emotional appeal of their products. In a competitive market where aesthetic and emotional connections are key differentiators, understanding the impact of negative emotions is essential for creating products that resonate with consumers and foster positive brand associations.

Methods

Participants

This study recruited 16 participants (11 males and 5 females; M = 23.38 years, SD = 1.26) from Taiwan. All participants had at least a college-level education in industrial design and had received formal training in product aesthetics and shape design [39]. The rationale for selecting participants with an industrial design background was to ensure consistent visual literacy and evaluative ability. This helped reduce data variability caused by differences in visual interpretation and enabled more accurate observation of participants’ emotional and cognitive responses to specific design elements. To control for familiarity bias, participants were screened to exclude individuals with prior exposure to luxury watch brands to ensure that emotional responses were influenced by design features rather than brand familiarity. Participants were also required to be right-handed to minimize variability in EEG lateralization effects [12]. Additionally, all participants had normal or corrected-to-normal vision, ensuring that visual acuity differences did not affect perception. This study was reviewed and approved by the Research Ethics Committee of National Taiwan University, and all participants provided written informed consent in accordance with the Declaration of Helsinki.

Sample

Card sorting for selecting sample

In the first stage, a structured card sorting task was conducted to classify and select representative watch designs for the study. Three expert judges (3 males; M = 45.66 years, SD = 5.6) with over 6 years of experience in product design and watch collection participated in the classification of 360 watch images. The watches were categorized based on shape (round, square, triangle, etc.), proportion (1:1 vs. 1:1.5), and surface elements (traditional vs. smart interfaces). To ensure experimental control, confounding elements such as electronic displays, numerical markings, and excessive decorations were removed.

Additionally, material properties were manipulated through surface texture variations, including smooth vs. rough and warm vs. cold metallic textures. These variations were systematically controlled in the 3D-rendered images using Rhino (3D modeling software) and KeyShot (rendering software) to simulate different material perceptions while ensuring that only visual stimuli influenced participants’ emotional responses, eliminating potential confounds from tactile sensations (Fig. 2) and Table 1.

Questionnaire evaluation

The second stage assessed participants’ emotional responses to the selected watch designs using a semantic differential scale questionnaire. A total of 30 participants (15 males, 15 females; M = 21.33 years, SD = 1.0) with industrial design backgrounds participated in this phase to ensure they possessed sufficient visual and aesthetic literacy, allowing them to assess subtle design cues and their emotional impact more reliably. Each participant evaluated the emotional impact of the watch designs, ensuring a reliable assessment of their affective responses. The questionnaire applied the Affective Valence Model [3, 15] to measure emotional valence, distinguishing between pleasant and unpleasant feelings, as well as arousal, which captures the intensity of emotional stimulation. This method is widely used in affective neuroscience research to evaluate the emotional perception of visual stimuli [40].

To ensure the reliability and validity of the study, the questionnaire followed a structured approach to assess emotional responses to the watch designs. Participants rated the watch designs on a 5-point Likert scale to quantify their emotional responses. Results showed that positive designs (N = 30) had a mean valence score of 3.45 (SD = 0.39), ranging from 4.07 to 3.00, indicating a generally high positive emotional response. Conversely, negative designs (N = 30) had a mean score of 2.06 (SD = 0.30), with a range of 2.53 to 1.33, confirming their lower affect valence. Based on these ratings, 30 high-positive and 30 high-negative watches were selected, along with 30 neutral images from the Nencki Affective Picture System (NAPS) [8, 41] as controls. Therefore, 90 images were chosen to represent distinct emotional categories and ensure a balanced experimental design for the subsequent neurophysiological testing. The distribution of selected images across different emotional categories is visually depicted in Fig. 3.

Fig. 3

Positive, negative, and neutral samples

This questionnaire phase was crucial in refining the experimental stimuli, as it ensured that the selected watch designs effectively triggered the intended emotional responses. The inclusion of neutral images from the NAPS database further strengthened the study’s methodological rigor by providing a standardized reference for emotional neutrality. By systematically evaluating participants’ affective responses through this structured assessment, the study was able to establish a strong foundation for the subsequent ERP experiment, aligning the stimulus selection with the research objective.

Procedure

Participants were tested in a sound-insulated recording room to minimize external auditory distractions. The room’s lighting was kept consistent with daily indoor lighting conditions, ensuring that brightness levels did not influence visual perception. Participants were seated in a comfortable chair, maintaining a fixed distance of approximately 60 cm from the center of the screen to ensure standardized viewing conditions across trials. Before the experiment, each participant received detailed instructions about the testing procedure. They were instructed to maintain a relaxed posture and minimal body movement to prevent EMG artifacts in the EEG recordings. Once the participants confirmed that they understood the procedure, the experiment commenced. Although all participants had received professional training in product design, they were not exposed to any design instruction or guidance related to the context of this experiment prior to the study. In addition, no information about design preference was provided during the experiment. The entire procedure emphasized natural and intuitive visual and emotional responses to minimize potential bias.

As shown in Fig. 4, each trial began with the presentation of a fixation cross at the center of the screen for 1000 ms. This fixation period ensured that participants were visually aligned with the screen and ready for the upcoming stimulus. Following the fixation cross, a blank inter-stimulus interval (ISI) of 1000 ms was introduced to prevent carryover effects between trials. After the ISI, the watch stimulus was displayed for 2000 ms, allowing participants sufficient time to visually process the design. This sequence was followed by another 1000 ms ISI before the next trial began. Each participant completed 90 trials, with each stimulus appearing only once in a randomized order to counterbalance potential learning effects. A 10-minute break was provided at the midpoint of the experiment to prevent fatigue and maintain attentional consistency.

Fig. 4

ERP testing procedure

This study did not include a behavioral response task (e.g., button presses) during the EEG recording. The primary objective was to capture participants’ spontaneous neural responses to product design features without introducing additional cognitive processes associated with decision-making or motor execution. This approach is consistent with prior ERP studies investigating passive emotional processing [42], ensuring that brain activity reflects automatic affective responses rather than task-induced artifacts.

ERP recording

The study used a NeXus-32 EEG system (Mind Media, Netherlands) with 32 wireless electrodes for ERP data collection. The device was selected for its high signal quality and flexibility in non-invasive neurophysiological research. Electrode impedance was maintained below 5 kΩ to ensure signal stability and minimize electrical noise interference. The 10–20 international system was used for electrode placement, ensuring standardized spatial distribution across participants. EEG signals were recorded at a sampling rate of 250 Hz, with a band-pass filter between 0.5 and 60 Hz applied to remove low-frequency drift and high-frequency muscle artifacts. Data collection spanned 0 ms (stimulus onset) to 1000 ms post-stimulus, capturing both early sensory processing and later cognitive responses. To enhance data quality, a multi-stage artifact rejection pipeline was implemented. Eye movement artifacts exceeding 80 µV were identified and corrected using the [43, 44] method to compensate for vertical blinks and lateral eye movements, preventing contamination in frontal and central electrode sites. Additionally, high-frequency noise above 20 Hz in the frontal lobe was removed following [42] EEG best practices, ensuring that only task-relevant neural activity was retained.

The EEG data underwent preliminary filtering using BioTrace + software, followed by segmentation, baseline correction, and trial averaging using WINEEG 2.124.95 software to extract ERPs. Brainwave segmentation was performed continuously from 0 to 1000 ms, ensuring full coverage of early sensory and late cognitive responses. Individual ERP waveforms that exceeded artifact rejection thresholds were excluded from further analysis, ensuring only high-quality EEG data were used in statistical processing.

Nine electrode sites were selected for LPC analysis, representing key scalp regions for emotional and cognitive processing of visual stimuli [45]. These sites were categorized into three anterior-posterior regions and three left-right hemispheric zones: left-anterior (F3), middle-anterior (Fz), right-anterior (F4), left-central (C3), middle-central (Cz), right-central (C4), left-posterior (P3), middle-posterior (Pz), and right-posterior (P4)). Figure 5 displays the ERP amplitude distributions recorded at these sites. ERP waveform analysis revealed that the lowest LPC amplitude peak occurred at Cz at approximately 644 ms, while the highest peak appeared around 748 ms. Following this peak, the waveform gradually declined, forming a complete LPC wave shape between 680 ms and 800 ms. Therefore, the 680–800 ms time window [46] was selected for LPC amplitude analysis, as this period represents the peak of cognitive-emotional processing. The EEG signal from this window was segmented, averaged within each participant’s condition, and computed into a grand average waveform across all participants.

Fig. 5

ERP waveform: LPC position is at approximately 680 ms to 800 ms

Data analysis

To analyze LPC amplitude and ERP responses related to watch shape perception, a combination of Repeated Measures ANOVA (MANOVA) was employed. MANOVA was conducted to assess the effects of emotion category (positive, negative, neutral), anterior-posterior region (anterior, central, posterior), and left-right scalp distribution (left, medial, right). This analysis examined how different emotional valence conditions influenced ERP amplitudes, as well as how electrode positioning along the scalp impacted the neural responses to watch design features.

Regarding watch shape, MANOVA was applied to assess the effects of multiple related factors for watch frame and surface, including: frame shape (circle, ellipse, square, rectangle, triangle, arc), frame proportion (1:1 and 1:1.5), frame R angle (with R angle and without R angle), surface pattern (non-curving, point curving, line curving, point-line curving (black), line curving (black), multi-information, intelligent (black-white), intelligent color), surface content (traditional, intelligent), surface background (white, black), and surface color (black-white, Colorful).

The purpose of this analysis was to determine how various design elements of the watch influenced neural processing and emotional responses. The interaction effects between shape parameters and emotional categories were further analyzed using a second MANOVA, ensuring that significant shape-related factors were identified. To account for violations of sphericity assumptions, Greenhouse-Geisser corrections (G-G corrections) were applied to adjust degrees of freedom for F-tests, ensuring that non-sphericity did not artificially inflate statistical significance. For pairwise comparisons, Bonferroni corrections were implemented to control for Type I errors, ensuring that multiple comparisons did not produce spurious significant results, thereby maintaining the integrity of the findings.

Results

LPC effect (600–800 ms)

Table 2 presents the LPC average amplitude and standard deviation for the positive, negative and neutral stimulants. Results showed that positive stimuli (N = 30) had a mean LPC amplitude of 0.89 (SD = 1.41), ranging from 1.25 to 0.47, indicating a generally high positive emotional response. Conversely, negative stimuli (N = 30) had a mean LPC amplitude of 1.64 (SD = 1.26), with a range of 2.07 to 0.95, suggesting a stronger emotional processing effect. Neutral stimuli (N = 30) had the lowest mean LPC amplitude of 0.37 (SD = 1.60), ranging from 0.75 to -0.42, confirming the absence of significant emotional engagement. The neutral stimulant is obviously lower than the positive and negative stimulants. Generally speaking, due to the neutral stimulant having no elements related to emotions, the participants will not produce any emotional reaction [33]. The positive, negative and neutral stimulants will all arouse high amplitude to the afterbrain.

Table 1 Sample list

Table 2 Group mean LPC amplitudes of the responses to positive, negative, and neuronal conditions that were recorded from 9 electrodes over 9 regions of the scalp: left-anterior (F3), middle-anterior (Fz), right-anterior (F4), left-central (C3), middle-central (Cz), right-central(C4), left-posterior (P3), middle-posterior (Pz), and right-posterior (P4) (standard deviation of the mean in parentheses)

Table 3, with respect to the overall detection of MANOVA to LPC, the emotions have the main effect (F [2,30] = 5.51, p <.05). The emotion × left–right factor interaction (F[4, 60] = 2.84, p <.05, ε = 0.68) and the anterior–posterior × left–right factor interaction (F[4, 60] = 3.02, p =.05, ε = 0.63) demonstrate statistically significant effects. The detection of the double-factor MANOVA in a positive vs. neuronal comparison identified that emotion and the left–right factor do not have the interactive effect (p =.12), and through the detection of double-factor MANOVA negative vs. neuronal it found that emotions and the left–right factor do not have the interactive effect (F [2,30] = 4.43, p <.05, ε = 0.73). After the post detection, the amplitude of the negative in the left, medial, and right zones is obviously larger than the neuronal (respectively F [1,15] = 5.08, p <.05; F [1,15] = 9.46, p <.01; F [1,15] = 9.45, p <.01), and that through the detection of double-factor MANOVA that a positive vs. negative comparison showed that emotion and left–right factor do not have the interactive effect (p =.90).

Table 3 LPC amplitude results for MANOVA analysis for positive, negative and neutral emotions

Influence of designed shape on emotion

Table 4 indicates the LPC average amplitude of frame and surface under the positive and negative stimulants. The average amplitudes (standard deviation) of frame under the positive and negative stimulants are 0.65 (2.42) and 1.49 (1.69), respectively; the average amplitudes (standard deviation) of the surface under the positive and negative stimulants are 0.77 (2.09) and 1.50 (2.19), respectively.

Table 4 LPC average amplitudes for frame and surface with positive and negative stimulants

By comparing the values of average amplitudes, the amplitude for the frame shape is the highest with the negative triangle, and the negative arc takes second place, while the amplitude for the positive ellipse shape is the lowest. The amplitude for the frame proportion is the highest with the negative 1:1, and the lowest for positive 1:1.5. The amplitude for the frame R angle is the highest with the negative R angle, and the lowest for the positive without R angle. In addition, the amplitude for the surface pattern is the highest with negative intelligence (black-white), and the negative line curving (black) takes second place, while the amplitude for the positive intelligent point curving is the lowest. The amplitude for surface color is the highest with the negative black-white, and the lowest for positive black. The amplitude for surface color is the highest with the negative black-white, and the lowest for positive color. In conclusion, regardless of the frame or surface, the LPC average amplitudes for all negative stimulants are the highest, and the lowest for positive stimulants.

Table 5 indicates the two-factor MANOVA comparison for neuronal vs. positive, and neuronal vs. negative emotions. In terms of the frame shape, the triangle and arc with negative emotions are significantly higher than the neutral (F [1,15] = 7.08, p <.05; F [1,15] = 4.82, p <.05), while the other shapes (round, ellipse, square and rectangle) have no significant difference to any emotion. With respect to proportion, only the negative emotion 1:1 proportion is significantly higher than the neutral (F [1,15] = 13.14, p <.01). In terms of R angle, the negative emotion with R angle and without R angle is significantly higher than the neutral (F [1,15] = 14.89, p <.01; F [1,15] = 5.33, p <.05).

Table 5 MANOVA results for positive, negative, and neuronal emotions

In terms of the surface pattern, the negative emotion patterns, including the non-curving, point curving, multi-information, line curving (black) and intelligent (black-white) LPC, the amplitude is significant higher than the neutral (respectively F [1,15] = 5.05, p <.05; F [1, 15] = 10.62, p =.01; F [1,15] = 8.06, p <.05; F [1,15] = 11.99, p <.01), and the positive emotion of non-curving is also significant higher than the neutral (F [1,15] = 7.08, p <.05). In addition, in terms of the content, the content of the negative traditional form is significant higher than the neutral (F [1,15] = 6.14, p <.05). In terms of the background, the white and black background of the negative emotion is significant higher than the neutral (respectively, F [1,15] = 5.70, p <.05 and F [1,15] = 4.78, p-=0.05). In terms of the color, the black-white surface of the negative emotion is significantly higher than the neutral (F [1,15] = 7.51, p <.05).

Discussion

This study investigates how unfavorable visual features in wristwatch design may elicit negative emotional responses and potentially influence consumers’ purchase intentions. The research focuses on visual geometric elements—such as frame and surface—and employs event-related potential (ERP) neurophysiological techniques to objectively capture participants’ emotional and cognitive reactions to these design stimuli. The ERP findings indicate that such unfavorable design features evoke significantly heightened neural responses, providing empirical support for the study’s hypothesis. The following sections will further discuss and interpret these results.

The relationship between negative emotions and consumer purchase intentions

Emotions play a crucial role in consumer decision making [4]. Moreover, negative emotions often have a greater impact on consumer decisions than positive emotions [7]. These include frame shapes such as triangle and arc, a 1:1 proportion, and complex surface patterns like non-curving, point curving, line curving (black), multi-information, and intelligent (black-white). These design features are significantly associated with stronger negative emotional responses [22, 30]. Additionally, watches with traditional content, black or white backgrounds, and high-contrast black-white color schemes elicited heightened neural responses, suggesting enhanced cognitive and emotional processing in the brain [18, 29]. This indicates that the significant increase in LPC amplitude suggests that participants experienced greater attentional and emotional conflict when viewing these designs [25]. These visual elements are often perceived as visually inharmonious, which can lead to emotional discomfort and ultimately reduce purchase intention [11, 20, 21]. Therefore, designers should incorporate consumers’ emotional needs into the product development process to enhance product appeal and user satisfaction [47, 48].

Unfortunately, negative emotions tend to be more intense and longer-lasting than positive emotions [11, 23]. This suggests that negative emotions evoked by watch design elements may leave a lasting impression on consumers, causing them to avoid the brand or product over time, even if the product has other positive attributes [37]. This is consistent with the concept of “negative emotion bias” [35], which highlights the bias of consumers to retain negative emotional memories when encountering design elements. In this case, it may be difficult for consumers to think rationally when faced with unpleasant product designs. Designers should be careful when choosing elements that may evoke negative emotions and should avoid overusing such elements.

The influence of frame shape on negative emotion

Shapes with sharp angles are more likely to trigger negative emotional responses. This study found that triangle and arc frame designs significantly increased LPC amplitudes under negative emotional stimulation, indicating enhanced cognitive and emotional engagement [22, 30]. These reactions may stem from the visual sharpness and perceived threat typically associated with pointed geometry [19, 20]. Previous study has indicated that triangular shapes are subconsciously associated with danger or warning. For instance, triangles are frequently used in caution signage due to their acute angles and visual prominence, which capture attention and activate avoidance tendencies [19]. Angular shapes activate the amygdala—linked to threat detection—more than curved shapes, resulting in heightened negative affect [29].

Interestingly, arc designs, while lacking acute corners, also elicited strong emotional responses. Their semi-circular, asymmetric forms may disrupt visual expectations and symmetry, increasing perceptual salience and discomfort. Aesthetic evaluations are influenced by visual balance and predictability; arc shapes, which deviate from symmetrical standards, may demand greater cognitive resources for processing [30].

Therefore, Triangle shapes tend to evoke avoidance due to their threat associations, while Arc forms may trigger emotional unease through asymmetry and perceptual imbalance. Although both enhance product distinctiveness, they may reduce emotional comfort and consumer appeal. For designers, these findings highlight the need to balance form innovation with emotional compatibility. Overly provocative frame shapes may inadvertently cause emotional rejection, undermining purchase intentions despite visual uniqueness.

The impact of complex surface patterns on negative emotion

Surface patterns are essential visual elements that influence consumers’ emotional impressions and cognitive load. This study found that several complex surface patterns—specifically non-curving, point curving, line curving (black), multi-information, and intelligent (black-white)—were significantly associated with increased LPC amplitudes under negative emotional conditions. This indicates that these patterns elicited stronger emotional responses and required greater cognitive resources for processing [22, 25, 30].

Non-curving and point curving designs lack fluidity, resulting in rigid visual perception, which may be interpreted as emotionally cold or unapproachable [10]. Particularly, line curving (black) and intelligent (black-white) patterns, with their high contrast and structured layouts, may be perceived as visually intense or overstimulating, triggering emotional discomfort and perceptual fatigue [25, 29]. These findings were consistent with [10], who demonstrated that visual complexity and deviation from prototypicality can increase cognitive effort and negatively affect aesthetic judgments.

In the context of product design, excessive detail or high-contrast layouts on a limited surface area, such as a watch face, can contribute to visual overload. This not only strains perception but also weakens the affective bond between the product and the user. When design stimuli exceed users’ perceptual capacity, negative affective responses are more likely to arise, which can lower consumers’ purchase intention and brand affinity [21, 37]. Therefore, designers should thus be cautious when incorporating visually complex or cognitively demanding patterns into product surfaces. Simplifying the arrangement or incorporating more visually harmonious elements may mitigate negative emotional reactions and support a more pleasant user experience.

The emotional conflict of traditional content in modern design

Traditional design elements do not always convey positive emotional experiences. In general, traditional watch content often include multiple visual elements such as tick marks, numerals, and hands. Compared to the minimalist displays of digital or intelligent watch, the traditional content designs may require more cognitive resources for quick recognition, which can lead to increased LPC amplitudes. Because higher visual complexity would lead to worse first impressions and lower aesthetic evaluations [10].

Moreover, for consumers accustomed to modern digital interfaces, traditional content on watch faces may symbolize obsolescence or inefficiency, conflicting with contemporary expectations of product language [47, 48]. This kind of semantic conflict could trigger stronger emotional and cognitive processing, as reflected by elevated LPC responses. Traditional designs that fail to align with modern aesthetic trends may be perceived as outdated or visually cluttered. Aesthetic evaluation is influenced by factors such as novelty and symmetry, and when a design fails to meet aesthetic expectations, it may evoke negative emotions [1, 30].

Although traditional content may appeal to nostalgic or culturally oriented markets, designers should carefully consider the context and ensure alignment with the overall product style. By striking a balance between historical imagery and emotional aesthetics, it is possible to mitigate negative emotional responses and enhance the overall appeal of the product.

The connection between colorless design and negative emotion

Color is a core element in design and has a particularly significant impact on emotions. Previous studies [38] suggest that color can strongly influence consumers’ emotional responses. This study found that both background color (black and white) and Watch color configuration (black-white) were significantly associated with increased LPC amplitudes, indicating stronger emotional arousal and cognitive effort [22, 25]. This suggests that black or white backgrounds, under certain contexts, may still provoke negative emotional responses. In particular, black-white color schemes are more likely to induce emotional discomfort [10, 29, 30, 47, 48].

In addition, patterned watch surfaces with black-white color, such as line curving (black) and intelligent (black-white), also significantly increased LPC amplitudes, indicating stronger emotional responses and greater cognitive load. While these designs convey a sense of modernity and technological sophistication due to their high contrast and structured appearance, they may cause emotional discomfort and a sense of detachment for users [22, 25, 29]. Black-white compositions tend to intensify visual tension, leading to more negative emotional evaluations [30]. Therefore, designers should be cautious when using black-white colors and high-contrast patterns on watch design, as these may trigger psychological resistance and reduce product appeal.

In contrast, watches with colored faces or backgrounds with color tended to elicit lower LPC amplitudes, indicating a lower emotional burden [38]. Therefore, incorporating color into watch design may help reduce emotional discomfort and enhance both product appeal and consumers’ purchase intention.

Conclusion

Negative emotions in product design present both challenges and opportunities. Designers and brands should adopt flexible emotional design strategies that respond to consumers’ emotional needs, reducing the impact of negative emotions or effectively leveraging them in appropriate contexts to achieve brand goals. Although negative emotions are typically seen as a risk in design, designers can, in certain cases, effectively use them to create unique product experiences. For example, some brands focus on challenging consumers’ comfort zones by introducing dissonant or unusual design elements to evoke strong reactions, thereby generating market attention and discussion. This strategy is particularly effective in avant-garde designs or niche markets, which rely on innovation and differentiation to attract specific consumer segments. In conclusion, while negative emotions often carry risks in product design, they can be skillfully managed and even leveraged in certain contexts to create memorable, distinctive consumer experiences. Designers should balance emotional factors, using them strategically to foster brand loyalty and consumer satisfaction.

Based on the findings of this study, the following three recommendations are made for designers: (1) Optimize design elements to reduce negative emotional triggers: Designers should prioritize the use of shapes and colors that evoke positive emotions, avoiding overly sharp or discordant design elements. Specifically, rounded shapes and soft colors are more likely to elicit pleasant emotional responses, thereby increasing consumers’ purchase intentions. (2) Enhance emotional compatibility of materials: The materials used in products should meet both functional requirements and provide a comfortable emotional experience. Designers should avoid using materials that may provoke discomfort or unpleasant sensations, particularly in products like wristwatches that come into direct contact with the skin. (3) Apply emotional design theory to strengthen emotional connections: Designers should delve deeper into emotional design theory and incorporate consumers’ emotional needs into the design process. By refining design elements and avoiding unnecessary negative emotional triggers, designers can enhance consumers’ positive emotional connections with products.

This study provides valuable insights into the impact of negative emotions on product purchase decisions; however, several limitations should be acknowledged, and future research directions considered: (1) The sample size of participants was relatively small, which may limit the generalizability of the findings to a broader consumer population. A larger sample size in future studies would help increase statistical power and improve the robustness of the conclusions. Moreover, with a larger dataset, predictive validation could be conducted using machine learning techniques to assess how ERP responses predict consumer preferences. (2) Additionally, all participants had industrial design backgrounds, which may not fully represent general consumer perceptions. Individuals trained in design may have heightened sensitivity to aesthetic elements, potentially influencing their emotional responses. Future studies should include a more diverse participant pool, incorporating individuals with varying levels of design expertise and different consumer demographics. (3) This study was conducted within a single cultural context in Taiwan, and cultural influences on emotional responses were not explicitly examined. Since emotion and aesthetic preferences are culturally shaped [49], future research should include cross-cultural comparisons to explore how consumer reactions to design features vary across different cultural settings. This would enhance the global relevance and generalizability of the findings. (4) Another promising direction is longitudinal studies on design perception, which could track how emotional responses to product design evolve over time, providing insights into the long-term effects of design on brand perception. By addressing these limitations and exploring new research directions, future studies can further refine our understanding of how negative emotions impact product perception and consumer decision-making.