1 Introduction

Product design is the process of designing a product by implementing the target performance or function based on the specifications that were set in the product planning stage. Product design can be divided into concept design, functional design, detailed design, and production design according to the stages of design processes. Therefore, the function, structure, and shape of a product are determined through four steps. In the design process, the design of surface is typically done at the later stage of product development, usually called as the design of color, finish and material design. Especially for the products that require direct contact and interaction with human, the surface design is important. If the product designer does not consider the surface of specific products properly, the user may feel uncomfortable when using the product and consequently will not buy the product. For example, when designing a yoga mat, if the area of contact with the body is too rough or hard, it will not satisfy both the designer’s intention and the consumer’s expectation. In this sense, the surface design have mainly focused on functional aspects of the product, such as ease of handling, convenience, and usability of handles, buttons, and sticks. However, as the design guideline gradually becomes clear, emotional design that emphasizes not only ease of manipulation, convenience, usability but also human tactile sensibility gains more attention. Although it depends on the product characteristics, emotional appeal is closely related with the purchase decision. Therefore, when designing the surface of product, it is necessary to reflect human tactile sense appropriately to meet the needs of the customer. However, it is not systematically investigated what expectation consumers have depending on the product categories. Thus, in this study, we focused on the surface characteristics of consumer products to check the expected emotions from the surface feeling.

2 Related Works

Among the various classification schemes for products to explain the purchase behavior Foote, Cone, & Belding grid (FCB grid) is one of the most cited. The FCB Grid is a comprehensive model created by Vaughn [9], for analyzing consumers’ purchase decisions. It analyzes the purchase decision process into two dimensions of high involvement and low involvement, thinking and feeling, it is used to establish appropriate advertising strategies depending on their location in the grid. For the ‘feel’ type product with low involvement are more likely to be influenced by affective appeals whereas ‘think’ type products with high involvement depends more on rational decision making processes. Along this line, the locations of tested products in FCB grid were identified o check proper coverage of interested consumer product set.

The surface of the product refers to the outermost or topmost part of the product. Therefore, the product surface differs depending on the material constituting the surface, and the surface stimulus varies depending on the characteristics of the material. Studies on tactile sensibility emerging from a material or a surface can be classified into a study on emotions according to physical characteristics related to surface roughness and a study on emotions according to vibro-tactile stimuli. For the first part, Chen et al. [1] investigated the physical characteristics of the surface in order to confirm the relationship between the tactile perception and the physical properties of the surface. A questionnaire consisting of 37 samples and 6 pairs of adjectives (warm-cold, slippery-sticky, smooth-rough, hard-soft, bumpy-flat, wet-dry) constructed the relationship between the characteristics and emotions. Kawasegi et al. [4] fabricated 14 different samples with different physical properties (pitch, height) to develop plastic molded parts with tactile properties to be used in various industrial fields. Morishima et al. [7] tried to express the tactile sensibility according to the physical properties of fibers by using 18 adjectives with five samples including nylon in order to obtain the physical properties of fibers to express tactile sensibility. Kim et al. [5] classifies the mechanical properties of automobile seat skin material into four types (Resilience, Bending Moment, Thickness, Friction) to make a prediction model for development of the skin material considering the mechanical characteristics and sensitivity of automobile seat skin material. The neural network model was constructed by expressing the mechanical properties of leather (natural, PU, PVC) using four kinds of sensibility (Softness, Elasticity, Volume, Stickiness) by using fuzzy logic. Dépeault et al. [2] classified the physical properties of surface roughness into 3 types (Longitudinal spacing, Transverse spacing, Dot density) and measured the physical properties and evaluated the surface roughness by making a cylindrical sample with protrusions on the surface. Park et al. [8] classified the degree of roughness of six different materials used in automobile interior materials into two physical property values ​​(Ra, Rz) in order to investigate the change of emotion when contacting with various car skin materials. In order to investigate the emotional changes caused by various fingertip vibrations, Hwang and Hwang [3] studied 29 emotional stimuli with frequency and sensory levels, Kim et al. [6] evaluated the responses of 10 types of adjectives to 15 stimuli with different frequencies and amplitudes.

Still, tactile sense is not fully known and understood yet, and many studies are under way to find the relationship between emotions and physical characteristics. Especially, studies on tactile sensibility that changes according to physical characteristics are limited to specific samples and materials. Therefore, in order to investigate various aspects of tactile sensibility, this study intends to identify the emotions that are related with the surface of a specified product groups.

3 Methods

To investigate the expected tactile emotions for material surfaces of products, online questionnaire was designed with 7 product categories and 12 emotional expressions, and data was collected from 121 participants.

3.1 Design of Questionnaire

Participants were asked to respond to the extent of agreeability for emotional expressions, which consumers expected to perceive from the material surfaces of products when they thought of a particular product. 12 (or 6 pairs of) emotional expressions for tactile perceptions of material surfaces were prepared from prior studies in the literature: cold/warm, sticky/slippery, hard/soft, dry/wet, flat/uneven, and rough/smooth. The extent of agreeability for each of 12 emotional expressions were measured with 7-point interval scales (1: strongly disagree, …, 4: neutral, …, 7: strongly agree).

7 product categories, such as bed, kitchen tool, VR (virtual reality) headset, body fat analyzer, yoga mat, digital door lock and electric drill, were presented to participants, who were supposed to think a preferred product that belonged to the presented product category, and described by words and pictures in the questionnaire. 7 product categories were selected because they were familiar to consumers and located in four spaces based on the FCB Grid. ‘High involvement/think’ includes ‘bed’, ‘VR headset’, ‘body fat analyzer’; ‘high involvement/feel’ includes ‘kitchen tool’; ‘low involvement/think’ includes ‘electric drill’ and ‘digital door lock’; and ‘low involvement/feel’ includes ‘yoga mat’.

3.2 Participants and Procedure

A total of 121 participants took part in the survey. They were 52 males (43.0%) and 69 females (57.0%). 87 participants (72.0%) belonged to the age group of 20 to 29 years old, and 27 participants (22.3%) were between 40 and 49 years old. The others were 4 participants (50–59 years old), 2 participants (30–39 years old) and 1 participant (equal to and more than 60 years old). Thus, with regard to age, majority of participants belonged to two age groups, ‘20–29 years old (72.0%)’ and ‘40–59 years old (25.6%)’.

Survey was conducted based on the online questionnaire, which was opened during a week and advertised by emails and SNS to Korean consumers. Thus, even though the questionnaire did not contain questions for ethnicity or nationality, it seemed that all of participants were Korean consumers. Participants were expected to respond to 12 questions for each of 7 product categories, while they thought of a preferred particular product from the presented product category, and the responses were automatically collected by online.

4 Results

The data collected from online survey was analyzed using ANOVA (analysis of variance) to find out whether there was significant difference among product categories for the expected tactile emotions. In addition, it was analyzed whether there were significant interaction effects between product categories and age groups for the expected tactile emotions.

4.1 Expected Emotions for Products

ANOVA was conducted for each of 12 expected tactile emotions to examine significant difference among 7 product categories, and Tukey multiple comparison tests were conducted to find out where there was significant difference.

‘Cold’/‘Warm’.

For ‘cold’ emotion, there is significant difference among product categories (F 6,819 = 15.35, p = 0.000). According to Tukey multiple comparison test, ‘digital door lock (mean = 4.65)’ and ‘electric drill (mean = 4.42)’ show significantly higher value than ‘bed (mean = 3.03)’ and ‘yoga mat (mean = 3.03)’ (see left graph in Fig. 1). Likewise, for ‘warm’ emotion, there is significant difference among product categories (F 6,819 = 21.05, p = 0.000), but ‘bed (mean = 3.94)’ show significantly higher value than ‘digital door lock (mean = 2.12)’ according to Tukey multiple comparison test (see right graph in Fig. 1). Therefore, it could be inferred that consumers expect ‘cold’ emotion from the surface of ‘digital door lock’ and ‘electric drill’, and that consumers associate ‘warm’ emotion with the surface of ‘bed’ rather than the others but the association strength is not high.

Fig. 1.
figure 1

Products and ‘Cold’/‘Warm’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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‘Sticky’/‘Slippery’.

For ‘sticky’ emotion, there is significant difference among product categories (F 6,819 = 13.18, p = 0.000). According to Tukey multiple comparison test, ‘yoga mat (mean = 2.35)’ show significantly higher value than the others (see left graph in Fig. 2). Meanwhile, for ‘slippery’ emotion, there is significant difference among product categories (F 6,819 = 5.34, p = 0.000), and ‘digital door lock (mean = 3.34)’ show significantly higher value than ‘bed (mean = 2.36)’ and ‘electric drill (mean = 2.43)’ according to Tukey multiple comparison test (see right graph in Fig. 2). Therefore, it could be inferred that consumers do not usually expect ‘sticky’ and ‘slippery’ emotions from the surfaces of all 7 product categories, but relatively associate ‘sticky’ and ‘slippery’ emotions with the surfaces of ‘yoga mat’ and ‘digital door lock’, respectively, compared to the others.

Fig. 2.
figure 2

Products and ‘Sticky’/‘Slippery’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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‘Hard’/‘Soft’.

For ‘hard’ emotion, there is significant difference among product categories (F 6,819 = 70.35, p = 0.000). According to Tukey multiple comparison test, ‘kitchen tool (mean = 4.74)’, ‘VR headset (mean = 4.49)’, ‘body fat analyzer (mean = 4.85)’, ‘digital door lock (mean = 4.96)’ and ‘electric drill (mean = 5.12)’ show significantly higher value than ‘bed (mean = 2.48)’ and ‘yoga mat (mean = 1.97)’ (see left graph in Fig. 3). On the contrary, ‘soft’ emotion (F 6,819 = 106.2, p = 0.000) shows the exact opposite pattern to ‘hard’ emotion with product categories (see right graph in Fig. 3). Therefore, it could be inferred that consumers expect ‘hard’ emotion from the surface of ‘kitchen tool’ ‘VR headset’, ‘body fat analyzer’, ‘digital door lock’ and ‘electric drill’, and ‘soft’ emotion from the surfaces of ‘bed’ and ‘yoga mat’.

Fig. 3.
figure 3

Products and ‘Hard’/‘Soft’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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‘Dry’/‘Wet’.

For ‘dry’ emotion, there is no significant difference among product categories (F 6,819 = 1.44, p = 0.197) (see left graph in Fig. 4). Meanwhile, for ‘wet’ emotion, there is significant difference among product categories (F 6,819 = 12.6, p = 0.197), and ‘kitchen tool (mean = 2.63)’ show significantly higher value than the others according to Tukey multiple comparison test (see right graph in Fig. 4). Therefore, it could be inferred that consumers are neutral to all of product categories for ‘dry’ emotion, and that consumers do not usually expect ‘wet’ emotion from the surfaces of all 7 product categories, but relatively associate ‘wet’ emotion with the surfaces of ‘kitchen tool’ compared to the others.

Fig. 4.
figure 4

Products and ‘Dry’/‘Wet’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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‘Flat’/‘Uneven’.

For ‘flat’ emotion, there is significant difference among product categories (F 6,819 = 17.53, p = 0.000). According to Tukey multiple comparison test, ‘digital door lock (mean = 4.57)’ show significantly higher value than ‘VR headset (mean = 3.77)’ and ‘electric drill (mean = 2.41)’ (see left graph in Fig. 5). Meanwhile, for ‘uneven’ emotion, there is significant difference among product categories (F 6,819 = 18.62, p = 0.000), and ‘electric drill (mean = 3.65)’ show significantly higher value than the others according to Tukey multiple comparison test (see right graph in Fig. 5). Therefore, it could be inferred that consumers expect ‘flat’ emotion from the surface of ‘digital door lock’, and that consumers do not usually expect ‘uneven’ emotion from the surfaces of all 7 product categories, but relatively associate ‘uneven’ emotion with the surface of ‘electric drill’, compared to the others.

Fig. 5.
figure 5

Products and ‘Flat’/‘Uneven’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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‘Rough’/‘Smooth’.

For ‘rough’ emotion, there is significant difference among product categories (F 6,819 = 25.35, p = 0.000). According to Tukey multiple comparison test, ‘electric drill (mean = 3.53)’ show significantly higher value than the others (see left graph in Fig. 6). Meanwhile, for ‘smooth’ emotion, there is significant difference among product categories (F 6,819 = 12.47, p = 0.000), and ‘kitchen tool (mean = 4.90)’ and ‘digital door lock (mean = 4.83)’ show significantly higher value than ‘yoga mat (mean = 3.98)’ and ‘electric drill (mean = 3.19)’ according to Tukey multiple comparison test (see right graph in Fig. 6). Therefore, it could be inferred that consumers expect ‘smooth’ emotion from the surface of ‘kitchen tool’ and ‘digital door lock’, and that consumers do not usually expect ‘rough’ emotion from the surfaces of all 7 product categories, but relatively associate ‘rough’ emotion with the surface of ‘electric drill’, compared to the others.

Fig. 6.
figure 6

Products and ‘Rough’/‘Smooth’ (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill; alphabets indicate Tukey multiple comparison groups)

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4.2 Interaction Effects Between Products and Age Groups

Majority of participants were divided by age into two groups: ‘younger group: 20–29 years old (n = 87)’ and ‘elder group: 40–59 years old (n = 31)’. Interaction effects between product categories and age groups were investigated for each of 12 emotions, and it was found that ‘soft (F 6,805 = 2.66, p = 0.015)’ and ‘uneven (F 6,805 = 3.99, p = 0.001)’ emotions showed significant interaction effects. For ‘soft’ emotion, younger group (mean = 5.08) shows significantly higher value than elder group (mean = 3.66) in ‘bed’ product, according to Tukey multiple comparison test (see Fig. 7). Meanwhile, for ‘uneven’ emotion, younger group (mean = 3.97) shows significantly higher value than elder group (mean = 2.62) in ‘electric drill’ product, and likewise, younger group (mean = 3.39) shows significantly higher value than elder group (mean = 1.83) in ‘yoga mat’ product, according to Tukey multiple comparison test (see Fig. 8). Therefore, it could be inferred that younger consumers expect softer beds than elder consumers, and that all consumers do not usually expect ‘uneven’ emotion from the surfaces of electric drills and yoga mats, but younger consumers would like to easily associate ‘uneven’ emotion with the surfaces of ‘electric drill’ and ‘yoga mat’ rather than elder consumers.

Fig. 7.
figure 7

Products and ‘Soft’ by age groups (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill)

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Fig. 8.
figure 8

Products and ‘Uneven’ by age groups (Bd: Bed, Kt: Kitchen tool, VR: VR headset, Bf: Body fat analyzer, Ym: Yoga mat, Dl: Digital door lock, and Ed: Electric drill)

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5 Discussion and Conclusions

This study investigated what emotions consumers expected from the surfaces of products through their tactile perceptions. 7 product categories were selected to represent all spaces of FCB grid, and 12 emotional expressions were used to measure tactile emotions perceived from surfaces of products. Based on the data collected from online survey, we can conclude what emotions consumers expect from the tactile perception on product surfaces as follows.

First, consumers expect ‘soft’ emotion from ‘bed’ and ‘yoga mat’ surfaces. Especially, younger consumers expect soft emotion from bed more than elder consumers. Second, consumers expect ‘hard’ and ‘smooth’ emotions from ‘kitchen tool’ surfaces. Third, consumers expect ‘hard’ emotion from ‘VR headset’ and ‘body fat analyzer’ surfaces. Fourth, consumers expect ‘cold’, ‘hard’, ‘flat’ and ‘smooth’ emotions from ‘digital door lock’ surfaces. Finally, consumers expect ‘cold’ and ‘hard’ emotions from ‘electric drill’ surfaces. These conclusions show what emotions product designers should focus on relatively when designing the product surfaces, even though product surfaces have many emotions perceived by consumers.

Since this study is an exploratory study for expecting consumer’s tactile emotions for product surfaces, there are some limitations to achieve research goals. This study only measure consumer’s expectation based on online questionnaire. Survey participants responded the questions depending on their memory related to using a particular product. More elaborate experiments with a number of variables related to product surfaces would be needed for further study rather than the survey.