1

Ethnic Impression Structure in Car Seat Fabric

*Graduate School of Engineering, Takushoku University, Japan**Takushoku University, Japan, *** Shibaura Institute of Technology, Japan

Narumi TAKESHITA*, Julaila ABDUL RAHMAN*, Akira KIJIMA**, Shigeru FURUYA***, Masahito TAKIZAWA**

1. Introduction

Trend changes in various areas have a big impact on social transitions, and vice versa. Trend change duration

can be divided into three categories: short, intermediate, and long [1]. Trends that change slowly over a long

period best relate to automotive design. Automotive design has a long development history, and its trend

transitions have happened throughout the world.

Various factors contribute to car design changes, including social transitions [2]. However, the factors that

influence car trend transitions are still being examined. It is believed that factors that significantly influence car

trend changes between countries can be grasped by observing ethnic impressions. In doing so, it is believed that

this study can be used as an initial idea for companies to re-strategize their design transitions for other countries.

2. Research Background

2.1 Trend Transition in Car Design

Japanese car designs are popular throughout the world. In Asian countries, such as Malaysia, many local car

factories collaborate with Japan in order to support local automotive industries [3]. It can therefore be said that

Japanese car trends in both exterior and interior designs have been transferred to other countries. However, the

way in which trends in automotive design elements change is still an open question.

Abstract: Trends have been broadly transferred throughout the world, especially in the recent glo-

balization era. In order to grasp the way in which trend transitions happen, the ethnic impression

of one trend needs to be observed in advance. Through ethnic impression studies, the factors that

influence car trend transitions between countries can be determined as well. In order to obtain this

study aim, a survey on the impression evaluation of one element, car seat fabric, was performed

in Japan and Malaysia. Data collected were analysed by factor analysis. As a result, four kinds of

factors were obtained: [comfortableness], [fanciness], [brightness], and [heaviness]. Samples were

then grouped, via a cluster analysis that measures distance scores, based on comfortableness and

colour brightness. The resulting groups were A [soft and bright], B [hard and dark], C [moderately

soft and dark], and D [moderately soft and bright]. Most of the same samples from both countries

were categorized into the same groups. In other words, even though the car seat fabric designs ap-

pear in two different countries, Japan and Malaysia, there is a kind of similarity in people’s impres-

sions of those designs, such as in their [comfortableness] and colour [brightness]. Moreover, it can

be assumed that this study shows that there are car design elements that undergo slow changes that

contribute to the slow car trend changes between countries.

Keywords: Ethnic impression, car seat fabric design, trend transition

2

Table 1 Sample Characteristics

Figure 1 Car Seat Fabric Design Development Process

2.2 Car Seat Fabric Design in

Development Process

Car interior spaces have a high

frequency in terms of user contact.

A good interior design leads to the

comfort and convenience of users. It

also cannot be denied that car seats

comprise the biggest area with which

users come in contact. Thus, one of

the common strategies to attract users

is seat fabric design because it is easy

to change. Seat fabric trends change

from time to time, but the changes

are limited due to car specification

requirements in terms of fabr ic

colours, patterns, and textures.

Normally, the car seat fabric design

development process begins with

a planning stage, dur ing which

Project Planning

NG

OKCheck

NG

OKCheck

NG

OKCheck

NG

OKCheck

5

6

Fabric Sample

Complete set seat sample

3 41 2

Single seat sample

Seat Simulation

CheckNG

OK

CheckNG

OK

Styling Research Fabric Concept

Evaluation on Decision Making Authorities

Image for seat sample changes by main fabric and side fabric arrangement Designer, Manager4

Product positioning base on line-up , market line-up, trends, users Designer, Manager1

Clear concept that could enhance the fabric elements to support interior design Designer, Manager2

Relation between concept and fabric sample elements : variant, pattern, texture Designer, Manager, Vendor3

Designer, Manager, VendorSingle seat image that considers fabric concept, texture and stitching5

Designer, ManagerInterior image when seat is assembled in the car6

Finish

7Final Design

7 Final design confirmation on overall exterior and interior design Top Management(RnD, Planning, Marketing)

research is conducted for design positioning and a sample mock-up is made. Several stages of design evaluation

take place in order to reach the potential final design. Design elements that fit with a particular culture, such as

fabric, are one of the most important criteria in selecting the designs, especially when trying to sell cars to other

countries. A number of studies have discussed the comfort of car seat fabric [4-5]. However, few studies have

examined ways to understand which elements significantly influence the car seat trend impression evaluation

differences between countries [Figure 1].

3. Research Objective

This research aims to observe the ethnic impressions of car seat fabric design trends between countries.

Thus, the ethnic impression structure is observed in advance in order to ascertain which element has the main

Sample Colour Pattern type Pattern size Texture Construction1 or 31 bluish grey plain small soft bolster2 or 32 black, grey abstract big hard woven3 or 33 black, grey geometry small hard knit4 or 34 medium grey geometry medium hard woven5 or 35 blusih grey geometry big soft bolster6 or 36 black, grey abstract big moderately soft woven7 or 37 reddish grey geometry small hard woven8 or 38 dark grey geometry small moderately soft bolster9 or 39 yellowish grey geometry medium soft woven10 or 40 bluish black geometry small moderately soft knit11 or 41 medium beige geometry small moderately soft knit12 or 42 black geometry medium hard woven13 or 43 grey, black, blue geometry medium moderately soft woven14 or 44 yellowish beige geometry big soft woven15 or 45 grey, black geometry medium hard woven16 or 46 grey, black geometry big moderately soft woven17 or 47 reddish beige geometry big soft woven18 or 48 grey, black geometry big soft woven19 or 49 yellowish grey, black natural big soft woven20 or 50 beige geometry medium moderately soft woven21 or 51 yellowish beige natural big moderately soft woven22 or 52 black, grey abstract big hard woven23 or 53 beige plain small moderately soft woven24 or 54 grey, black natural big soft knit25 or 55 black, white, grey geometry medium hard woven26 or 56 black geometry medium soft woven27 or 57 yellowish beige plain small soft knit28 or 58 black, grey, red geometry big hard knit29 or 59 beige natural big moderately soft woven30 or 60 medium grey natural big moderately soft woven

3

Figure 2 Sample Fabric Patterns

Sample 6 or 36

Sample 24 or 54

Sample 30 or 60

Sample 18 or 48

Sample 12 or 42

Sample 1 or 31

Sample 19 or 49

Sample 25 or 55

Sample 13 or 43

Sample 7 or 37

Sample 2 or 32

Sample 20 or 50

Sample 26 or 56

Sample 14 or 44

Sample 8 or 38

Sample 3 or 33

Sample 21 or 51

Sample 27 or 57

Sample 15 or 45

Sample 9 or 39

Sample 4 or 34

Sample 22 or 52

Sample 28 or 58

Sample Numbers: 1-30 for Japanese, 31-60 for Malaysian

Sample 16 or 46

Sample 10 or 40

Sample 5 or 35

Sample 23 or 53

Sample 29 or 59

Sample 17 or 47

Sample 11 or 41

impact on car trend transitions that happen between countries. By observing the factors that influence these

trend transitions, it is believed that this study can provide information for other kinds of product trend transition

studies. To achieve this research objective, Japan and Malaysia are taken as country examples and the survey

method is used, as discussed in the following section.

4. Research Method

4.1 Sample Selection

Thirty kinds of car seat fabric samples were selected from average kinds of design [Figure 2] in terms of colour,

pattern type and size, texture, and construction [Table 1]. Physical characteristics of samples also were checked

by a Wavelet Test in terms of its L*a*b* colour scale [6]. The a* and b* showed very little difference in their

cycle/image, so only L* will be discussed further in this study. The L* average shows the lightness average for

each frequency. In other words, at a certain frequency of colour, a certain contrast level that exists in one colour

for a sample will be determined [Figure 3]. A frequency of one cycle per image is only the first condition of

light and dark, and a frequency of 256 cycles per image is the 256th condition of light and dark. The L* standard

deviation graph shows that there is a scattering of colour contrast levels among all of the samples [Figure 4].

4.2 Research Outline

Twenty-two respondents aged 20 to 30 years old were selected from two groups, Japanese and Malaysians. Data

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Figure 3 L* ave of Frequency

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collected for the evaluation of Japanese and Malaysian respondents were mixed together. Thirty samples were

used; the Japanese samples were numbered 1 to 30 and the Malaysian samples 31-60 [Figure 2]. With this kind of

sample arrangement, it is believed that the result has a higher potential not only to show the difference between

both countries, but also to show the changes in impression evaluation from Japan to Malaysia. In relation to this,

12 paired evaluation terms for a questionnaire [Table 2] on a five-point Likert scale were chosen. For example,

in the evaluation of one sample with evaluation term ‘A-B’, only one answer needs to be selected: [highly A],

[moderately A], [neither A or B], [moderately B] and [highly B].

5. Result

5.1 Extraction of Potential Factors

The collected data was analysed by factor analysis. The principle component method and a varimax rotation

were employed. The number of factors extracted was determined by the eigenvalue before rotation. Only

factors with an eigenvalue greater than 1.0 were accepted. In total, four factors were extracted. The cumulative

contribution for the four factors was 76.15%. Table 3 shows the structure for the factor matrix.

Figure 4 L * std of Frequency

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light-heavyhard-softdark-brightblurr-clearinconvenience-convenienceunrefined-refined

cool-warmcheap-expensivetraditional-modernplain-showysimple-decorativeintellectual-emotional

Table 2 12 pairs of Evaluation Terms

5

Factor 1 includes the variables [comfortable], [refined], [warm] and [soft]. Factor 1 is categorized overall as

[comfortableness]. This factor relates to fabric comfort, particularly regarding texture. The length of fabric pile

contributes to the softness or roughness of the texture: the longer the pile, the softer the fabric.

Factor 2 includes the variables [showy], [decorative], [clear] and [expensive]. This group relates to the relative

quality, or [fanciness], of the fabric. Most of the samples involved high-quality finishes such as embossing or

shine effects.

Factor 3 includes the variables [bright], [warm], [traditional], and [emotional]. Factor 3 is categorized as

[brightness]. Both Japanese and Malaysian respondents evaluated the brightness or darkness and warmth or

coldness of the colour categorization of each fabric sample.

Factor 4 is known as [heaviness] and relates to the overall appearance of the fabric, which has strong contrasts

in its combinations of pattern size.

5.2 Sample Score Maps of Factor Analysis

Sample scores from the factor analysis were plotted into several maps in order to clearly observe the relation

between samples and factors. Then, a cluster analysis was performed in order to group the samples. In this stage,

only sample maps for Factors 1-2, 1-3, 1-4 and 2-4 were discussed. Other sample maps did not show the potential

results [Figure 5].

The axis of the map of Factor 1-2 is [fanciness - comfortableness]. There is also a direction for [soft luxury] and

[soft simple]. [Soft luxury] is for samples that have a decorative pattern and a soft texture. [Soft simple] is for

samples that have a small or basic pattern with a soft texture.

The axis of the map of Factor 1-3 is [comfortableness - brightness]. There are also directions for [warm soft]

and [cool soft], which show the direction of colour groups with soft textures. The axis of the map of Factor 1-4

is [comfortableness - heaviness]. There are also directions for [soft contrast] and [hard contrast]. The axis of the

map of Factor 2-4 is [fanciness - heaviness]. There are also directions for [hard decorative] and [soft decorative],

which have a hard or soft texture and a decorative pattern in terms of its size and shine effect.

5.3 Different Impression Evaluation between Japanese and Malaysia by Factor Score

The factor score maps for the samples were further discussed. Japanese sample scores numbered from 1 to 30

were mostly positioned in a kind of outer area on the map. In contrast, the Malaysian sample scores, numbered

Table 3 Structure of Factors

Variable

EigenvalueContribution rate (%)

Cumulative contribution rate (%)

Comfortableness Fanciness Brightness Heaviness

Discomfort-comfort

Notes: Factor loadings with absolute values less than .3 are omitted.

0.9180 -0.2630 -0.0462 -0.2931Unrefined-refined 0.7472 0.1349 0.0232 0.0255Hard-soft 0.6199 -0.2761 0.1913 -0.3887Plain-showy -0.0133 0.8957 -0.0397 0.1466Simple-decorative -0.1583 0.6708 -0.1109 0.3403Unclear-clear -0.0220 0.6579 -0.1354 -0.0318Cheap-expensive 0.5506 0.5801 0.0270 0.2504Dark-bright 0.2987 0.1891 0.8769 -0.3256Cold-hot 0.3145 -0.2860 0.5216 0.1915Classic-modern 0.0944 0.1794 -0.4803 0.0693Intellectual-emotional -0.3402 -0.0220 0.4002 0.0708Light-heavy -0.1585

3.6153 2.6199 1.7522 1.150330.03 21.83 14.60 66.5630.03 51.96 66.56 76.15

0.2489 -0.0861 0.9516

6

Figure 5 Score Maps for Factors 1-2, 1-3, 1-4 and 2-4

31 to 60, were mostly positioned in a kind of inner area on the map. Hence, it can be said that the Japanese

respondents had a wider evaluation of the samples. On the other hand, the Malaysian respondents had a smaller

evaluation of the samples and their understanding is more similar to each other [Figure 6].

One of the reasons for this is that Japanese people are outstanding in design ideas and they have detailed

preferences in that area because Japan is a highly developed country. In contrast, the understanding of design

among Malaysians is lower than it is in Japan. Malaysians may evaluate the details of design images in a similar

way because they have less information about design than do people in a highly developed country such as Japan.

5.4 Cluster analysis to show the fabric impression score between Japanese and Malaysian.

A cluster analysis was performed in order to obtain the relative distance between samples. The nearest distance

between samples shows a kind of similarity in its elements, and vice versa. The collected data was then analysed

by cluster analysis and yielded four groups: A, B, C, and D. Group A is categorized as [soft and bright], B is [hard

and dark], C is [moderately soft and dark] and D is [moderately soft and bright]. The groups were categorized

based on fabric texture and colour. In this analysis, the sample evaluation scores were numbered 1-30 for the

Japanese group and 31-60 for the Malaysian group. In this way, the difference in impression evaluation of trends

between both countries can be studied [Figure 7].

Almost all of the samples showed that the evaluation score of one sample between Japanese and Malaysian

respondents is positioned in one group. In other words, the distance is near the evaluation score of both

respondent groups. The three sets of samples with the closest evaluation scores were [27 and 57], [21 and 51] and

[29 and 59]. The three sets of samples with the most different impression scores were [26 and 56], [2 and 32] and

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Comfortableness

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Soft Luxury

Soft Simple

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Comfortableness

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Warm Soft

Cool Soft

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Figure 6 Evaluation Difference between Japan and Malaysia

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Figure 7 Distance Scores of Samples for Evaluation between Japanese and Malaysia

1 11 5 30 48 60 35 41 38 54 23 27 57 39 47 31 53 9 14 17 44 8 18 24 26 2 22 527 28 3 12 25 4 15 33 42 45 55 58 34 37 50 6 32 36 16 10 13 19 43 46 49 40 56 20 21 2951 59

A

B CD

[soft and bright]

[hard and dark] [moderately soft and dark][moderately soft, and bright]

Sample 21 or 51

Sample 29 or 59

Farthest in distance of sample scores between both countries

Closest in distance of sample scores between both countriesClosest in distance of sample scores between both countries

Close in distance of sample scores between both countries

Sample 6 or 36 Sample 19 or 49Sample 13 or 43Sample 16 or 46 Sample 10 or 40

Sample 2 or 32

Sample 2 or 32

Sample 3 or 33

Sample 4 or 34

Sample 20 or 50

Sample 22 or 52

Sample 25 or 55

Sample 28 or 58

Sample 15 or 45

Sample 7 or 37

Sample 12 or 42

Sample 23 or 53

Sample 27 or 57

Sample 30 or 60Sample 1 or 31 Sample 5 or 35

Sample 24 or 54

Sample 26 or 56

Sample 9 or 39Sample 11 or 41 Sample 14 or 44 Sample 17 or 47

Sample 18 or 48Sample 8 or 38

[20 and 50]. This result shows that there is almost no difference in the impression of fabric images between the

Japanese and Malaysian respondent groups.

Moreover, an analysis of variance by repetition of a two-way Anova was performed for the paired evaluation

terms. The two-way test represents the respondents and samples. The evaluation terms showed a 0% significance

difference, while the significance difference of the Japanese and Malaysian groups was 47%, which showed there

is no difference in the impressions of the Japanese and Malaysian groups.

Sample groups A, B, C, and D were analysed by L*std (lightness standard deviation) in cycle/image. The graphs

represent the contrast level of the samples. Larger pattern size and different colour brightness in the fabrics might

lead to higher levels of contrast in the graph. Graph A shows the highest contrast in the sample. The graphs

are arranged by decreasing contrast level: B, C, A, and D [Figure 12]. Samples that have similar impression

evaluation scores for both countries mostly occur in groups A, B, and C, which relate to consideration of colour

8

[brightness] in terms of contrast level in sample pattern and colour combinations.

6. Conclusion and Future Study

The four kinds of factors which best explain the impression evaluation of car seat fabric by Japanese and

Malaysian respondents are [comfortableness], [fanciness], [brightness], and [heaviness]. All of these factors have

a relation with the total image of the samples in terms of pattern, colour, and texture. Nonetheless, based on the

cluster analysis results, it can be said that the impression of fabric design images is almost the same between the

two countries based on two kinds of elements, which are mostly included in the factors [comfortableness] and

[brightness].

Car seat fabric design trends change from time to time, but those changes are very limited due to considerations

of various automotive requirements. Almost similar considerations of [comfortableness] and [brightness] by

respondents from both countries showed that Malaysians might be able to accept outstanding Japanese fabric

trends as they are offered on the market. However, some adjustment of the fabric in terms of its [fanciness] and

[heaviness] may be required with Malaysian local preference. It is believed that fabric design trends undergo very

small, limited changes between countries. This study thereby supports the existing evidence for long, slow car

trend changes between countries.

However, the detail preference of people from each country in selecting car seat design fabric is still in question.

In future research, Japanese and Malaysian preferences in car seat fabric should be observed separately and a

comparative study between both countries should be discussed further.

Reference

1. http://www.investopedia.com/terms/t/trend. asp#axzz28P2NpmiG, accesed April 2013.

2. Komada Hiroshi. Understanding Social transition through automobile Design History, Automobile

Technology 2012; 66: 6: 44-51.

3. http://sco.wikipedia.org/wiki/Perodua accessed April 2013.

4. Fueki Shintaro, Sato Hiroki. A study on the effect of interior environment on passenger comfort evaluation

by passenger seat user, Bulletion of JSSD, 2009; 56: 298-299.

5. Akiyoshi Murakami. Comfortable Seat for Vehicle - Evaluation of Seat Performance, Bulletion of JSSD,

2008; 111: 40-41.

6. http://www.hunterlab.com/appnotes/an08_96a.pdf, accessed April 2013.

Figure 8 Lightness Standard Deviation (L*std) in cycle/image

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