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
4
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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Fanciness
Comfortableness
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3445
Soft Luxury
Soft Simple
37
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245
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Brightness
Comfortableness
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Warm Soft
Cool Soft
5623
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Heaviness
Comfortableness
46
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Figure 6 Evaluation Difference between Japan and Malaysia
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JapaneseSample: Evaluation Score Area:
MalaysianJapaneseMalaysian
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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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