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Manchester School of Art
Manchester Metropolitan University
02-05 September 2019
International Association of Societies of
Design Research Conference 2019
DESIGN REVOLUTIONS
Less for more, but how & why? – Number of elements
as key determinant of visual complexity
Shin, Yooncheola; Joo, Jaewoob*
a Smart Experience Design Department, Graduate School of Techno Design, Kookmin University, Seoul, Korea
b College of Business Administration, Kookmin University, Seoul, Korea
* designmarketinglab@gmail.com
Although designers aim at “less for more” when developing a product, they struggle with how
to achieve simplicity and why making a product simple improves the commercial value of the
product. To answer the two questions, we performed one experimental study. In the study, we
searched for which of the six different types of lowering visual complexity is effective and
examined whether authenticity mediates the effect of visual complexity on commercial value.
Results show that three out of six types of lowering visual complexity (e.g., irregularity of
arrangement, amount of material, incongruity) deemed to be more commercial value. Results
also show that decreasing the amount of material is the only way to enhance authenticity,
which in turn increases the commercial value of the product.
Keywords: Visual complexity, Authenticity, Commercial value
1 Introduction
“Less for more” is a popular saying among designers. This design tendency is also evident in
the principles and philosophies of influential designers. It led the “less is more” movement in
architecture characterized by the works of Mies van der Rohe. It introduced “white space” in
advertisement originated from a famously simple IBM block logo designed by Paul Rand
(Pracejus, Olsen, Guinn, Olsen, & Guinn, 2006). This tendency also resulted in the
commercial success of the consumer electronics designed by Dieter Rams in Braun, who
introduced “good design is as little design as possible.” (Lovell, 2011). He argued that a
product is beautiful when it has a few basic geometric shapes with non-fussy colors. His
approach later inspired Jonathan Ive, who has designed a wide variety of highly popular
electronic products at Apple.
Designers have a consensus about what is simple. The common design style ‘simple’
corresponds to prior research that has demonstrated a general preference towards objects
and designs that are symmetric, unified, and have low complexity (Berlyne, 1970; Hekkert &
Leder, 2008; Hutchinson, 1998). Complexity is a design attribute that is used by designers
which are opposite (and therefore correlated) to the attribute simplicity (Blijlevens, Creusen,
& Schoormans, 2009).
However, package designers often struggle with how to achieve simplicity and are not fully
informed about why making a product simple improves commercial value in package design.
2
For instance, simplicity was identified as the appearance attributes that consumers in
general use to distinguish between different product appearances (Blijlevens et al., 2009).
Therefore, simplicity is related to a product’s competitiveness, which can lead to commercial
value. Most designers would agree that simplicity is a virtue in design. However, the nature
of this simplicity has yet to be clearly elucidated (Shelley, 2015). Also, most approaches and
methods aimed at reducing complexity in some way, but reducing design complexity is not
an easy task (Stolterman, 2008).
Therefore, this research has two purposes. Note that answering each purpose benefit
different groups of people. First, we aim to answer “How can we decrease visual
complexity?” Answering this question will benefit designers. In the past, designers have
achieved simplicity in many different ways. Some have done decreasing the amount of
embellishments in fashion (Cox & Cox, 2002) and others have done simplifying shapes in
car design (Lee, Jung, & Chu, 2015). In general, practical knowledge about decreasing
visual complexity in package design has not been established.
Second, we aim to answer “Why does decreasing visual complexity of a package design
improve the commercial value of the product?” Answering this question will benefit
managers. In the past, studies regarding how visual complexity affects commercial value of
the product were scarce. Therefore, practical knowledge about decreasing visual complexity
needs in-depth research.
In the prior literature, decreasing visual complexity has been found to be advantageous in
processing information (Reber & Schwarz, 2004). This metacognitive advantage is believed
to benefit commercial value, suggesting that decreasing visual complexity is rather a non-
cognitive advantage. In this research, we argue there is another cognitive reason why doing
so increases commercial value.
2 Theory
2.1 Visual complexity
Visual complexity is narrowly defined as the amount of detail or intricacy of lines in the
picture (Snodgrass & Vanderwart, 1980). A broader definition of visual complexity comes
from Berlyne, an experimental psychologist who investigates complexity, arousal, and
preference. According to his research (1958), there are six different types (ways) of
increasing or decreasing visual complexity.
• (VCA) Irregularity of arrangement: the elements are arranged in an irregular
geometrical pattern and irregularly scattered (Berlyne, 1958). For instance, an image
containing an irregular geometrical pattern is visually more complex than an image
with a regular geometric al pattern.
• (VCB) Amount of material: the amount of elements is arranged as independent visual
elements. For instance, an image containing more lines is visually more complex
than an image with fewer lines (Peckham, 1966).
• (VCC) Heterogeneity of elements: the same number of different elements in a similar
spatial arrangement (Berlyne, 1958). For instance, when a picture consists of a
circle, triangle, and square, it is visually more complex than a picture with multiple
circles only.
• (VCD) Irregularity of shape: is the nonsymmetrical shape arrangement. For instance,
nonsymmetrical shape is more complex than regularity of shape, regularity of contour
3
and symmetry. Regularity of contour and symmetry imply similarity of parts and
predictability of changes in curvature, all of which means high redundancy (Berlyne,
1958)
• (VCE) Incongruity: an unusual arrangement as a picture of a normal animal and a
picture of an incongruous animal, i.e., one with parts appropriate to different species
or with three heads (Berlyne, 1958). These are closely related to Gestalt
characteristics of a product. For instance, when a picture shows a bird's head with a
cat's body, it is visually more complex than a picture of either a bird or a cat (Berlyne,
Craw, Salapatek, & Lewis, 1963).
• (VCF) Incongruous juxtaposition: this arrangement bears the same material but with
the halves of the two objects incongruously juxtaposed (Berlyne, 1958). For instance,
when the halves of flowers and the halves of airplane incongruously juxtaposed, it is
visually more complex than when either the flowers or the airplanes are placed in an
isolated way.
Much prior research has shown that visual complexity influences the psychology of people.
When it increases, people increase their attention, interest, and looking time (Eisenman,
1966; Geissler, Zinkhan, & Watson, 2006; Morrison & Dainoff, 1972; Peckham, 1966). For
instance, consumers respond more favorably when they watch moderately complex
websites than simple or highly complex websites (Geissler et al., 2006). Consumers look at
visually complex advertising for longer periods of time (Morrison & Dainoff, 1972). Indeed,
visual complexity critically influences people’s first impressions, emotions, and aesthetic
preferences concerning the stimuli (Berlyne, 1970; Cox & Cox, 2002). For instance, (Cox &
Cox, 2002) showed consumers' preferences for visually complex product designs increase
with repeated exposures whereas their preferences for visually simple product designs do
not. Berlyne (1971) claims that the visual complexity of a product determines its arousal
potential, which determines people’s arousal response to it. Especially minimalistic package
design will positively affect the product’s perceived quality and premium perceptions. An
example comes from the Sourcy Pure Blue bottle. This bottle is minimalistic and thus
premium because it has a basic shape and does not feature any superfluous visuals or text.
In contrast, the Aquapax package and the complex shape of Tŷ Nant associated the
extensive illustrations and considered less premium water brands (Mugge, Massink, Hultink,
& Berg-, 2015).
Differently from what has been discussed in the prior research, based partially on Geissler et
al. (2006), we propose that decreasing visual complexity of a product increases the
commercial value of the product.
• H1: If the visual complexity of a product decreases, its commercial value will
increase.
2.2 Authenticity
‘Authentic’ implies that the product design refers to a historical, original source, and has
been created within that particular context (Snelders, Mugge, & Huinink, 2019). Authenticity
is widely acknowledged as a critical dimension for consumers that can be assessed along
dimensions such as product styling, connections to a particular location, and firm values
(Newman & Dhar, 2014). For example, the Gem paper clip - firstly introduced in the early
4
1870s - is nowadays considered a classic because it is the oldest and the most practical
paper clip model, setting the world standard from the very beginning (Snelders et al., 2019).
Authenticity is an important variable in contemporary marketing (Belk, Costa, & Costa, 1998;
Holt, 1997; Kozinets, 2001) and has been garnering increasing attention in the literature
(Ilicic & Webster, 2014). As a result, different definitions referring to different types of
authenticity have emerged (Valsesia, Nunes, & Ordanini, 2016).
Interestingly, authenticity widely appears in the marketing literature, but only a few design
researchers have investigated it. For instance, in craft design, the knowledge of the touch of
the human hand makes the product more valuable than a machine-made one because of its
authenticity (Kälviäinen, 2000). In textile design, It is considered to render textile design
relevant and is a determinant of the level of its craftsmanship (Valentine, Ballie, Robertson,
Bletcher, & Stevenson, 2017).
In the present research, we claim that when the visual complexity of a product decreases,
the authenticity of the product increases. Our claim is supported by two cases. First,
consider the introduction of the original Bondi iMac in 1998. The new iMac was to be the
design that re-introduced the public to Apple design, as Steve Jobs envisioned it. It turned
out, however, that the design of the Bondi iMac contained an unwelcome surprise for him, in
the form of a CD drive with a loading tray (Shelley, 2015). For the user, a CD drive with a
tray is more complex than a CD drive with a slot. The tray has a button that the user must
push in order to unlatch it. Once the tray is unlatched, the user pulls it out, places a CD in it
and pushes it to close. By contrast, the CD slot has no tray and no button. From the user’s
perspective, it is simply a hole into which CDs may be pushed and from which they may be
pulled upon ejection. So, the slot drive is more minimal and thus better than the tray
(Shelley, 2015). Second, for a company like Bang & Olufsen, heritage and craftsmanship are
vital parts of the brand – even such traits are concepts often perceived concerning
authenticity (Sommer, 2012). In order to enhance the authenticity, Bang & Olufsen’s focus
on simplicity and style as a brand is something that can be seen in everything they do. While
B&O believes that beauty is important alongside function, they do not over-work their
designs. Instead, they take a minimalist approach (Hodgson, 2017).
In the prior research decreasing visual complexity increases processing fluency (Reber &
Schwarz, 2004). The authors proposed that processing fluency, the speed, and ease at
which one processes information, was positively related to people’s aesthetic judgment of
objects. When visual complexity increases, the salience of the source of perceptual fluency
decreases, enhancing the misattribution of fluency to beauty. However, further increases in
complexity will eventually reduce processing fluency, leading to a decrease in perceived
beauty (Reber & Schwarz, 2004). As a result, a decrease in visual complexity allows for
easy processing of visual information, which results in high preference.
In contrast, we propose that visual complexity influences the authenticity of the product,
which enhances its commercial value. Put simply, differently from the prior research
suggesting that people like a visually simple product because visual simplicity relieves the
cognitive burden; we argue that people like a visually simple product because, they think, it
is perceived to be authentic.
5
• H2: Authenticity mediates the relationship between visual complexity and commercial
value.
Figure 1: Research framework
3 Study
3.1 Objective
We tested hypotheses 1 and 2. We decreased the visual complexity of an eyeshadow
palette package design in multiple ways to examine which way increases the commercial
value of the product (H1). We also examined whether decreasing visual complexity of an
eyeshadow palette package design increases its commercial value through its enhanced
authenticity (H2).
3.2 Design
In this study, we employed a 7 (0 vs. VCA vs. VCB vs. VCC vs. VCD vs. VCE vs. VCF)
between-subjects design.
3.3 Stimuli
We selected an eyeshadow palette as a baseline stimulus and then manipulated its visual
complexity in six different ways. The product of the Korean cosmetic company ARITAUM -
eye shadow palette (=0) - was chosen because it met all the conditions of visual complexity
(Berlyne, 1958), and also presents several visual elements. Furthermore, if Korean
cosmetics are used as stimulus, it can be applied directly to the sensitive Korean cosmetics
market. A trained designer created digital 2D models of eyeshadow palette package and
manipulated the shape of the stimuli following the six different types of lower visual
complexity. The brand name was removed to eliminate the brand effect (see Table 1).
Table 1: Six types, manipulations, and stimuli of visual complexity
Types
Type of visual
complexity based
on Berlyne (1958)
Manipulation Stimuli
0
-
-
VCA
Compared with the control, the
manipulated product presents the
elements watermelon slices and seeds
arranged in a regular geometrical
pattern
6
VCB
Compared with the control, the
manipulated product removed some
watermelon slices and seeds at once
VCC
Compared with the control, the
manipulated product presents the
same number of identical elements
(watermelon slices and seeds) in a
similar spatial arrangement
VCD
Compared with the control, the
manipulated product presents
watermelon slices and seeds with
regularity of shape, regularity of
contour and symmetry.
VCE
Compared with the control, the
manipulated product presents a
congruous picture combining
watermelon slices and seeds.
VCF
Compared with the control, the
manipulated product presents
watermelon slices and seeds placed in
an isolated way
3.4 Procedure
This experiment was conducted for 14 days from January 10 to January 24, 2019, at a
university located in Seoul, Korea. We recruited 254 female students. Since male students
rarely use eye shadows, we avoid them. We approached them using SNS advertisements.
We used Qualtrics to design an online questionnaire and collect responses. We wrote
questions in both English and Korean to prevent misunderstanding. Participants received
one of the seven questionnaires randomly (0 vs. VCA vs. VCB vs. VCC vs. VCD vs. VCE vs.
VCF). Note that the specifications of the eye shadow palette were provided equally to the
whole participants.
3.5 Measure
To test whether our manipulations were successful, we measured perceived complexity of
the product as well as asked a specific question for each product. First, perceived complexity
was measured by two questions on 7-point scales anchored by complicated-simple (1 =
7
complicated, 7 = simple) and simple-complex (reverse coded) (1 = simple, 7 = complex)
(Cox & Cox, 2002): ‘1. How simple does this product look like?; 2. How complex does this
product look like?.’ Second, we asked a specific question in each condition. After realizing
the questionnaire (Cox, 2002) was insufficient to measure the six conditions, we developed
based on Berlyne (1958). It was measured on 7-point semantic differential scales anchored
by few-a lot (1 = few, 7 = a lot), regular-irregular (1 = regular, 7 = irregular), homogeneous-
heterogeneous (1 = homogeneous, 7 = heterogeneous), and symmetrical-asymmetrical (1 =
symmetrical, 7 = a symmetrical) (Peckham, 1966): ‘1. How many design elements does this
product have?; 2. Are the design elements of this product irregular (not even or balanced in
shape or arrangement)?; 3. Are the design elements of this product heterogeneous (diverse
in character or content)?; 4. Are the design elements of this product asymmetrical (having
parts or aspects which are not equal or equivalent)?’ The coefficient alpha for the
measurement scale was .78.
The authenticity was measured by one question on one 9-point semantic differential scale
anchored by inauthentic-authentic (1 = inauthentic, 9 = authentic) (Newman & Dhar, 2014):
‘1. When you think about what it means to be truly authentic product, you would have to say
that this product is…’
Finally, the commercial value consists of the sum of purchase intention and willingness to
pay. Purchase intention was measured by three questions on 7-point scales (1 = strongly
disagree, 7 = strongly agree) (Putrevu & Lord, 2014): ‘1. It is very likely that I will buy this
product; 2. I will purchase this product the next time I need a product; 3. I will definitely try
this product.’ Regarding willingness to pay, it was measured by two questions on a 9-point
scale anchored (1 = would not pay a premium, 9 = would pay a premium) (Newman & Dhar,
2014): ‘1. How much would you be willing to pay for this particular product relative to the
average product?; 2. How likely would you be to purchase this particular product?’ The
coefficient alpha for both measurement scales was .87.
4 Results
4.1 Manipulation check
Multiple independent t-tests were performed in order to test whether visual complexity was
manipulated as intended. Data suggest that five products (VCA, VCB, VCC, VCD, and VCE)
were successfully manipulated and one product (VCF) failed to be manipulated. More
specifically, participants responded that when the product has a regular arrangement
(M0=4.640 vs MvcA=2.707, t(52)=4.011, p<0.01), when the product has fewer materials
(M0=4.640 vs MvcB=2.260, t(48)=5.260, p<0.01), when the product has homogeneous
elements (M0=4.640 vs MvcC=2.760, t(48)=3.788, p<0.01), when the product has a regularity
shape (M0=4.640 vs MvcD =2.518, t(51)=4.479, p<0.01), and when the product has a
congruent element (M0=4.640 vs MvcE =2.900, t(48)=3.801, p<0.01), it was considered
visually less complex than the original product which was not manipulated. However, when
the visual elements are congruously juxtaposed, doing so failed to decrease perceived visual
complexity.
8
Figure 2: Mean scores of visual complexity
4.2 Commercial value
Independent t-tests were performed in order to test H1. Data suggest that three products
(VCA, VCB, and VCE) were significantly higher than control. More specifically, participants
responded that when the product has a regular arrangement (M0 =2.952 vs. MvcA = 4.427,
t(52) = 4.351, p<0.01), when the product has fewer materials (M0=2.952 vs. MvcB= 4.440,
t(48)= 4.430, p<0.01), when the product has a congruent element (M0=2.952 vs MvcE =3.984,
t(48)= 3.296, p<0.05), and when there are three types of lower visual complexity (VCA, VCB,
and VCE) it increased the commercial value of the product whereas the other three types
(VCC, VCD, and VCF) failed to increase its commercial value.
Figure 3: Mean scores of commercial value
4.3 Authenticity
Independent t-tests were performed in order to compare the difference in the mean scores of
authenticity. Data suggest that three products (VCA, VCB, VCE) were significantly higher than
control. More specifically, participants responded that when the product has a regular
arrangement (M0 = 3.800 vs. MvcA = 5.172, t(52) = 2.959, p<0.01), when the product has
fewer materials (M0=3.800 vs. MvcB=5.240, t(52)=2.586, p<0.01), and when the product has
a congruent element (M0=3.800 vs. MvcE =4.880, t(48)=2.247, p<0.05), the three types of
lower visual complexity (VCA, VCB, and VCE) increased the authenticity of the product
whereas the other three types (VCC, VCD, and VCF) failed to increase its authenticity.
4.640
2.707 2.260
2.760 2.518 2.900
3.720
1
2
3
4
5
6
7
Control Irregularity of
arrangement
Amount of
material
Heterogeneity
of elements
Irregularity of
shape
Incongruity Incongruous
juxtaposition
Visual complexity(1
-7)
2.952
4.427 4.440
3.552 3.243 3.984
2.928
0
1
2
3
4
5
6
7
8
9
Control Irregularity of
arrangement
Amount of
material
Heterogeneity
of elements
Irregularity of
shape
Incongruity Incongruous
juxtaposition
Commercial value (1
-9)
9
Figure 4: Mean scores of authenticity
4.4 Mediation analysis
To test H2, data were analyzed using Hayes’ (2013) PROCESS Model 4 for simple
mediation with 5,000 bootstrap samples and a bias-corrected 95% confidence interval. The
analyses were performed for commercial value as the dependent variable, with visual
complexity as the independent variable and authenticity as the mediation.
As a result of the analysis, we confirmed that only the VCB is mediated through authenticity.
It can be judged statistically significant when 0 does not enter the confidence interval at 95%
level. The direct effect of visual complexity on commercial value was -.382, which was not
statistically significant. The indirect effect of visual complexity on commercial value was
-.238, which is statistically significant. The effect on the visual complexity to commercial
value is fully mediated by the authenticity (see Table 2).
Table 2:
Total effect, direct effect, and indirect effect of visual complexity on commercial value
.
Total effect visual complexity on commercial value
effect
SE
LLCI
ULCI
t
p
-.619
.230
-1.096
-.142
2.685
.013*
Direct effect visual complexity on commercial value
effect
SE
LLCI
ULCI
t
p
-.382
.185
-.766
.003
2.060
.051
Indirect effect visual complexity on commercial value
effect
Boot SE
Boot LLCI
Boot ULCI
-.238
.130
-.548
-.032
5 Findings
Our experiment produced in total three findings. First, decreasing visual complexity
differently results in different degrees of commercial impacts. For instance, five types of
lower visual complexity (VCA, VCB, VCC, VCD, and VCE) could decrease the perceived visual
complexity whereas one type failed to do so (see Table 3).
Second, the effect of visual complexity on commercial value depended on the type of visual
complexity. For instance, three types of lower visual complexity (VCA, VCB, and VCE)
increased the commercial value of the product whereas the other three types (VCC, VCD,
and VCF) failed to increase its commercial value. Regarding the three types of lower visual
complexity (VCA, VCB, and VCE), because of their simple design, we conjecture people are
more familiar than those other three types (VCC, VCD, and VCF). This implies that three types
3.800
5.172 5.240 4.640 4.750 4.880 4.280
1
2
3
4
5
6
7
8
9
Control Irregularity of
arrangement
Amount of
material
Heterogeneity
of elements
Irregularity of
shape
Incongruity Incongruous
juxtaposition
Authenticity (1
-9)
10
of lower visual complexity (VCA, VCB, and VCE) can improve the commercial value
differently.
Third, the results of the mediating effect of authenticity provide important insights into the
role of authenticity in the effect of visual complexity on commercial value. They show that
VCB is the only way to decrease visual complexity, which increases commercial value
through enhanced authenticity
Table 3:
Statistically significant visual complexity type by variable
Type
Control
VCA
VCB
VCC
VCD
VCE
VCF
Stimuli
IV
Visual complexity
4.640
2.707**
2.260**
2.760**
2.518**
2.900**
3.720
DV
Commercial value
2.952
4.427**
4.440**
3.552
3.243
3.984*
2.928
MeV
Authenticity
3.800
5.172**
5.240**
4.640
4.750
4.880*
4.280
*p< 0.05 **p< 0.01
6 Discussion
In conclusion, this study has academic significance showing that visual complexity (high vs.
low) affects commercial value through authenticity, which has not been actively discussed in
the existing visual complexity studies. Although authenticity appears in some marketing
research, it is interesting that in this study we have found that visual complexity can affect
authenticity.
The results of this study support our hypotheses. As expected, package design in the high
level of visual complexity is less commercial than package design in the low level of visual
complexity (H1). Moreover, a mediation analysis shows that this effect of visual complexity
on commercial value is mediated by authenticity (H2).
7 Theoretical implications
In this study, we showed that visual complexity influences the authenticity of the product,
which enhances its commercial value. Our findings differ from the prior research arguing that
aesthetic pleasure depends on the perceivers’ processing dynamics (Reber et al., 2004).
Prior research suggests that cognitive load caused by a lot of information leads to a
decrease in processing fluency (Reber & Schwarz, 2004). High cognitive load and low
processing fluency decrease preferences for products. Differently from the prior research
suggesting that people like a visually simple product because it relieves cognitive burden, we
demonstrated that people like a visually simple product (VCB - fewer materials) because it is
perceived to be authentic. In summary (Figure 5), prior studies suggest a metacognitive
mechanism in which lowered visual complexity positively influences observers’ process
fluency. But this study suggests a cognitive mechanism that lowers visual complexity,
positively influences observers’ authenticity.
This research is meaningful because it has further proposed cognitive mechanisms in
relation to product preferences. In other words, although prior studies say that the
preference for products depends on the observer's processing fluency, the product's
authenticity is also academically meaningful, and it can be considered an important
mediator.
11
Figure 5: Compared metacognitive and cognitive mechanisms
8 Practical implications
Our findings have practical implications for answering how and why decreasing visual
complexity.
First, this research provides practical knowledge helping designers in developing a visual
design strategy for their products. This study verified that consumers respond differently to
visual complexity in a package design depending on their types. This implies that all types of
lower visual complexity can be appealing to consumers differently, and the six types of lower
visual complexity (Berlyne, 1958) should be applied differently depending on the
circumstances.
Designers have a consensus about what is simple. But they rely on their senses for their
simple designs. This research suggests six different types of lower visual complexity and
how to decrease it, and quantitatively provides them with what is effective. Therefore,
designers can use separately effective methods for decreasing visual complexity.
For instance, designers and managers need to pay attention to irregular arrangement,
amount of material and incongruity to improve commercial value. Furthermore, this study
verified that consumers respond differently to visual complexity in a package design
depending on their level of authenticity. Therefore, designers need to consider the
importance of authenticity and to do this; they consider reducing the amount of visual
material.
Second, this study provides practical knowledge helping managers in developing a
marketing strategy. In this study, we have extracted an effective way of using lower visual
complexity. Considering this, managers need to attract consumers’ attention by using
appropriate visual complexity based on irregular arrangement, amount of material, and
incongruity. Thereby, drawing an arousal response from consumers and encouraging them
to experience excitement and to focus on the product. Furthermore, this study verified that
consumers respond differently to visual complexity in a cosmetic package design depending
on their level of authenticity. Those with authenticity - cosmetic package design with low
visual complexity - were found to have greater commercial value than those with high visual
complexity.
9 Research limitations
This study has several limitations, but if we overcome these limitations step by step, we can
expect interesting future research.
12
First, cosmetics vary in types, but in this study, it was difficult to deal with various
characteristics of cosmetics by limiting experimental stimulus to ARITAUM's eyeshadow
pallet. For example, even if it is the same cosmetic line, the commercial value can be
affected differently depending on the product type. In future research, we will need to make
use of a variety of product line to make more comprehensive research.
Second, the results of this study have demographic limitations. The study participants were
limited to female students. Because male students rarely use eye shadows, we avoid male
participants. If we conduct further research on more diverse groups, we can draw more
generalized conclusions theoretically and practically.
Third, this study is expected to be an important variable in how sensitive it is the design of a
product. In other words, if participants have a major in design or related people, they can
increase their authenticity because it is accepted positively when they see a simple product.
In additional experiments, participants should review how familiar they are with the field of
design.
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About the Authors:
Shin, Yooncheol: Yooncheol is a graduate student at the Graduate School
of Techno Design, Kookmin University. His research area focuses on how
design influences marketing, particularly related to new product development.
Joo, Jaewoo: Jaewoo teaches and writes in the areas of design thinking,
new product development, and behavioral economics. He is an associate
professor of marketing and participating professor of experience design at
Kookmin University.
Acknowledgement: This paper has been conducted with the support
of the "Design Engineering Postgraduate Schools" program, a R&D
project initiated by the Ministry of Trade, Industry and Energy of the
Republic of Korea. (N0001436)
