Noh et al 2016

International Journal of Software Engineering and Its Applications
Vol. 10, No. 2 (2016), pp. 105-116
http://dx.doi.org/10.14257/ijseia.2016.10.2.09
ISSN: 1738-9984 IJSEIA
Copyright ⓒ 2016 SERSC
Effect of Smartphone Brand Satisfaction on the Purchase of Other
Smart Devices of the Same Brand
Minyoung Noh1
, Myungsin Chae2
, Byungtae Lee3
and Moonsoo Yoon2
1
SK (Corporation) Jong-ro, Jongno-gu, Seoul, 03188, Republic of Korea
2
Seoul Venture University, 405 Bongensa-ro Samsung-dong, Kangnam-gu, Seoul,
Korea
3
85 KAIST, Hoegiro, Dongdaemun-gu, Seoul, Korea
1
nohmy@business.kaist.edu, 2
mlee31@naver.com, 3
btlee@business.kaist.ac.kr,
4
msyoon@wmit.or.kr
Abstract
This research focuses on the effect of brand perceptions formed through the usage of a
smartphone on user satisfaction and on subsequent purchasing decisions for other smart
devices of the same brand, using the theoretical background of the Expectation-
Confirmation Model in IT. This study showed that the brand expectation confirmation
before and after using a smartphone affected brand user experiences (perceived
usefulness, perceived playfulness, and perceived aesthetics) significantly.
This study is meaningful in that it has defined the perceived playfulness and perceived
aesthetics in the existing ECM-IT as ‘user brand experience’ factors, and confirmed the
relevant correlations. Also, the confirmation that smartphone usage experience can be
fully transferred a user’s intention to purchase other smart devices is what differentiates
this study with other studies. The research results show that the user’s playfulness and
aesthetics perception formed through smartphone brand usage experience affects both the
brand usage satisfaction and the purchase intention of portable and non-portable devices.
Keywords: Brand user experience, smart device, smartphone, ECM, SEM, purchasing
intention, aesthetic, mediating effect
1. Introduction
Smartphone market growth has already begun to stagnate, so manufacturers have
released or are trying to launch new types of smart devices to develop new avenues for
growth. IDC [1] predicted that potential wearable device shipments would explode by
more than 500% in 2015, i.e., 25.7 million units from 4.2 million in 2014.
Thus, it is important for smart devices not to be separated from smartphones, but rather
smart devices should be an expansion of the existing ecosystem of the platform and the
services formed through smartphones.
Consumers nowadays not only consider the device itself, but also take many other
diverse elements, such as the image of the brand, into consideration when choosing a
device [2]. Thus, modern consumers try to obtain more than just the value of the device.
They would even pay for the emotions and experiences gained through the usage of the
device.
That the consumer‟s brand usage experience and usage satisfaction has a meaningful
effect on the reuse and repurchase of the device has been proved through many previous
studies [3] [4]. These have only confirmed the usage satisfaction and the intention of
reuse of the smartphone itself. Yet, studies confirming the decision changing occurred
through the experience of a certain brand during the the usage of other devices of the
*Corresponding Author

Vol. 10, No. 2 (2016)
106 Copyright ⓒ 2016 SERSC
brand are not enough. Thus, the purpose of this study is to find out what kind of effects
the brand user experiences, formed by the usage of smartphones, have on the purchase of
a device of the same brand.
2. Theoretical Background
The purchase of a smart device seems to take the Post-Adaption style which is
influenced by the experience of the owner‟s smartphone usage. The most well-known
Post-Adaption Theory related to IT devices or Information Systems is the Expectation-
Confirmation Model-IT (ECM-IT).
Bhattacherjee [5] suggested through the ECM-IT that a product‟s function (usefulness)
is significant; however, a consumer‟s satisfaction can be determined not only by function
(usefulness) but also by the confirmation of expectations before purchase and user
experience after purchase (See Figure1)
Figure 1. ECM-IT
However, The ECM-IT is limited to only being able to explain the effect on the
acceptance decision factor of the information system through perceived usefulness. As the
information system becomes more individualized and diverse, the elements affecting the
user experience have become diverse; factors affecting perceived decision came to
include more than usefulness. [6], pointed out that the current ECM-IT is limited because
it only focuses on the usefulness. It added other new elements such as the product
consumption value, perceived playfulness, and subjective standards, and tried to figure
out the continuance intention based on the usage of smartphones. It stated that smartphone
expectation-satisfaction affects all aspects of the value of the products.
[7] claimed that it had added service quality and dedication to the factors of the ECM-
IT, in order to measure the effect of user experience on the consumer‟s intention to
continue using a particular smartphone. Among other factors, the quality of the device
affected the user experience of smartphones greatly as well as the intention of the
continuous usage of smartphones. [8] tried to predict the continuance intention of the
usage of smartphones by adding two factors, perceived playfulness and behavioral
loyalty, to the Expectation-Confirmation Model. This study showed that perceived
playfulness had a meaningful effect on the satisfaction and the continuance usage
intention.
However, smart devices other than smartphones have not yet passed Chasm [9] and
because they are only in the spreading phase, there are not many studies on the intention
to purchase or the continuance intention itself. [10] stated that in a study on the purchase
and intention to continuously use a wearable wrist healthcare device, perceived usefulness

Vol. 10, No. 2 (2016)
Copyright ⓒ 2016 SERSC 107
and perceived ease of use have a meaningful effect on the purchase and continuance
usage intention‟.
3. Research Model and Methodology
3.1. Research Model
This study sets up the conceptual research model (see Figure 2) based on the IT
Continuance Model. The ECM-IT has been used in previous studies to examine the
continuous use of smart devices, but it has limitations in explaining the trend of consumer
value in modern society because it only focuses on perceived usefulness. As the personal
computer (PC) and smartphones have emerged as a means of the personalization of IT
devices, previous studies found that emotional characteristics like playfulness [11, 12] and
aesthetic elements such as design are important factors for consumers to consider when
deciding whether to continuously use IT products [13, 14].
As the individualization of IT devices has rapidly taken place due to the appearance of
PCs and smartphones, many studies that have included playfulness characteristics, such as
perceived enjoyment, as an IT device acceptance factor [15, 16] insisted that in studies
related to the hedonic information system, perceived playfulness was a much more
important factor than usefulness.
[17] considered aesthetics also as an important factor for technology, and aesthetics
that could make the consumer feel „beauty‟ through it, could affect the consumer‟s
intention to purchase through satisfaction [18, 19] claimed that „design‟ was an important
factor for satisfying the user‟s emotion, and was a factor in the selection process of the
product. Recently, [20] stated that according to research studies by the LG Economic
Institute, since 2012, the factor that affected a consumer‟s decision to purchase
smartphone the most was „design‟.
By referring to previous studies, this study has established the research model as shown
Figure 2, which includes not only the user brand experience, but also usefulness,
playfulness, and aesthetics. The hypotheses based on the model, are suggested in Table 1.
Figure 2. Research Model

Vol. 10, No. 2 (2016)
Table 1. Research Hypothesis
H1 The expectation-confirmation of a smartphone brand will have a positive
relationship with the user-brand experience.
H1-1 Users with a high expectation-confirmation will have a positive relationship with
the perception of perceived usefulness regarding brand usage experience.
the perception of perceived playfulness regarding brand usage experience.
the perception of perceived aesthetics regarding brand usage experience.
H2 The smartphone brand usage experience of a user will have a positive relationship
with the brand usage satisfaction.
H2-1 Perceived usefulness regarding the brand usage experience will have a positive
relationship with the usage satisfaction.
H2-2 Perceived playfulness regarding the brand usage experience will have a positive
H2-3 Perceived aesthetics regarding the brand usage experience will have a positive
H3 Smartphone brand usage satisfaction will have a positive relationship with the
purchase intention of another smart device of that brand.
H3-1 Smartphone brand usage satisfaction will have a positive relationship with the
purchase intention of a portable device of that brand.
H3-2 Smartphone brand usage satisfaction will will have a positive relationship with the
purchase intention of a non-portable device of that brand.
H4 The Expectation-Confirmation of a smartphone brand will have a positive
relationship with the brand usage satisfaction.
3.2.Measurement
There are a total of 7 constructs in this study, and 28 questions were developed to
measure the constructs. The items for measurement were adopted from previous studies
and reworded to suit the context of the current study. Each item was measured with a 5
point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree).
3.3. Data Collection and Analysis Method
The survey was conducted with smartphone users, and it was collected from April 22,
2015 to April 30, 2015. Of 613 respondents, a total of 583 respondents were eligible for
analysis using SPSS 22.0 and AMOS 22.0.
4. Empirical Analysis
4.1. Demographic Characteristics of the Sample
The characteristics of the respondents by demographic variables showed that there are
583 respondents in total; and there are more females (315 respondents, 54.0%) than males
(268, 46.0%), and the number of respondents in their 20s, 30s, and 40s accounted for 173
(29.7%), 167 (28.6) and 123 (21.1%) respectively. (see Table 2) The answers to what are
the key considerations when purchasing smartphone were functionality(36.7%),
manufacturer and brand(19.6%), price(16.5%), design(15.4%) as shown in Table 3.

Vol. 10, No. 2 (2016)
Table 2. Demographic Variables of the Respondents
Number of Respondents (N=583) %
Sex
male 268 46.0
female 315 54.0
Age
10~19 3 0.5
20~29 173 29.7
30~39 167 28.6
40~49 123 21.1
50 and over 50 117 20.1
Income Level (Korean Won; during survey period, 1,083 KRW= 1 USD)
Below 2,000,000 177 30.4
2,000,001~4,000,000 234 40.1
4,000,001~6,000,000 118 20.2
6,000,001~8,000,000 27 4.6
Over 8,000,001 27 4.5
Average time spent per day on smartphone (minutes)
less than 10 19 3.3
10~30 46 7.9
31~60 111 19.0
61~120 172 29.5
Over 121 235 40.3
Table 3. The Key Considerations when Purchasing Smartphone
Number of Respondents (N=583) %
Functionality 214 36.7
Manufacturer / Brand 114 19.6
Price 96 16.5
Design 90 15.4
Convenience of After Service 21 3.6
Telecommunication Company 16 2.7
Durability 13 2.2
Fashion / Trend 13 2.2
Recommendation by others 6 1.0
4.2. Measurement Model Estimation and Analysis
A confirmatory factor analysis was performed to estimate the measurement model.
First, the fit of the measurement model was estimated in Table 4. The results for various
indices of goodness-of-fit of the measurement model are summarized at the bottom of
Table 4. The results show that the measurement model was adequate. Second, the
reliability of all constructs were tested by Cronbach‟s α. All measurement scales in Table
4 showed relatively higher than 0.70 for all measure, which is the minimum alpha value
for good internal reliability on all measures [21] To validate our measurement model, two
types of validity were assessed: convergent validity, and discriminant validity. We
assessed convergent validity by examining 1) factor loading, 2) composite reliability and
3)AVE (average variance extracted). Factor loading of all indicators should exceed 0.6
and be significant [22]. Table 4 exhibits the weights and loadings of the measures in our
research. It shows that all measures are significant on their path loadings at the level of
0.01. For composite reliability 0.7 is a recommended value [23]. As shown in Table 4, our

Vol. 10, No. 2 (2016)
composite reliability values are over 0.836. Third, for AVE, a score of 0.5 is a cut-off
value [24]. Table 4 shows that AVEs by our measures are over 0.509 which are above the
acceptability value. Thus, the convergent validity of the measurement model was
confirmed.
Table 4. Measurement Model Estimation Results
S.E C.R
Construct
Reliability
AVE Cronbach’s α
EC 1
EC 2
EC 3
.857
.889
.818
.356
.308
.480
29.001
25.195
.890 .673 .921
EC 4 .884 .303 28.711
Usefulness 1
Usefulness 2
Usefulness 3
.629
.760
.889
.949
.563
.242
17.032
22.135
28.683 870 .576 .890
Usefulness 4 .845 .321 26.265
Usefulness 5 .863 .295
Playfulness 1
Playfulness 2
Playfulness 3
.800
.850
.673
.552
.383
.840
21.270
22.812
17.051
.805 .509 .892
Playfulness 4 .799 .591
Aesthetics 1
Aesthetics 2
Aesthetics 3
.776
.872
.768
.532
.325
.640
21.452
22.539
21.107
.833 .556 .861
Aesthetics 4 .812 .599
Satisfaction 1
Satisfaction 2
Satisfaction 3
.821
.856
.734
.516
.381
1.240
26.149
28.216
21.641 .855 .543 .917
Satisfaction 4 .870 .440 29.026
Satisfaction 5 .874 .340
Portable 1
Portable 2
Portable 3
Portable 4
Portable5
.769
.763
.854
.864
816
.663
.536
.625
.704
.705
21.416
21.762
24.807
29.153
.836 .506 .910
Non- Portable 1
Non- Portable 2
Non- Portable 3
Non- Portable 4
Non- Portable 5
.814
.808
.837
.927
.888
.753
.956
.771
.323
.485
27.086
26.383
28.915
35.248
.847 .527 .932
Model Fit
Χ2= 1018.08 (P=.000) ( p>.05), Χ2
/df=2.514 (2-3), GFI=.900 (>
0.9), AGFI=..866 (>0.9), IFI=.964 (>0.9), TLI=0958 ( > 0.9),
CFI=0964 (> 0.9) , RMSEA =.51(< 0.8)
Note.
EC = Expectation Confirmation
The number inside ( ) each index of Model Fit is the recommended cutoff value
To verify the discriminant validity of we looked at the square root of the AVE as
recommended by [25]. As Table 5 shows, the square root of the average variance
extracted for each construct is greater than the levels of correlations involving the
construct. This means that each construct shares larger variance with its own measures

Vol. 10, No. 2 (2016)
than with other measures. The result confirms the discriminant validity of the
measurement model. In addition to validity assessment, we also checked for
multicollinearity due to the relatively high correlations among some variables (e.g., a
correlation of 0.638 between Playfulness and Aesthetics). The resultant variance inflation
factor (VIF) values for all of the constructs are acceptable (i.e., between 1.112 and 1.432).
Table 5. Discriminant Validity Estimation
Variables 1 2 3 4 5 6 7
1. Expectation
Confirmation
(0.821)
2. Usefulness .666 (.760)
3. Playfulness .672 .642 (.713)
4. Aesthetics .667 .689 .638 (.746)
5. Satisfaction .605 .671 .609 .638 (.737)
6. Portable .585 .377 .581 .587 .682 (.711)
7.Non-Portable .430 .273 .493 .422 .505 .603 (.726)
Note. ( ): square root data of AVE of each variable
4.3. Structural Equation Model Estimation and Hypothesis Testing
The structure equation model was used for hypothesis testing. From Table 4 the
structural model shows an adequate fit as most indices showed passed cut-off values. All
the hypothesized paths were significant except for the path between perceived usefulness
and brand satisfaction at the 0.05 significance level. (see Table 6.).
Table 6. Hypothesis Model Testing Results
Hypothesi
s Path of Model Coefficient t-value Result
H 1-1 brand expectation confirmation
→ perceived usefulness 0.722 19.085** accept
→ perceived playfulness 0.621 15.493** accept
→ perceived aesthetics 0.805 17.656** accept
H 2-1 usefulness→ brand satisfaction 0.063 -1.372 reject
H 2-2 playfulness→ brand satisfaction 0.286 3.842** accept
H 2-3 aesthetics
→ brand satisfaction 0.329 5.845** accept
H 3-1 brand satisfaction
→ portable purchase intention 0.505 4.400** accept
H 3-2 brand satisfaction
→ non-portable purchase intention 0.355 2.991** accept
H 4 brand expectation confirmation
→ brand satisfaction 0.550 8.519** accept
Model Fit
Χ2= 932.683 (P=.000) ( p>0.05), Χ2
/df=2.343 (2-3), GFI=0.908 (> 0.9),
AGFI=0..878 (>0.9), IFI=0.969 (>0.9), TLI=0.961 ( > 0.9),
CFI=0.969 (> 0.9) , RMSEA =0.48 (< 0.8)
Note. **: p<0.01, *: p<0.05
The number inside ( ) each index of Model Fit is the recommended cutoff value

Vol. 10, No. 2 (2016)
5. Conclusion
5.1. Research Summary and Discussions
According to the results of this research, the Expectation-Confirmation, which shows
the difference in the consumer‟s thoughts before and after the usage of a brand, had a
meaningful effect on the brand usage experience (perceived usefulness, perceived
playfulness, and perceived aesthetics). Yet, among the types of brand usage experience,
„perceived usefulness‟ did not have a meaningful effect on the user‟s satisfaction;
„perceived playfulness‟ and „perceived aesthetics‟ had a meaningful effect on user brand
usage satisfaction.
This study found that perceived usefulness does not have an impact on brand
satisfaction; this implies that functionality and performance are not key differentiation
factors in the mature smartphone market. Meeting user satisfaction through functionality
is difficult in the market in the maturity phase because the speed of technology
development and user IT skills do not match [26]. It is shown that the advancement in
device technology and the speed of its adaptation do not match the user‟s actual
experience. In a fully-grown market such as the market for smartphones, factors other
than the supplement of new features and advancement in functions are necessary for
improving consumer satisfaction.
Currently smartphones have been standardized in an upward direction in terms of
functionality. Thus, usefulness no longer plays a role as a differentiation factor [27]. The
study also suggests that user satisfaction in a matured market like the smartphone market
may be enhanced by focusing on the senses and emotions or stimulating perceived
playfulness and aesthetics.
This study is meaningful in that it has defined the perceived playfulness and perceived
aesthetics in the existing ECM-IT as „user brand experience‟ factors, and confirmed the
relevant correlations. Also, the confirmation that smartphone usage experience can be
fully transferred a user‟s intention to purchase other smart devices is what differentiates
this study with other studies. The research results show that the user‟s playfulness and
aesthetics perception formed through smartphone brand usage experience affects both the
brand usage satisfaction and the purchase intention of portable and non-portable devices.
This is expected to help smartphone manufacturers to establish a product strategy, and it
should also help establish effective communication between the product development
department and the marketing department.
5.2. Limitations of the Study and Directions of Future Research
This study has a few limitations and some things to consider for future research: First,
it would have been better if this study measured the factors the users most frequently
considers when choosing a smartphone brand. If the first reason for choosing a
smartphone brand had been measured, and the correlation with it and the brand usage
experience factors had been studied, a meaningful effect could have been confirmed
regarding the establishment of switching barriers for the development of smart devices. In
future research, it is expected that if a study is carried out regarding the correlation of
user‟s first perceived intention of purchasing a smartphone brand, the smartphone brand
usage experience, and the smart devices‟ first perceiving intention, it would have an
interesting result.
Second, there is a limitation that this study does not include the service-related factors
in the smartphone brand usage experience. In modern industries, the management of after
service provided for consumers and VoC (Voice of Consumers) shows the industry‟s
capability and is one of the brand factors that enhances loyal consumer. This study had
not included this due to the worry that the research scale would become too big, but in
future studies, it is likely that service-related factors will be included.

Vol. 10, No. 2 (2016)
Third, it would have been better if modern consumption patterns had been reflected in
the study. Modern consumers tend to purchase products after having rationally compared
and analyzed the products through searching for information on various products
involving factors such as reputation and product reviews. The correlation with the
recommendation and review of a product by a stranger, rather than an acquaintance, and
one‟s brand experience, and the effect this has on the future purchase of a product could
have been considered.
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Authors
Minyoung Noh, He received the degree of Master of Science in
Information Management from KAIST at Seoul Korea. He works as a
business manager in SK Holdings.
Myungsin Chae, She received Ph. D in MIS from the University of
Illinois at Chicago in 2003. She is a professor in the department of MIS
at Seoul University of Venture and Information at Seoul Korea. She
teaches courses and conducts research in e-business and mobile
business, and strategic IS management.
Byungtae Lee, He is a professor of College of Business, KAIST and
CEO of KAIST Venture Investment Holdings. He is also managing
three research centers at KAIST; SK Center for Social
Entrepreneurship, Research Center for Corporate Social Responsibility
and Research Center for Digital Economy and Innovation. He also
taught at The University of Illinois at Chicago and The University of
Arizona as a faculty member of their business schools. He received his
Ph.D. in Business Administration (major in MIS, Minor in Economics)
from The University of Texas at Austin. His research topics include
Economics of IS, IT productivity measurement, strategic IT
investments, Electronic Commerce, Electronic Auction markets, IT
applications for health industry, Economic Analysis of Digital Content
Business, and Analysis on Virtual Economy.

Vol. 10, No. 2 (2016)
Moonsoo Yoon, He is the Chief Researcher at the Wonju Medical
Industry Technovally(WMIT), Korea. He is the adjunct professor at the
Biodefense Research Institute (BDRI), Korea University. He is
studying for Ph. D. in Business Management at the Seoul Venture
University. He served for the DPKO, United Nations in New York as
the Medical Support Officer from 2001 to 2005. He was graduated
from the Public Health Graduate School, Yonsei University in 1994.

Vol. 10, No. 2 (2016)

Noh et al 2016

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