This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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A Study of the Factors Effecting Customer Loyalty - Focusing on Korean
Cyber-Learning
Woohyun Kim1, Ruth Jongsuk Lee 2, Kumwon Cho 3, Bongyou Lee 4
1,2,3
National Institute of Supercomputing and Networking
Korea Institute of Science and Technology Information
Daejun, South Korea
{woohyun, jsruthlee, ckw}@kisti.re.kr
4
Yonsei University
Information Graduate School
Seoul, South Korea
bglee@yonsei.ac.kr
Abstract :
Today, Cyber-Learning has been greatly influencing many fields of the educational industry in korea. The
Cyber-Learning would provide students with chances to expand their horizons and knowledge anywhere and
anytime. Not only that, Now, Satisfying needs of the students by offering various solutions in order to help their
even more profound learning and studying. Especially, in case of Korean Cyber-Learning, Science-engineering
simulation based Cyber-Learning education industry (For example: The EDISON Project form Korea Institute
of Science and Technology Information) for Graduate/Undergraduate students, which can replace foreign
simulation SW, or various e-Learning system for advanced learning capacity-building of elementary school/
middle school/high school students are continuously developed so that more various and wide education market
is being constituted. This paper investigate elements affecting on customer loyalty in order to find out
consumers' intend for continuous by recognizing an importance of Cyber-Learning which is rewriting paradigm
of education industry. For this, first of all, relationship among Customer satisfaction, Perceived value, Image
which can be applied for Customer Loyalty are investigated, and then by recognizing positive/negative effects of
these found variables, what shall be improved in order to increase Customer Loyalty will be studied. Thus,
through this research, by anticipating continuous development and improvements of Cyber-Learning, it is
expected that this will have a positive effect on education industry development, and furthermore, it will
contribute to increase diversity of customer loyalty research area.
Keywords-component; Cyber-Learning; e-Learning; Customer Loyalty
I.
Introduction
Cyber-Learning means a type of education being performed in the advanced IT-based cyber space. With the
development of the internet in the late 1990s, the advanced IT has been spread in the public. Since the
establishment of a cyber- university in 2001, Cyber-Learning has widely been known in Korea. (WIKIPEDIA,
http://en.wikipedia.org/wiki/Cyber-Learning)
Generally, Cyber-Learning is aimed at realize a change and
innovation in the overall educational industry by making the teaching method of off-line(traditional) education
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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more conventional. The Cyber-Learning helps students directly experience high-quality learning through
computer graphics, virtual reality, and shape modeling(Alexei, 2006).
In this thesis, Cyber-Learning, emerged as the key to the educational industry after its constant development,
is defined as follows:
Cyber-Learning is something expanded in the learning and teaching areas
by the use of IT in the educational field.
Cyber-Learning is changing the current paradigm in the Korean educational industry.
For instance, the Super-Computing Center at the Korea Institute of Science and Technology Information has
Cyber-Learning System which helps students and researchers access a virtual laboratory and calculate the
complex fields which they never experienced in real time. The Korean innovative Cyber-Learning system
(EDISON: EDucation research Integration though Simulation On the Net) is used in more than 100 universities
and colleges and by over 10,000 students, and is expected to reach the economic ripple effect worth 500 billion
KRW(EDISON, http://edison.re.kr). Korean Educational Broadcasting System provides Cyber-Learning
education for primary and secondary school students. In Korea, students should take College Scholastic Ability
Test to enter in college or university. For the test, they intensively complete three-year secondary education. In
the course, more than 80% (830,000 students as of 2006, the number estimated to rise as of now) of students who
will take the test use the Cyber-Learning educational system of EBS Plus 1for studying. Considering the high
private education cost for high school students (the private education cost for high school students accounts for
17.5%; for primary school students 52.5%; and for middle school students 30%), the Cyber-Learning system
produces a big outcome(EBS1, http://www.ebsi.co.kr). As such, the Korean educational industry is developing in
various types at the center of Cyber-Learning. The users of the Cyber-Learning is on the rise. Therefore, realizing
that Cyber-Learning plays a leading role to change the Korean educational industry, this study tries to investigate
the Customer Loyalty which serves as an important factor to keep developing Cyber-Learning and increasing the
use rate.
II.
Theoretical Background
A. ECSI Model
European Customer Satisfaction Index(ECSI) model, designed on the basis of Swedish National Customer
Satisfaction Barometer(SCSB), American Customer Satisfaction Index(ACSI), and Norway Customer
Satisfaction Barometer(NCSB), is the latest model to find the present and future performance and customer
loyalty of companies. ECSI Model has already been studied in many countries, including Denmark, Australia,
France, the Netherlands, and Switzerland(Grigoroudis, 2004).
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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[Figure 1. The basic ECSI model]
The SCSB was proposed as the satisfaction with companies and industries was first surveyed in 1989. The
ACSI was developed in 1993 to survey the satisfaction of American customers. The NCSB, an extended model of
the ACSI, was developed in 1996. In 1999, Norway extended the structure of customer loyalty with mediating
factor of customer satisfaction effect earlier than the US (ECSI Technical Committee,1998; Grigoroudis et,
al,2004).
[Figure 2. Source: ECSI Technical Committee, 1998 ]
Kai et, al(2010) reported that the basic ECSI model serves a role to connect customer satisfaction with
customer loyalty and that such variables as Image, Expectation, Hard ward, Human ware, and Perceived value
explained well the atmosphere of service environments and the intentions of customers' personal behaviors (Kai
et, al, 2000). In other words, when the ECSI model is applied, it is possible to calculate the effects of customer
satisfaction levels and the future customer loyalty (ECSI Technical Committee,1998).
Therefore, the Research model used in this thesis was based on the ECSI (European Customer Satisfaction
Index (ECSI) proved to be the most proper model to read customers' behaviors. And this study excluded three
variables, proved to be not significant in the educational industry, but only used Image, Perceived Value, and
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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Customer Satisfaction variables to investigate the effect of the variables on customer loyalty(Grigoroudis 2004;
Robert et, al, Kai et, al,2000; Robert M.B et, al.,2009; ECSI Technical Committee,1998).
[Figure 3. Research model]
B. Image
Generally, the definition of image can be found in marketing literatures. Image is considered to be a greatly
important part of the service in terms of the general evaluation of service(Andreassen,1998). The basic ESCI
model regards the image as the most fundamental variable, and the image variable is used to determine whether to
fit customer loyalty (ECSI Technical Committee,1998). According to the aforementioned research on customer
satisfaction and loyalty in different industries, performed in Denmark in 1990, eight images were investigated, all
of which positively affected customer satisfaction and loyalty. Given that customer satisfaction and loyalty were
proved to be positively affected in eight different industries, including the fast food industry, the
telecommunication industry, and the bank industry, it indicates that the two variables will be positive to various
industries and will be able to be applied widely(Andreassen,1998; ECSI Technical Committee,1998). Image can
become a decisive means for consumers' purchase decision (e.g., use of Cyber-Learning), or customer loyalty. It
emerges as a factor to lead the on/off-line community activities based on information reliability. In addition,
Image is used to determine customer loyalty through customer experience, which is connected with the decision
of perceived value. Above all, Image influences the decision of contents purchase. As part of satisfaction
evaluation, it exerts great influence on the choice of a brand which can give high customer satisfaction
(Andreassen,1998; ECSI Technical Committee,1998; Muhammad,2012) .
Hypothesis 1: Image positively influences Customer Loyalty.
Hypothesis 2: Image positively influences Perceived value.
Hypothesis 3: Image positively influences Customer Satisfaction.
C. Perceived Value
Customers' actual experience greatly affects their satisfaction and dissatisfaction, which are associated with
Perceived Value. Usually, perceived value can be determined by the overall evaluation of customers (Perceived
value includes time and effort).The annual educational cost for a Korean college (or university) student is around
10,560,000 KRW, which means that a generous investment is made into education. Accordingly, it can be
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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understood that Korean students using Cyber-Learning are not concerned about financial sacrifice. However, the
values of non-financial sacrifices, such as personal learning hours and efforts, are decided according to
individuals' perception. Therefore, It is expected that Korean students grant as much value as they spend previous
hours in studying, and that the higher the value is, the more it positively affects customer loyalty. According to
Fornell(1992), once there are expectations for quality, perceived value occurs. In other words, when there is
perceived value, customer satisfaction occurs. The positive perceived value means that there is the likelihood of
business success. Therefore, when customers using Cyber-Learning spend time to acquire knowledge, it is
possible to measure their value and satisfaction(Andreassen,1998; ECSI Technical Committee,1998;
Muhammad,2012) .
Hypothesis 4: Perceived value positively influences Customer Satisfaction.
Hypothesis 5: Perceived value positively influences Customer Loyalty.
D. Customer Satisfaction
According to Andreassen(1998) and Fornel(1992), there is positive correlation between customer
satisfaction and customer loyalty. According to ECSI Technical Committee(1998), customers decides a level of
satisfaction in evaluation when they have expectations about product features, and customer satisfaction occurring
at a certain time is the most important factor to determine customer loyalty. Customer loyalty can be found by
cumulative customer satisfaction, which can be an index of the past, the present and the future so that it plays a
big role to give a company a motive for investing in customers. As for the cumulative satisfaction, once
expectations are equal to evaluation, zero disconfirmation occurs. At that time, a high level of customer loyalty
appears (Kai et, al,2000; Andreassen,1998; ECSI Technical Committee,1998; Muhammad,2012). Therefore, it is
expected that as the expectations and evaluation of people using Cyber-Learning are more accumulated, they
positively influence customer loyalty.
Hypothesis 6: Customer Satisfaction positively influences Customer Loyalty.
E. Customer Loyalty
Andreassen et, al.(1998) reported that customer loyalty had something to do with service or companies'
behavioral intention. In other words, by listening to customers' voices and detecting their changes, companies
tend to update customer satisfaction with service in a better way. On the contrary, if companies have a little
conversation with customers and poorly understand customers' complaints, their service tend to downgrade, and
customer satisfaction falls. When companies have a grip on customers' requests and changes, they can not only
secure long-term demands, but increase the future retention rate and make exponential changes(Anderssen, 1995).
According to Andreassen et al.(1998), the reasons for the occurrence of customer loyalty are switching barriers,
or a lack of real alternatives. In other words, when customers are satisfied with the relationship with the
companies that they try to use constantly, customer loyalty occurs(Muhammad,2012). said that when there are
consistent image and perceived value between service suppliers and customers, customer satisfaction and loyalty
are positively influenced. In Cyber-Learning, customer loyalty can be viewed in two kinds of dimension:
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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customer attitude and decision. For instance, Cyber-Learning users' recommendation to other people and their
intention of reuse of Cyber-Learning can be used to decide a level of customer loyalty.
III. Research Method
A. Research Subjects
This study conducted a questionnaire survey with the Cyber-Learning users to investigate constant use
intention of the Cyber-Learning consumers and analyze the factors affecting the customer loyalty. The
questionnaire survey was performed on April 21, 2014. A total of 200 people participated in the survey. The
study participants in their 20s accounted for 34.0%, those in their 10s 27.5%, those in their 30s 21.5%. The
study subjects with less than 1 year experience of Cyber-Learning accounted for 30.5%, those with 1-2years
experience 24.5%, and those with 2-3years experience 24.5%.
Gender
Frequency
Percentage
Male
92
46.0
Female
108
54.0
Total
200
100.0
10s
55
27.5
20s
68
34.0
30s
43
21.5
40s
28
14.0
50s
6
3.0
Total
200
100.0
In middle school
3
1.5
In high school
8
4.0
Graduated from high school
20
10.0
In college (university)
60
30.0
90
45.0
In graduate school
6
3.0
Received M.A.
11
5.5
Received Ph.D
2
1.0
Total
200
100.0
Less than 1 year
61
30.5
Between 1 and 2 years
49
24.5
Between 2 and 3 years
49
24.5
Between 3 and 4 years
25
12.5
Between 4 and 5 years
8
4.0
Between 5 and 6 years
4
2.0
Age (in the unit of 10 years)
Graduated from college
Final education
(university)
Cyber-Learning Use Period
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Between 6 and 7 years
2
1.0
More than 7 years
2
1.0
Total
200
100.0
[Figure 4. Demographical distribution of respondents]
B. Validity & Reliability Analysis and Summary of the Results of Hypothesis Testing
In order to analyze that questionnaire questions were measured in the same way of study intention, this
study used SPSS and AMOS to perform reliability and validity analysis. And structural equation was applied to
test hypotheses. First, Image, Perceived Value, Customer Satisfaction, and Customer Loyalty had more than 0.6
of reliability. It means that there is no problem with internal consistency of questions. However, according to the
factor analysis to confirm validity, for Image factors, questions 1 to 7 were loaded well, but questions 8 to 10
were not loaded well. In the case of Perceived Value, questions 1 to 4 were loaded well, but the questions 1 to 2
which were subject to Customer Satisfaction were also loaded. For Customer Loyalty factors, questions 2 to 5
were loaded well, but question 1 was not loaded well.
Factor
Variables
Cronbach’s
Question
1
2
3
4
Image1(Q3)
.153
.758
.140
.084
Image2(Q4)
.168
.728
.302
.038
Image3(Q5)
.251
.660
.032
.153
Image4(Q6)
.387
.572
.158
.163
Image5(Q7)
.282
.688
.232
.101
Image
Perceived Value
Alpha
.873
Image6(Q8)
.344
.749
.187
.087
Image7(Q9)
.516
.532
.339
.154
Image8(Q10)
.563
.371
.264
.156
Image9(Q11)
.046
.155
.251
.839
Image10(Q12)
.084
.116
.223
.863
PV1(Q13)
.533
.122
.088
.560
.791
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Customer
PV2(Q14)
.677
.265
-.026
.184
PV3(Q15)
.727
.166
.294
.058
PV4(Q16)
.722
.318
.279
.089
SF1(Q17)
.657
.305
.295
.034
.818
Satisfaction
Customer Loyalty
SF2(Q18)
.688
.378
.356
-.061
CL1(Q19)
.565
.303
.409
.112
CL2(Q20)
.458
.242
.551
.216
CL3(Q21)
.345
.263
.730
.210
CL4(Q22)
.335
.280
.780
.173
CL5(Q23)
.134
.144
.727
.271
.874
[Figure 5. The result of Reliability and Exploratory Factor Analysis]
According to Confirmatory factor analysis(CFA), goodness-of-fit index was presented in the following:
2
χ (183) = 541.014, p < .001, TLI = .836, CFI = .857, and RMSEA = .099. It is translated that although TLI and
CFI somewhat fall short of the base value .09, they are in proper level. The judgment criteria of convergent
validity are presented as follows: Average Variance Extracted(AVE) is more than 0.5; construct reliability is
more than 0.7; standardized lambda of each observed variable is more than 0.5. AVE met only Customer
Satisfaction, and construct reliability met all variables. In addition, the standardized lambda of each observed
variable was analyzed. As a result, for Image, questions 11 and 12 were not met, but for other latent variables,
the standardized lambda of each observed variable met the criteria.
Latent Variables
Image
Observed
Variables
Lambda(λ)
C.R.
Standardized
Lambda(λ)
Q3
1
Q4
1.148
8.719
0.7
Q5
1.109
7.653
0.602
Q6
1.152
8.646
0.693
Q7
1.56
9.031
0.73
AVE
Construct
Reliability
0.653
0.369
0.848
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Perceived
Value
Customer
Satisfaction
Customer
Q8
1.334
9.757
0.803
Q9
1.764
9.993
0.828
Q10
1.602
8.637
0.692
Q11
0.9
5.24
0.398
Q12
0.853
5.096
0.386
Q13
1
Q14
0.887
6.994
0.633
Q15
1.298
7.826
0.755
Q16
1.399
8.343
0.851
Q18
1
0.57
0.405
0.726
0.644
0.783
0.382
0.753
0.877
Q17
0.902
12.906
0.788
Q19
1
Q20
1.012
9.702
0.73
Q21
1.245
11.366
0.863
Q22
1.262
11.647
0.888
Q23
0.852
8.706
0.652
0.702
Loyalty
Note. C.R=critical ratio, AVE=average variance extracted
[Figure 6. The result of Confirmatory Factory Analysis(CFA)]
In the judgment criteria of discriminant validity, as shown in the below table, AVE was larger than the
square of correlation coefficient, but all were not met. Therefore, it was found that there was poor discriminant
validity.
The square of correlation coefficient (ρ2)
AVE
Image
Image
PV
PV
CS
0.369
0.696
0.405
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CS
0.689
0.774
CL
0.621
0.626
0.644
0.616
0.382
[Figure 7. The Judgment Criteria of Discriminant Validity]
C. Results
Above all, goodness-of-fit index was presented in the following:χ2(183) = 541.014, p < .001, TLI = .836,
CFI = .857, and RMSEA = .099. It is translated that although TLI and CFI somewhat fall short of the base
value .09, they are in proper level. Therefore, the statistical significance of each hypothesis in this thesis is
presented as follows: Hypothesis 1(Image positively influences Customer Loyalty, p < .01.), hypothesis 2(Image
positively influences Perceived value, p < .001.), hypothesis 3(Image positively influences Customer
Satisfaction., p < .05.), and hypothesis 4(Perceived value positively influences Satisfaction, p < .001.) were
found to be the factors which positively influenced Customer-Loyalty. However, the positive influence of
hypothesis 5(Perceived value positively influences Customer Loyalty)and hypothesis 6(Customer Satisfaction
positively influences Customer Loyalty) was found to be insignificant. In other words, the independent variable
which was statistically significant to the dependent variable Customer Loyalty was only Image variable, which
positively influenced dependent variables. Therefore all hypotheses were accepted. However, Customer
Satisfaction and Perceived Value negatively influenced dependent variables so that relevant hypotheses were
rejected.
Dependent Independent
Standard
C.R.
p
0.16
6.692
***
2
○
0.807
0.188
4.301
***
4
○
Image
0.535
0.213
2.516
.012
3
○
PV
0.431
0.265
1.624
.104
5
×
CS
0.282
0.199
1.419
.156
6
×
Image
0.652
0.244
2.673
.008
1
○
Lambda (λ)
Variables
Variables
PV
Image
1.072
PV
Error
Hypothesis Acceptance
CS
CL
***
p < .001
[Figure 8. The Research Result]
Many studies already revealed that Image variable positively influenced Customer Loyalty. As such, this
study also concluded that Image variable most positively influenced Customer Loyalty in the Cyber-Learning
industry. Also, given that Image affected Perceived Value and Customer Satisfaction, it was found that Image
variable significantly affected customers' purchase decision.
This paper is presented on : 2nd International Conference on E-Learning and E-Educational Technology ( ICELEET 2014 ) Zurich, Switzerland on July 9-10, 2014
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IV. Conclusions
The Cyber-Learning market changes very rapidly. For the constant development of the market, it is very
important to understand customers' needs from the industrial point of view.
In this sense, the result of this study showed that quality Image could play a big role to understand customers'
needs and draw their positive interest. For instance, given that Image positively affects Customer Loyalty (equal
to the understanding of customers' needs), when image is applied to customer marketing in the business
perspective, it is possible to provide fresh and various services and analyze customers' needs accurately. As a
result, image can be served as a critical factor of business growth. Studies related to Customer Loyalty have
been conducted in various industries, but in the Cyber-Learning industry. In this sense, this study is very
meaningful in the point that customer loyalty was investigated in the Cyber-Learning area. However, it is hard
to generalize this study for the following reasons: one single independent variable (Image) positively influenced
dependent variables; although it collected the samples reflecting various characteristics, the 200 samples
collected were not able to represent all types of Cyber-Learning. Nevertheless, if the future research based on
this study uses the differentiated control variables and various independent variables only for Cyber-Learning, it
will possible to make new suggestions which can help Cyber-Learning customers create new values.
ACKNOWLEDGMENT
This research was supported by the EDISON Program through the National Research Foundation of
Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(No. NRF-2011-0020576).
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