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Telecommunications Policy 28 (2004) 751–765
www.elsevierbusinessandmanagement.com/locate/telpol
Determinants of subscriber churn and customer loyalty in the
Korean mobile telephony market
Hee-Su Kima,Ã, Choong-Han Yoonb
a
Korea Information Society Development Institute, 1-1 Juam-dong, Kyunggi-do, Kwachun City 427-710,
Republic of Korea
b
College of Economics and Business Administration, Hanyang University, 1271 Sa-1 dong, Sangrok-gu, Ansan,
Kyunggi-do 426-791, Republic of Korea
Abstract
By using a binomial logit model based on a survey of 973 mobile users in Korea, the determinants of
subscriber churn and customer loyalty are identified in the Korean mobile telephony market. The
probability that a subscriber will switch carrier is dependent on the level of satisfaction with alternativespecific service attributes including call quality, tariff level, handsets, brand image, as well as income, and
subscription duration. However, only factors such as call quality, handset type, and brand image affect
customer loyalty as measured by the intention/non-intention to recommend the service provider to other
people. The insignificance of subscription duration in affecting the loyalty-induced action indicates that
lock-in effects are likely to be concentrated among the ‘‘spuriously loyal’’ customers who are not willing to
churn just because of switching costs. These findings provide implications for the mobile business as well as
competition policies for the mobile telephony market.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Mobile; Churn; Satisfaction; Customer loyalty; Korea
ÃCorresponding author. Tel.: +82-2-570-4120; fax: +82-2-570-4069.
E-mail addresses: hskim@kisdi.re.kr (H.-S. Kim), yoonchoo@hanyang.ac.kr (C.-H. Yoon).
0308-5961/$ - see front matter r 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.telpol.2004.05.013

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1. Introduction
The mobile telephony market is one of the fastest-growing service segments in telecommunications. Nearly half of all potential telephone calls worldwide can be made through mobile phones.
This figure was expected to reach more than 75% by the end of 2003, indicating that mobile
telephony is poised to surpass fixed telephony as the service most available to potential callers
around the globe.1 The spectacular growth of the mobile market has been driven not only by
innovation in wireless technologies but also by fierce competition among mobile carriers under
minimal regulations in sharp contrast to the fixed telephony market.
As with many other services offered on a subscription basis, the mode of competition has
shifted from acquiring new subscribers to retaining existing customers and luring away customers
from rival companies. As wireless penetration increases each year, how to avoid outbound churn
and maximize customer loyalty has become a serious concern for wireless companies, though a
higher rate of customer churn signifies that the market is functioning well.2
The first step in minimizing outbound churn and building up loyalty of the existing customers is
to understand the causes of churning. By using a binomial logit model based on a survey of 973
mobile users in Korea, this paper identifies the determinants of subscriber churn and customer
loyalty in the Korean mobile telephony market.
The determinants of subscriber churn are estimated by a model that relates the probability of
switching to a set of possible explanatory factors including various service attributes and subscriber
characteristics. The results show that the probability a subscriber will switch carriers is significantly
dependent on the level of satisfaction with various (alternative-specific) service attributes of that
carrier (call quality, tariff level, handsets, brand image), his income level, and subscription duration.
Among these factors, brand image and duration of subscription provide interesting
implications. Brand image is found to remain important even after controlling other factors
affecting brand image such as call quality and handsets. On the one hand, this implies that brand
management in itself is an important area in mobile business, in which corporate resources need to
be committed separately. On the other hand, when viewed from the perspective of effective
competition, brand-building efforts to reduce churn may serve to raise a mobility barrier that
reduces competition, in particular when it is made by a dominant service provider.
In addition, by estimating the determinants of customer loyalty as measured by intention to
recommend the present carrier to others, the factors of call quality, handset type and brand value
are shown to have significant explanatory power. Subscription duration is found to be negatively
associated with churn probability, but turns out to have no significant influence on those loyal
customers who are willing to recommend their present mobile carrier to other people. Therefore, a
so-called lock-in effect is identified as existing among the non-loyal subscribers who wish to stay
put most likely due to switching costs.
The results of this paper can be useful for mobile operators interested in growth strategies and
churn/retention management, since the Korean mobile market has exhibited the fastest growth
1
See ITU (2000).
According to IDC, nearly one-third of all wireless phone customers changed carriers at least once in 1998. IDC
expects defections to hit 57% in 2003, as wireless competition intensifies. IDC also estimates that each lost customer
cost wireless companies an average of $676 in 1998. (Wall Street Journal (European Edition), September 18, 2000).
2

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753
rate in the world for the past few years and is entering a mature or saturated stage. This paper also
raises concerns over the anticompetitive effect of customer lock-in in the mobile market and calls
for appropriate policy measures to ease switching barriers for more effective competition.
An increasing number of articles regarding the mobile market have appeared in academic
journals and econometric analysis of customer churn has been applied to some communications
sectors in which service providers compete fiercely to acquire more subscribers. However, to the
knowledge of the authors, there has been no article analyzing econometrically the determinants
for customer churn in mobile telephony.
Valletti and Cave (1998) traced the development of competition in the UK mobile telecom
market and reviewed mobile operators’ strategies, while Fullerton (1998) studied the relationship
between market structure and market performance in regional mobile markets of the US. More
recently, a special issue of Telecommunications Policy in February/March 2001 was devoted to
articles on the current issues of mobile telephony. In particular, two papers in this issue deserve
mention. Song and Kim (2001) measured the effect of restructuring the Korean mobile phone
market through a simulation analysis, and Choi, Lee, and Chung (2001) analyzed the business
strategies of the five mobile carriers in Korea and assessed the performance of government
regulation on the Korean mobile market.
Gerpott, Rams, and Schindler (2001), studying the German mobile cellular phone market, showed
that customer retention, loyalty and satisfaction were causally interlinked and that mobile service
price, mobile service benefit perceptions as well as lack of number portability have strong effects on
customer retention. In terms of subject matter and key implications, his article is similar to the
present paper, but the latter uses an econometric model (logit model) that can properly deal with the
dichotomous decisions of consumers on whether to churn or not and whether to remain loyal or not.
Kim and Kwon (2003), studying the factors that consumers take into account when they choose
mobile operators, showed that network size mattered to the Korean consumers in their choice of
mobile operators, ascribing the result to intra-net call discounts and the quality signaling effect.
Madden, Savage, and Coble-Neal (1999) estimated a binomial probit model relating the
probability of subscriber churn in the Australian ISP market to various service attributes and
demographic characteristics.
In the non-academic arena, two OFTEL reports, Consumer Switching Behaviour in the Telecoms
Market and Mobiles-Barriers to Switching and Quality Issues, present findings on the UK
customers’ switching of their telecom carriers including mobile operators. But they do not employ
an econometric method in analyzing the reasons for switching.
The paper is organized as follows. Section 2 provides a snapshot of the evolving structure of the
Korean mobile telephony market and recent policy issues. In Section 3, a logit model is
constructed for deriving the factors that can explain the switching intention and loyalty of mobile
consumers. Section 4 then presents the results of the estimation analysis and their implications,
and Section 5 provides the conclusion.
2. Overview of the Korean mobile telephony market
The mobile telephony service in Korea was launched in 1984 by a government-owned company,
Korea Mobile Telecom (KMT). Later, in 1994, KMT became SK Telecom under the new

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ownership of the SK Group. The long-time monopolistic market structure began to change from
1996 with the entrance of new operators. Shinsegi Telecom entered the market in 1996 and three
more competitors, KT Freetel, Hansol M.com and LG Telecom entered the following year. The
wireless technology of the three new entrants, called PCS (Personal Communications System),
was hyped as a harbinger of ‘‘dream communications’’ with superior capability of data
communication over existing cellular technology. This state-of-the-art image of the new entrants,
as embodied partly in more stylish handsets, enabled them to outpace the incumbent operators in
attracting new subscribers for more than a year, though the incumbents soon caught up with these
entrants. In Fig. 1, the period from December 1997 to June 1999 shows the declining market share
of the leading incumbent, SK Telecom.
The fierce competition among the five operators to acquire new subscribers resulted in a rapid
growth in mobile phone users. The number of mobile service subscribers was at around 6 million
in 1997, but it quickly reached around 30 million (61% of the population) as of June 2002 (Fig. 1).
Note also that the number of users exiting the market or switching carriers (referred to as
‘outbound churn’ in the figure) had steadily increased until June 2000, when the Korean
government banned handset subsidies, thus raising the consumer cost of switching mobile
operators.
During the period of rapid growth, the five mobile carriers were engaged in a heavy marketing
blitz, offering handset subsidies to new subscribers in a bid to increase market share as quickly as
possible. Although the initial popularity of the entrants’ new handsets (and the resultant shortage
of handset supplies to the incumbent) made it possible for them to penetrate the market quickly,
subsidy competition subjected all the new entrants to severe financial strain, leading finally to
M&As among the carriers. In 2000, SK Telecom acquired Shinsegi Telecom and KT Freetel
acquired Hansol M.com.
Among the mergers, SK Telecom’s acquisition of Shinsegi Telecom raised concerns over the
possibility of dampening competition in the mobile market. One of the major conditions set by the
35,000,000
30,000,000
25,000,000
20,000,000
15,000,000
10,000,000
5,000,000
-
Jun- 97 Dec- 97 Jun- 98 Dec- 98 Jun- 99 Dec- 99 Jun- 00 Dec- 00 Jun- 01 Dec- 01 Jun- 02
Subscribers
Outbound churn
Fig. 1. Trends in the growth of subscribers and outbound churn. Source: Ministry of Information and Communication.
*Official outbound churn data not available after June 2001.

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755
80%
70%
60%
%
50%
40%
30%
20%
10%
0%
Dec. 1997
Jun. 1998
Dec.
Jun. 1999
Dec.
Jun. 2000
Dec.
Jun. 2001
Dec.
Jun. 2002
SKT
66.9%
50.5%
42.7%
41.3%
43.1%
57.6%
53.9%
49.7%
52.3%
53.4%
Shinsegi
16.5%
15.1%
15.3%
15.0%
13.8%
KTF
5.1%
13.5%
16.8%
18.4%
18.2%
18.7%
19.7%
34.5%
33.0%
32.8%
Hansol
6.1%
8.6%
10.1%
11.4%
11.7%
10.1%
11.7%
LGT
5.4%
12.3%
15.1%
14.0%
13.2%
13.6%
14.7%
15.8%
14.7%
13.9%
Fig. 2. Trends in market share of mobile carriers in Korea. Source: Ministry of Information and Communication.
Fair Trade Commission for the approval of SK Telecom’s acquisition bid was for SK Telecom to
reduce the merged firm’s share of subscribers (57% at the beginning of the consolidation) to less
than 50% by June 2001. As a result of this ruling, SK Telecom took measures to reduce its share,
one of which was to decline to accept new subscribers. As of July 5, 2001, SKT’s market share hit
just under the 50% target. However, soon after, SKT’s market share began to increase in such a
way that the net increase of subscribers to either of the other mobile operators became negative
(see Fig. 2).
Though market concentration can be viewed as a result of the efficiency-enhancing market
process, the recent direction of the Korean mobile market tipping towards SK Telecom is deemed
beyond reasonable bounds. In particular, the situation has led policy makers to believe that a
further market concentration would deprive consumers of options and that appropriate policy
measures are necessary for effective competition in the mobile telephony market.
A typical set of policy measures to this effect are what is referred to as asymmetric regulation.
This type of regulation provides greater advantages to new entrants and places more stringent
regulations on market dominating firms. As part of such measures, the interconnection fee that
the new entrants pay to the incumbent has been set close to the cost of termination on the
incumbent’s network, providing the advantage of economies of scale. In contrast, the incumbent’s
equivalent fee to the entrants has been arranged to represent the higher cost of termination on the
entrants’ networks. Under a retail price regulation currently imposed on SK Telecom, these costoriented access charges on termination would certainly benefit new entrants.
Another asymmetric regulation aimed at weakening incumbent advantages means that mobile
carriers will be disallowed to use carrier-specific prefixes in phone numbers, in order to prevent the
entry-deterring effects of advertising prefixes as brand names. The target of this policy is mainly
SK Telecom’s prefix (011). Since SK Telecom has more heavy users than any other mobile
companies and has spent amply on advertising its service products centered around the 011 prefix,
many Korean consumers prefer to have it (partly) out of a display motive, perceiving the prefix as

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a symbol of prestige.3 This consumer preference toward SK Telecom can be thought of as an entry
barrier to new entrants. (The following sections of this paper formally demonstrate and discuss
the implications of brand image in mobile businesses.) However, it remains to be seen whether
these policies will stop or reverse the tipping of the Korean mobile market toward the leading
incumbent, without overly handicapping the incumbent or doing harm to consumers.
3. Econometric model of subscriber churn and loyalty
In order to analyze the dichotomous decision of consumers on whether or not to switch carrier,
an appropriate econometric tool is a binomial logit model based on discrete choice theory.
Discrete choice theory is the study of behavior in situations where decision makers must select
from a finite set of alternatives. It posits that an individual is likely to choose an alternative over
others when the level of its utility to him is greater than the utility of other alternatives. And, as
can be seen below, the canonical discrete choice model specifies the probability of an individual to
choose a certain alternative as a function of observed attributes of the individual and of the
alternatives available to him, and these attributes are supposed to be causal variables affecting the
choice.4
For the subject of this paper, the set of alternatives is ‘to churn’ and ‘not to churn.’ The factors
that influence the decision of an existing consumer on whether to switch to another mobile carrier
are divided into choice-specific factors (service attributes of mobile operator) such as call quality
and price level and individual-specific factors (demographic characteristics and phone usage
characteristics) such as income, age or subscription duration. Then the level of utility that the nth
subscriber obtains from either churning outbound or remaining with the current carrier can be
expressed as the following indirect utility function in terms of zjn (service attributes, jA{churn, no
churn}) and sn (individual-specific characteristics).
U jn ¼ Uðzjn ; sn Þðj 2 fchurn; no churngÞ:
(1)
The indirect utility in (1) can be divided into an observed part ðV jn Þ and an unobserved
part ðejn Þ:
U jn ¼ V jn þ ejn :
(2)
The probability of the nth subscriber to churn, as derived by making the level of utility from
churning greater than that from not churning, can be expressed as follows.
PrðchurnjjÞ ¼ PrðU churn;n 4U no churn;n Þ:
(3)
If the unobserved part, ejn ; is identically and independently distributed following a logistic
distribution, the revealed utility and the probability of churning are related by a binomial
logit.
3
According to a consumer survey, 72.7% of Koreans picked up SK Telecom as the most used brand among the three
mobile service providers. This figure far surpasses SK Telecom’s market share (in terms of subscribership) that is
around 56% as of May 2003. (The Financial News, May 4, 2002) However, there are some other consumer reports
saying that call quality differences are negligible among the mobile carriers in Korea.
4
See Cosslett (1981).

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This discrete choice model can also be applied to the issue of customer loyalty, if the two
alternative decisions ‘churn’ or ‘no churn’ in the above paragraphs are replaced by ‘remain loyal’
or ‘not remain loyal’, respectively. Since customer loyalty generally refers to a customer’s
willingness to continue his/her relationship with a certain company or product/service, the
decision not to churn from the current mobile operator, dependent on the length of time, could be
equated to loyalty to that company.
However, customer loyalty in this paper refers to the ‘willingness to recommend his company
(or its service) to other people’. This can be considered a stronger form of trust in that company
than a mere decision not to churn. The stronger definition of customer loyalty adopted here is
likely to be more suitable for identifying true loyalty in mobile phone markets by filtering out
‘‘spurious loyalty’’5: since the act of churning generally incurs a variety of switching costs such as
change of phone number or purchase of a new handset, decisions not to churn may be simply the
result of avoiding the switching costs. These costs can often vary with changing strategies of
service providers such as exemption of entry fees or handset subsidies and even with policy
measures like mandatory number portability. Under this condition, a more robust measure of
customer loyalty is called for. The ‘loyal’ customers, as defined, would not turn to another
company even though switching costs become negligible.
Moreover, in markets like mobile telephony where consumers have limited ability to discern
differences in the quality of service across different companies, word of mouth from experienced
users is likely to have an impact on consumers’ subscription decisions. As a result, the mobile
service companies need to focus on increasing the number of supporters of their services/products
and not merely on retaining existing subscribers.
3.1. Model
A binomial logit model is utilized to relate the probability of a subscriber leaving his current
mobile carrier to explanatory factors including service attributes and demographic variables.
The model is expressed as follows:
Pjn ¼ Fðx0 jn bÞ;
(4)
where Pjn is the probability that the nth subscriber will switch from the jth carrier to another, x0 jn
is a vector of explanatory variables, b is a vector of coefficients to be estimated, and F represents
the cumulative logistic distribution function.
5
There is no definitive definition or method of measurement of customer loyalty, but Dick and Basu (1994),
synthesizing several definitions of customer loyalty, criticized the traditional behavioral measures of customer loyalty
that focus on propensity for repeat purchase with little attention to attitudinal factors behind the purchase decisions.
They label as ‘‘spurious loyalty’’ those purchases guided not by a concomitant strong attitude but merely by situational
exigencies. Cross-classifying two (low and high) levels of attitude and repeat patronage, they categorized loyalty into
four types: no loyalty, spurious loyalty, latent loyalty, and loyalty. Griffin (1995) renamed Dick and Basu’s four types
of customer loyalty as no loyalty, spurious loyalty, latent loyalty, and premium loyalty. According to Griffin, the
customers with premium loyalty become vocal advocates for the product or service and constantly refer it to others. In
sum, by defining customer loyalty as ‘willingness to refer/recommend to others,’ attitudinal factors are taken into
account and thus more robust predictions about continued relationships become possible.

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Table 1
Description of variables
Variable
Description
Dummy for switching (dependent variable for churning
model)
=1: Subscribers with intention to switch; =0:
Otherwise
Dummy for loyalty (dependent variable for loyalty model)
=1: Subscribers with intention to recommend the
present carrier to others; =0: Otherwise
Dummies for satisfaction with call quality (CS1), tariff level
(CS2), billing (CS3), value-added services (CS4), customer
services (CS5), handset (CS6), brand image (CS7)
=1: Satisfied with the respective service attributes of
the present carrier;
=0: Otherwise
Age
Subscriber’s age
Dummy for sex
=1: Male; =0: Female
Income
Midpoint of the income group each subscriber
belongs to
Monthly payment
Average monthly payment for mobile telephony
service
Duration of subscription
Duration of subscription with the present carrier
(months)
Duration of handset used
Duration of the present handset used (months)
Dummy for switching experience
=1: Subscribers with switching experience; =0:
Otherwise
The value of the dependent variable was set to 1 when the subscriber expressed an intention to
switch during the next one-year period or right after the expiration of the subscription contract,
whichever came first, and 0 for the complementary case.
Explanatory variables included in the model are listed and described briefly in Table 1. For
alternative-specific variables, instead of using the service attributes of the mobile carriers directly,
the level of satisfaction was used and it was measured by having each consumer evaluate (on a
5-point scale) major service attributes provided by the mobile carrier: call quality, tariff level,
billing, value-added services, customer services, handset, and brand image.6
6
There are some reasons for using the scores of customer satisfaction. First, most of the important service attributes
of the mobile service are hard to express as a single number that incorporates the various aspects of each attribute. For
example, call quality can be measured by such indices as access failure rate, call completion rate, average noise level,
and so forth, but any combined measure of these indices is inevitably subjective. As for price, any mobile operator
offers its service price as a large number of optional price plans to target the consumers with different minutes of use.
Thus, in order to express a mobile operator’s price as a single index, it is necessary to know the proportion of users for
each price plan or average price per minute (by dividing total end user revenue by total minutes of use), but such
information was not available. Secondly, mobile phone services can be considered heterogeneous or differentiated with
different consumers assigning diverse values for the same attribute of the same alternative.

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Satisfaction with tariff levels means satisfaction with the overall amount of money paid for line
rental, voice calls, and other services relative to the tariff plans offered by other mobile operators.
Satisfaction with value-added services refers to satisfaction with the variety and usefulness of
value-added services such as call forwarding, caller ID display and short messaging services.
Satisfaction with a handset means satisfaction with the overall performance of the handset being
currently used. Satisfaction with brand-image corresponds to how favorably one evaluates the
reputation/reliability of his present company.
Each of these variables is denoted as a CS (consumer satisfaction) variable for each service
attribute.7 The selection of these attributes as well as subscriber-specific variables (to be explained
below) is based on several references including a survey questionnaire used by a leading mobile
operator in Korea.8
For demographic variables, age and sex were used, while income and average monthly payment
for mobile calls were selected for economic variables. Mobile phone usage variables included the
subscription duration with current operator, duration of current handset used, and a dummy
variable to measure past switching. The subscription duration with the current operator is related
to the lock-in effect, since consumers are likely to stick with the same service provider to avoid
switching costs such as a change in phone number. Since subscribers are often observed to switch
to the carrier that offers more advanced handsets, the longer a subscriber has used his present
handset, the more likely he is to switch carriers for a new handset. This is why the duration of the
present handset used was included as an explanatory variable.
7
Customer satisfaction is ‘‘a summary psychological state resulting when the emotion surrounding disconfirmed
expectations is coupled with the consumer’s prior feelings about the consumption experience’’ (Parasuraman, Zeithaml,
Valarie, Berry, & Leonard, 1988). Or it refers to ‘‘a customer’s perception of the value received in a transaction or
relationship (where value equals perceived service quality relative to price) relative to the value expected from
transactions or relationships with competing vendors’’ (Hallowell, 1996). But it is often measured by way of consumer
surveys using questionnaires, where customer satisfaction is simply an everyday word so that survey respondents are
asked questions like ‘‘How satisfied are you withy
8
The following references were consulted in choosing the explanatory variables:
(i) A questionnaire used by SK Telecom (the leading mobile operator in Korea): At the time of beginning this
research, SK Telecom used this questionnaire for its regular customer surveys. In this questionnaire, the
respondents are asked to rate their satisfaction level (on a 5-point scale) for the following attributes of mobile
services: reputation/brand image, handset (price and functioning), value-added services, customer service
(complaint handling), tariff level, overall performance, willingness to remain with the company and willingness
to recommend the company to others. Typical demographic statistics are also asked for here.
(ii) Lowenstein (1995) shows an exemplary list of attributes of a service for designing customer retention models:
customer service, product availability, price, product quality, billing, etc.
(iii) Madden, Savage, and Coble-Neal (1999): Analyzing churning in the Australian ISP market, they included, as
explanatory variables, ISP-choice (dichotomous) variables indicating whether or not each respondent chose their
ISP because of value-added contents, available help desk, perceived reliability or advertised speed. For individualspecific variables, they used not only demographics such as age, sex and income but also Internet usage variables
such as monthly expenditure on the Internet.
(iv) Gerpott, Rams, and Schindler (2001): They report four individual features as key drivers of the customer value of
cellular services: network quality, price, customer care such as complaint/inquiry handling and billing. Though
their article was not consulted during work on this research, the model in this paper reveals the inclusion of these
drivers.

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Furthermore, a distinction was made between those who had churned in the past and those
who had not because those with the experience of churning in the past may be able to assess the
current carrier more accurately. A dummy variable was utilized in order to incorporate this
distinction.
As for the model of customer loyalty, a value of 1 was set for those who expressed a willingness
to recommend their current mobile operators to other people, and 0 for the remaining
respondents. Explanatory variables are the same as the ones used in the churn model.
3.2. Data
The necessary data for the above estimation was obtained from a phone survey conducted in
September 1999 from a sample of 973 subscribers belonging to the five mobile carriers in Korea.9
The phone numbers used for this survey were originally selected a few months earlier for a
government-initiated survey aimed at measuring customer satisfaction with mobile telephony
service.
Though the data may seem somewhat outdated, it is meaningful to use the 1999 survey data
since the period from June 2000 to the present can be regarded as abnormal (so consumer
responses during this period and the analysis based on these might be lacking in universality in its
implications for other countries) in that since June 2000, handset subsidies have been banned by
the Korean government to lessen the socially wasteful replacements of handsets and the resultant
financial strain on mobile operators.
The discontinuation of handset subsidies served to raise the switching barrier for consumers. As
a result, the number of mobile users who opted to switch service providers (not to mention the
proportion relative to the total number of subscribers) declined during the initial part of this
period as shown in Fig. 1.
It should be noted that the respondents in the survey were asked to select their
appropriate income group rather than report their exact income level. For this, the midpoint
of each group was taken to represent the monthly income variable of those who selected that
group.10
4. Estimation results and discussion
As shown in Table 2, the probability of subscriber churning was found to be dependent on the
level of subscriber satisfaction with service attributes that include call quality, tariff level,
handsets, brand image as well as income, duration of subscription, and duration of handset used.
And as expected, the estimated coefficients are negative for service attributes and subscription
duration, and positive for income and duration of handset used.
9
The original number of respondents was 1335, but only 973 of them answered all the questions that corresponded to
the variables included in the model.
10
Another way of quantifying monthly income is to dichotomize the subscribers into two groups, a low-income group
and a high-income group, with the threshold monthly income level set at 3 million won. Almost the same result
obtained from this method.

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761
Table 2
Estimation results for churn and customer loyalty models
Variable
(1) churn
(2) loyalty
Constant
0.282
(0.762)
À0.028***
(À3.375)
À1.052***
(À5.784)
À0.658***
(À3.271)
À0.108
(À0.596)
0.050
(0.256)
À0.140
(À0.744)
À0.881***
(À4.999)
À0.571***
(À3.198)
À0.007
(0.848)
0.015
(0.080)
0.002***
(3.762)
À0.002
(À0.667)
0.031***
(2.844)
À0.038
(À0.198)
973
251
À2.528***
(À7.168)
0.008
(1.248)
1.250***
(8.154)
0.088
(0.538)
0.213
(1.341)
0.033
(0.205)
0.238
(1.502)
0.379**
(2.343)
1.032***
(6.158)
0.0006
(0.746)
0.150
(0.619)
À0.0004
(À0.794)
0.002
(1.001)
À0.0002
(À0.021)
0.157
(0.892)
973
401
Duration of subscription
CS1 (call quality)
CS2 (tariff)
CS3 (billing)
CS4 (value-added services)
CS5 (customer services)
CS6 (handset)
CS7 (brand)
Age
Sex dummy (male=1)
Income
Monthly payment
Duration of handset used
Dummy for switching experience
Number of observations
Number of observations with dependent variable=1
t-values in parentheses.
*Significant at the 10% level; ** significant at the 5% level; *** significant at the 1% level.
It is often difficult for mobile phone users to discern differences in call quality and tariff level
across different mobile carriers since a direct comparison of these service attributes across
different carriers is rarely available and tariff plans are usually offered as a menu of contracts with
different combinations of rate elements.11 However, the estimation shows that users’ perception of
the quality and price of their mobile service directly affects their intention to switch.
11
Rate elements here refer to monthly rental charge, per-minute rates for different call types (mobile to land, on-net
mobile-to-mobile calls, off-net mobile-to-mobile calls), and so on.

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It is interesting that handsets are also a significant determinant of churn even though the ability
of mobile operators to differentiate their services via handsets is quite limited and of short
duration. The results indicate that the users take handsets seriously, whether it be aesthetic aspects
or advanced features, and that they attribute these factors to their mobile operators, KT Freetel,
Hansol and LG Telecom. In fact, as mentioned in Section 2, the stylish design and small size of
the handsets offered by PCS service providers KT Freetel, Hansol and LG Telecom enabled them
to outpace the incumbent operators in attracting new subscribers. After a year, the incumbents
soon caught up with these entrants by offering similar handsets. The competitive edge in handsets
a mobile operator may have over its rivals was short-lived, but the behavior of the mobile carriers
and the results of the estimation point to the value of creating even a subtle difference between
handsets.12
The finding that brand image remains important, even after controlling for other factors
affecting brand image such as call quality and handsets, implies that brand management in itself is
an important area in mobile business, in which corporate resources need to be committed
separately. As more and more new technologies are incorporated into mobile phone services, it
becomes harder for consumers to discern quality differences among similar service offerings.
Within this environment, building a distinctive brand name is likely to be a fruitful investment.
However, when viewed from the perspective of effective competition, it needs to be noted that a
strong brand image, once built up, can act as a mobility barrier that may reduce competition, in
particular when a dominant carrier possesses it. Recall that a related policy measure has been
taken in Korea as was explained in Section 2.
Furthermore, the estimation results indicate that a longer subscription duration tends to be
associated with a lower probability of churning. Simply, this means that the longer a customer has
subscribed to a mobile carrier, the more likely the subscriber will adhere to that carrier. Barring
the self-selection problem, this may indicate the existence of a so-called customer lock-in in the
mobile telephony market. As can be seen below, the tendency of less switching among those with
longer subscriptions is not attributed to self-selection since the subscription duration does not
explain customer loyalty. Rather, it does demonstrate the existence of customer lock-in. Notable
among the many causes of a customer’s lock-in with a mobile operator are switching costs, buyer
inertia, or loyalty originating from satisfaction with that company.
As for the determinants of customer loyalty as measured by intention to recommend the present
company to other people, only satisfaction with call quality, handsets, and brand image of that
12
One might attribute the significance of handsets in the present estimation result to the generous handset subsidies
the Korean mobile operators had competitively offered to new and switched subscribers around the time of our survey
in a race to build a larger subscriber base. However, this argument is not convincing in interpreting the present results
because (1) The model in the paper links the probability of churning to the level of customer satisfaction with handset
(its overall attributes) not to handset subsidies themselves, and (2) the users were often able to change handsets with
handset subsidies without switching their mobile carriers by terminating and re-contracting their subscription with the
same carrier. The latter point highlights the profusion of handset subsidies prior to June 2000, implying that consumer
dissatisfaction with inadequacy of subsidies would have been rare. Even though handset subsidies were very
commonplace, however, different mobile operators were provided with different handsets from mobile phone
manufacturers at least because of differences in timing of new handset roll-outs (probably due to differences in volumebased bargaining power across the mobile operators with the manufacturers).

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Table 3
Log likelihood ratio tests
(1) churn
Restricted Log likelihood (A)
Unrestricted Log likelihood (B)
Log likelihood ratio statistic ðÀ2 à ðA2BÞÞ
Degrees of freedom
Critical value from w2 table
Hypothesis: ‘‘All coefficients of explanatory variables equal zero’’
(2) loyalty
À555.50
À463.33
184.34
14
29.14
Rejected
À659.33
À549.30
220.06
14
291.4
Rejected
company is statistically significant. The estimated coefficients of these variables have higher levels
of significance than those in the estimation of churn.
Unlike the churn model, the subscription duration has no significant effect on these loyal
customers, indicating that long-time subscribers stick with their current companies purely out of
satisfaction with service performance, not by lock-in. This result implies that the lock-in effect
caused by a long subscription duration is concentrated on those customers who wish to remain
with their present company but not loyal enough to recommend it. The lock-in effect for this
group of customers probably comes from the switching costs that dominate the benefits from
churning.
In the churn model, the result of a positive estimated coefficient for the duration of handset
used indicates that the longer a subscriber has used the present handset, the more likely he is to
switch carriers. The benefit from having a new handset must be greater for those who have older
handsets.
In terms of the estimated coefficients of demographic variables, the probability of switching
carriers is not related to a subscriber’s age in both models. However, monthly income has a strong
positive relationship with the probability of churning. An obvious interpretation is that older
persons and/or higher-income earners perceive carrier switching as less costly.
Lastly, the likelihood ratio tests for estimation are reported for both the churn and loyalty
models (model (1) and (2) respectively) as shown in Table 3. The likelihood ratio tests reject the
hypothesis that the coefficients of the explanatory variables are all zero at the 1% level. For model
(1), the restricted log likelihood is À555.50, and the unrestricted log likelihood is À463.33. The w2
statistic is therefore 184.34. With 14 degrees of freedom, the critical value from the w2 table is
29.14, so the joint hypothesis that the coefficients of explanatory variables in model (1) are all zero
is rejected. Likewise, for model (2), the joint hypothesis that the coefficients of the explanatory
variables in model (2) are all zero is rejected.
5. Concluding remarks
As with many other services or products, mobile consumers tend to stick with the present
service provider unless they find a serious flaw or experience dissatisfaction with the services
offered by that company. And this tendency will strengthen if the act of switching brings about

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additional costs such as a change in telephone number. Thus far, the main cause of customer
churning in the Korean mobile market has been roughly known to be the desire to change
handsets and dissatisfaction with specific service attributes such as call quality or price level.
However, there has been no formal analysis of the cause of churning. In this study, an empirical
analysis was conducted to identify the determinants of churning and customer loyalty in the
Korean mobile telephony market.
From the estimation results, many implications were drawn in regard to competition policy as
well as the corporate strategies of mobile operators. However, some business strategies can be in
conflict with competition policy. In particular, customer lock-in and the entry-deterring effect of a
brand image need to be addressed in competition policies for the mobile telephony market. For
instance, policy measures to ease the switching barriers of consumers such as the introduction of
number portability will reduce customer lock-in, and publishing test results on the mobile
operators’ call quality and a multi-faceted comparison of their price plans will enable consumers
to choose or switch to the best company mostly based on more objective factors rather than brand
image.
For Korea, however, a perplexing dilemma for policy makers is that the introduction of number
portability might aggravate the ‘tipping’ of the market structure further toward SK Telecom, the
largest mobile operator. Those who want to switch are more likely to choose SK Telecom than
either of the two new entrants as recent trends in market structure demonstrate (see Table 2). In
regards to the worrisome prospect of worsening market structure, the best possible course of
action would be to help consumers to make a better-informed choice and then to tackle the
ensuing problem of market concentration by structural measures. In other countries, typical
structural measures include the introduction of MVNO (mobile virtual network operator) in the
UK, Hong Kong, and Denmark. It is also possible to separate, as in the UK, dominant mobile
operators into network operation and retail divisions and to require that affiliated and
independent retailers be treated in a non-discriminatory manner.
The mobile sector has been growing in a deregulated environment, but is coming under
increasing scrutiny by regulatory authorities in many countries as the mobile network becomes as
integral a component of the national telecommunications system as the fixed-line networks.13
Thus far, the issue of effective competition in the mobile sector has been restricted mostly to fixedto-mobile access (termination) sub-markets. However, more regulatory vigilance on the retail side
of the mobile market is called for as well, particularly in terms of the growing concentration of the
market structure and the presence of barriers to customer mobility.
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See Scott and Respini (2000).

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