A STUDY OF FACTOR AFFECTING CUSTOMER SWITCHING

BEHAVIOR OF MOBILE TELECOMMUNICATION 3.5G

SERVICES

Jungwoo Lee, Eok Baek

Yonsei University, Republic of Korea

Sujung Sung

Autoeversystems, Republic of Korea

Keywords: Switching Behavior, Attractive of Alternatives, Network Externality, Switching Cost, Moderated Effect,

3.5G Mobile Telecommunication.

Abstract: Recently, Mobile Telecommunication businesses contend with each other to expand their customer base by

using an aggressive marketing strategy. In order to determine if this strategy is effective, customer's and

their switching behavior needs to be studied. This study identifies and analyzes direct, indirect factors

affecting customer switching behavior such as attractiveness of alternatives, network externality, switching

cost. The research results show that attractiveness of alternatives, network externalities have a direct impact

on customer switching behavior. These factors also have a moderated effect on customer switching behavior

but the switching cost does not influence customers directly.

1 INTRODUCTION

As the service industry becomes diverse and

enhanced, competition increases among providers

and brand preference is reduced (Fornell, 1992),

prompting companies to practice defensive

marketing in an attempt to maintain existing

customers and attract new ones. In the mobile

communication service industry, the cost for signing

up a new customer is ten times greater than

maintaining an existing client, thus customer

retention has become an essential element of

survival in the industry (Bolton, 1998). Accordingly,

there is a need to examine customer behavior

associated with switching to the competition. There

are three main objectives of this study.

The first is to look into the dynamics of the

mobile communication market based on previous

studies conducted on the switching barrier.

The second is to explain how network externality

is expressed in 3.5G services and exchanges

influences with customer switching behavior.

Finally, this study attempts to conduct empirical

analyses base on the correlations among the factors

that affect switching behavior based on the two

aforementioned theories.

2 LITERATURE REVIEW AND

HYPOTHESES

2.1 Switching Behavior

Carpenter & Lehmann(1985) defined switching

behavior as 'customer shift to other companies'

products' and Reichheld & Sasser(1990) as

'customer defection'. Switching behavior can be

explained as a concept that counters customer

retention and intent to repurchase, and customer

retention refers to the overall notion that

encompasses the behavior of actual usage as well as

the attitude toward the intent of continued usage

(Oliver, 1999; Allen & Rao, 2000). Studies of

customer retention in the service industry have

focused on customer satisfaction and switching

behavior as major factors that affect how customers

can be retained. According to past studies, although

the intensity varies in the relationship between

241

Lee J., Baek E. and Sung S. (2008).

A STUDY OF FACTOR AFFECTING CUSTOMER SWITCHING BEHAVIOR OF MOBILE TELECOMMUNICATION 3.5G SERVICES.

In Proceedings of the International Conference on e-Business, pages 241-246

DOI: 10.5220/0001909502410246

 SciTePress

customer satisfaction and customer retention, the

former is generally regarded as a contingent factor

for the latter (Anderson and Sullivan, 1993; Jones,

1998; Oliver et al., 1993; Kim, Sang-Hyeon, 2002).

This implies that high customer satisfaction has a

negative effect on switching behavior, an opposing

concept of customer retention and intent to

repurchase. Accordingly, it can be concluded that

the higher the degree of satisfaction about the

current mobile communication service, the lower the

probability of switching to 3.5G services. This study

focuses on the switching behavior prompted by 3.5G

services, and the definition of switching behavior

shall include both churning to other service

providers and upgrading to 3.5G services within the

same provider.

H 1: Customer satisfaction toward current mobile

communication service has a negative(-) effect on

switching behavior to 3.5G services.

2.2 Switching Barrier

Jones(2000) defined switching barrier as the

psychological and financial difficulties that a

customer faces in the process of changing service

providers. Switching barrier consists of the

switching cost and alternative attractiveness, and

these factors play moderating roles between

customer satisfaction and switching behavior

(Anderson et al., 1994; Jones et al., 2002).

Jones(1998) categorized the switching cost into

continuity cost, contractual cost, searching cost,

learning cost, initial cost and dissociation cost.

However, since mobile communication providers

offer similar services and usage of 3.5G services is

not significantly different from conventional mobile

phone, the searching and learning costs can be

disregarded. Furthermore, since consumers are not

involved in face-to-face interactions with their

service providers, the dissociation cost of severing

personal relationships does not have to be

considered. Accordingly, this study only deals with

continuity, contractual and initial costs.

Alternative attractiveness is defined as

consumers' awareness of service providers that can

replace current providers (Jones et al, 1998) and

related to the concept of service augmentation in

related literatures (Porter, 1980). Service

augmentation refers to providing additional services

to be distinguishable from other service providers. In

turn, when there is an alternative that provides better

services, consumers will disconnect the relationship

with current providers and opt for the better option

(Bradford, 2000). On the other hand, if the

alternative lacks attractiveness, consumers will

continue to use current services albeit not

completely satisfactory (Porter, 1980).

H 2: Switching barrier has effects in the

relationship between customer satisfaction toward

the current service and switching to 3.5G services.

H 2-1: Switching cost has a positive(+) effect

between customer satisfaction and switching

behavior.

H 2-2: Alternative attractiveness has a negative(-)

effect between customer satisfaction and switching

behaviour

H 3: Switching barrier has effects on switching

behavior to 3.5G services.

H 3-1: Switching cost has a negative(-) effect on

switching behavior to 3.5G services.

H 3-1a; Continuity cost has a negative(-) effect on

switching behavior to 3.5G services.

H 3-1b: Contractual cost has a negative(-) effect on

switching behavior to 3.5G services.

H 3-1c: Initial cost has a negative(-) effect on

switching behavior to 3.5G services.

H 3-2: Alternative attractiveness has a positive(+)

effect on switching behavior to 3.5G services.

2.3 Network Externalities

First studied by Katz and Shapiro(1985), they

defined network externalities as the concept that "the

value consumer gains from a product or service is

proportional to the size of the network that the

product or service belongs to". In other words,

network externalities come into consideration when

the value of a product or service depends on the

number of its users.

Consumers generally wish to be linked to large-

scale networks because they expect products or

services with large user bases provide higher quality

and value. Accordingly, network externalities are

referred to as consumption externalities of quantity,

which does not provide much value on its own but

signifies network characteristics of a product or

service whose value increases with expansion of the

user base (Shapiro, 1999).

The value of 3.5G services would be marginal

without a significant user base of video telephony,

which is the core of 3.5G services. Once the number

of video telephony users increases, the value of 3.5G

services will also increase due to the bandwagon

effect. Thus the following hypotheses were

established

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Table 1: Manipulative definition of variable.

H 4: Network externalities have a negative(-) effect

between customer satisfaction toward current

service and switching behavior to 3.5G services.

H 5: Network externalities have a positive(+) effect

in switching behavior to 3.5G services.

3 RESEARCH METHODS

In order to verify the hypotheses of this study,

manipulative definition was established for each

variable based on the previous studies described in

Chapter 2 to elicit evaluation items for this study.

Online surveys were conducted from November 12

to 16, 2007 for male and female mobile telephone

users between the ages 10 and 60. Among 180

questionnaires retrieved, those with incomplete or

insincere responses were discarded and the

remaining 158 were used as the survey data for the

study. Likert 7-point scale was used for every

question except for the items regarding

demographics, and SPSS 12.0 was used to perform

statistics analysis, reliability analysis, factor analysis

and regression analysis.

4 DATA ANALYSIS

4.1 Characteristics of Sampe Space

The statistics related to the 158 respondents for the

survey. The male-female ratio was somewhat

Category Research Variables Manipulative Definition Items Evaluated

Questionnaire

Structure

Customer

Satisfaction

Overall Customer

Satisfaction

Customer recognition and

sentiment after service

experience

•Overall level of satisfaction

regarding fundamental services an

provider

I-1, 2

Alternative

Attractiveness

Degree of awareness

regarding providers that

offer alternative services

• Whether 3.5G services are offered

•Awareness of characteristics an

quality of 3.5G services(High-spee

data service, video telephony, USIM

card, roaming)

II-1, 2, 3, 4

Continuity

Cost

Cost associated with trouble

in switching service

providers

•Psychological/financial cost

associated with notification of new

phone number

• Cost associated with lost contacts

• Reluctance to use video telephony

due to compromised anonymity

II-5, 6, 7, 8

Contractual

Cost

Cost of losing financial

enefits by staying with the

current service provider

•Cost of losing current service

provider's membership services

• Cost of losing discount benefits

II-9, 10

Switching

Barrier

Switching

Cost

Initial Cost

Additional costs

associated with switching to

a new service provider

• Sign-up fee for the new service

provider

• Cumbersome sign-up procedure

• Cost of signing up for new value-

added services and loss of curren

contents

II-11, 12, 13

Network Externalities

Customer awareness of the

user base for new services

•Change in behavior according to

network externalities

•Degree of awareness regarding the

number of users for new services

III-1, 2, 3

Switching Behavior

Customer's switching

ehavior from current

service

•Intent of continued use of services

from the current provider

•Possibility of switching to new

service

•Conviction of switching to new

service

IV-1, 2, 3, 4

A STUDY OF FACTOR AFFECTING CUSTOMER SWITCHING BEHAVIOR OF MOBILE TELECOMMUNICATION

3.5G SERVICES

243

balanced at 53.2% and 46.8%, but 83.8% of the

respondents were in the 20~40 age group.

4.2 Analyses of Variable Scale

Reliability and Propriety

The internal consistency method was used for

verifying reliability of this study. The survey

questions were used without modification because

there was no indication of reliability being

undermined, and the Cronbach's Alpha coefficient

for the factor variables used in the study were

between 0.6 and 0.9, displaying a high level of

internal consistency.

In addition, factor analysis was performed for

each item that constitutes a variable to analyze

propriety and find out whether each variable was

isolated and assessing a unique property.

VARIMAX rotation based on major element

analysis was used to elicit factors, and factor loading

was set at 0.4 for those with Eigen value of 1.0 or

higher, which yielded 5 factors. The analytical result

indicated that the two variables that explain

switching cost - contractual cost and initial cost -

should be grouped as a single factor. It was

determined that the respondents regarded both

contractual and initial costs as being associated with

switching to or signing up for a new service

provider, and the two variables were redefined as the

initial switching cost.

4.3 Verification and Analysis of

Hypotheses

Verification for the 5 research hypotheses were

conducted in two stages. First, multiple regression

analysis was used to verify the factors that directly

affect switching behavior. H1, H3 and H5 are

classified as direct factors. The second stage

involved analyzing the moderating effect that

influence the relationship between current mobile

service satisfaction and switching behavior, for

which H2 and H4 correspond with. Hierarchical

multiple regression analysis was used to analyze the

moderating effect. In addition, the average value of

each factor was calculated for regression analysis.

Adoption criteria of hypothesis were set at 95%

reliability and a significance level of 0.05 or lower.

Summarizing the analytical result, 5 of the 7

hypotheses established for the study were adopted

and the remaining 2 were discarded.

Table 2: Result of Analyses.

Hypotheses Result

Hypotheis 1 Adoption

Hypotheis 2 Partialy adoption

Hypotheis 2-1 Discard

Hypotheis 2-2 Adoption

Hypotheis 3 Partialy adoption

Hypotheis 3-1 Discard

Hypotheis 3-2 Adoption

Hypotheis 4 Adoption

Hypotheis 5 Adoption

4.4 Additional Analysis: Effect of

Intensifying the Switching Cost

Research Model

Additional analysis was performed for this study to

assess how switching costs customer satisfaction and

switching behavior based on the fact that the initial

switching cost in particular has influence on the two

factors. The respondents were divided into two

groups based on whether they felt the initial

switching cost was high or low to analyze the effects

between degree of satisfaction and switching

behavior. The result indicated that there is

significant influence between level of satisfaction

and switching behavior for the group that felt the

initial switching cost was high, but the influence

insignificant for the other group.

Figure 1: Research Model for Study Results.

The result corresponds with the basic research

model demonstrating that customers who feel that

there is a high cost of switching mobile service

providers recognize the cost as a switching barrier

and will not display switching behavior. Therefore,

it can be learned from the additional analysis of this

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section that the initial switching cost reinforces the

research model of this study.

5 CONCLUSIONS

This study analyzed a comprehensive model of

switching behavior to examine consumer awareness

of the new 3.5G mobile communication services and

the factors that affect the switching behavior to 3.5G

services. The study was conducted in two stages.

First, the study assessed the factors that directly

affect the level of satisfaction as well as network

externalities, perceived switching cost and

alternative attractiveness of 3.5G services. Second,

the interaction effects of network externalities,

alternative attractiveness and switching cost were

examined as moderating variables between

satisfaction and switching behavior.

The expectation of 3.5G services providing various

distinguishing features from conventional mobile

communication to offer new sources of satisfaction

has been reflected in this study. In the case of video

telephony, the flagship 3.5G service, network

externalities significantly affect consumers'

switching behavior in terms of the perception of how

many others were using the service.

As for the switching cost, number portability and

sign-up fee waiver offered by the service providers

allow consumers to alleviate the burden of notifying

their new numbers to their contacts or signing up for

new services.

Whereas previous studies on the subject have

focused solely on the switching barrier, this study

bears significance in that network externalities were

analyzed from the consumer behavior perspective.

Moreover, the study provides a foundation for

establishing a practical strategy for securing a 3.5G

service customer base to gain a competitive edge.

However, this study failed to cover factors such as

consumer usage characteristics and more than 80%

of the survey respondents were in the age group

between 20 and 40. It is therefore necessary to

diversify the age groups of the sample space to

increase the accuracy of the study. Questions have

been raised regarding the effectiveness of the

strategies implemented by the mobile

communication providers to maintain and acquire

customers for 3.5G services, but this study did not

examine whether customers display switching

behavior according to the strategies. In turn, it would

be necessary in future studies to assess whether

service providers' strategies are effective based on

the mechanisms explained in this study as well as

the number of 3.5G service subscribers and changes

in the actual profit structure.

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