impact of brand switching in the telecommunication

IMPACT OF BRAND SWITCHING IN THE

TELECOMMUNICATION INDUSTRY

(A CASE STUDY OF XL AXIATA IN JAKARTA)

By:

Shandy Sutanto

ID: 014201300140

A Skripsi presented to the

Faculty of Business President University

In partial fulfillment of the requirement for

Bachelor Degree in Economics in Management

December, 2016

i

SKRIPSI ADVISOR

RECOMMENDATION LETTER

This skripsi entitled “IMPACT OF BRAND SWITCHING IN THE

TELECOMMUNICATION INDUSTRY – A Case Study of XL

Axiata in Jakarta”, Prepared by Shandy Sutanto in partial fulfillment

of requirement for the degree of Bachelor in Faculty of Business has

been review and found to have satisfied the requirement for a thesis to

fit to be examined. I therefore recommend this thesis for Oral Defense.

Cikarang, December 2016

Recommended by,

Dr. Dra. Genoveva, M.M

Head of Management Study

Acknowledge by,

Dr. Dra. Genoveva, M.M

Program Thesis Advisor

ii

DECLARATION OF ORIGINALITY

I declare that this skripsi, entitled “IMPACT OF BRAND

SWITCHING IN THE TELECOMMUNICATION INDUSTRY –

A Case Study of XL Axiata in Jakarta”, it to the best of my

knowledge and beliefs, an original piece of work that has not submitted,

either in a whole world in a part, to another university to obtain degree.

Cikarang, December, 2016

Shandy Sutanto

iii

PANEL OF EXAMINERS

APPROVAL SHEET

The Panel of Examiners declare that the Skripsi entitled “IMPACT OF

BRAND SWITCHING IN THE TELECOMMUNICATION

INDUSTRY – A Case Study of XL Axiata in Jakarta” that was

submitted by Shandy Sutanto in Management from the Faculty of

Business was assessed and approve to have passed the Oral

Examination on December, 2016

CHRISTINA LIEM, S.T., M. COMM.

Chair – Panel of Examiners

SISKA PURNAMA MANURUNG, S.KOM., MM

Examiner 1

DR. DRA. GENOVEVA, M.M

Examiner 2

iv

ABSTRACT

This research entitled “Impact of Brand Switching in The Telecommunication

Industry – A Study Case of XL Axiata in Jakarta” was conducted with 100

respondents who were a user of XL Axiata cellular network in Jakarta Area. There

were three independent variables being studied, these are price, inconvenience, and

service failure, and the dependent variable is brand switching towards XL Axiata.

Data analysis technique used were multiple linear regression with least squares

equation and test hypothesis using t-statistic for testing the regression coefficients

and F-statistic testing to test the impact together with a significance level of 5%. It

also tested the classical assumptions that included tests of normality,

multicollinearity test, test of heteroscedasticity and autocorrelation test. This shows

the available data has been qualified using multiple linear regression equation

model. The result indicates that Inconvenience (X2) has no significant impact on

brand switching towards XL Axiata in Jakarta. The variables Price (X1) and Service

failure (X3) have significant impact on brand switching towards XL Axiata in

Jakarta. Predictive ability of three variables Brand Switching towards XL Axiata in

Jakarta area in this study was 42.5% while the remaining 57.5% were affected by

other factors not included in the research model being studied.

Keywords: price, inconvenience, service failure, brand switching,

telecommunication industry

v

ACKNOWLEDGEMENT

First of all, I would like say thank you to the God because of His grace and

blessing, I can complete the skripsi entitled “Impact of Brand Switching in the

Telecommunication Industry (A Case Study of XL Axiata in Jakarta) very well,

both morally or spiritually so in this occasion the author would like to thank to:

Mrs. Geraldine B. Advincula MBA., as my advisor in this research that guides

me for suggestion and recommendation, also motivates me during the process of

this thesis.

My beloved parent, Iwan Sutanto and Lili Susanti who support me in getting

education until I finish my studies at President University.

My bestfriends, Yoko Kwanarta, Josephine Eunike, Agatha Rannu, Ravina

Tara, for their support in the completion of my thesis.

Last but not least, any parties which cannot be mentioned one by one by the

author, including people who are supporting me in filling the questionnaire.

Cikarang, December, 2016

Shandy Sutanto

vi

TABLE OF CONTENTS

SKRIPSI ADVISOR RECOMMENDATION LETTER ................................... i

DECLARATION OF ORIGINALITY ............................................................... ii

PANEL OF EXAMINERS .................................................................................. iii

ABSTRACT .......................................................................................................... iv

ACKNOWLEDGEMENT .................................................................................... v

TABLE OF CONTENTS ..................................................................................... vi

CHAPTER I - INTRODUCTION ....................................................................... 1

1.1 Background ................................................................................................. 1

1.1.1 Problem Identification ........................................................................... 3

1.1.2 Research Questions ............................................................................... 4

1.1.3 Research Objectives .............................................................................. 4

1.2 Significance of the Study ............................................................................ 4

1.3 Limitation .................................................................................................... 5

1.4 Organization of the Skripsi ......................................................................... 5

CHAPTER II - LITERATURE REVIEW .......................................................... 6

2.1 Introduction ................................................................................................. 6

2.2 Brand Switching .......................................................................................... 6

2.3 Price............................................................................................................. 7

2.4 Inconvenience ............................................................................................. 8

2.5 Service Failure ............................................................................................ 8

2.6 Research Gap .............................................................................................. 9

CHAPTER III - METHODOLOGY ................................................................. 10

3.1 Introduction ............................................................................................... 10

3.2 Theoretical Framework ............................................................................. 10

3.3 Hypothesis ................................................................................................. 11

3.4 Operational definitions of variable ............................................................ 11

3.5 Intrument ................................................................................................... 12

vii

3.5.1 Primary Data ....................................................................................... 12

3.5.2 Questionnaire ...................................................................................... 14

3.5.3 Data Analysis ...................................................................................... 17

3.6 Sampling ................................................................................................... 17

3.6.1 Research Framework ............................................................................ 19

3.7 Validity and Reliability ............................................................................. 20

3.7.1. Validity ................................................................................................ 20

3.7.2 Reliability ............................................................................................ 21

3.8 Descriptive Testing ................................................................................... 22

3.8.1 Mean .................................................................................................... 22

3.8.2 Standard Deviation .............................................................................. 23

3.9 Classical Assumption Testing ................................................................... 23

3.9.1 Normality Test .................................................................................... 23

3.9.2 Multicollinearity Test .......................................................................... 24

3.9.3 Heteroscedasticity Test ....................................................................... 25

3.9.4 Multiple Regression Analysis ............................................................. 26

3.9.5 Adjusted Coefficient of Determination (R2)....................................... 26

3.10 Durbin-Watson Test .................................................................................. 27

3.11 Testing the Hypothesis .............................................................................. 27

3.11.1 F-Test .................................................................................................. 27

3.11.2 T-Test .................................................................................................. 28

CHAPTER IV - ANALYSIS and INTERPRETATION ................................. 30

4.1 Data Analysis ............................................................................................ 30

4.2 Variable Frequency ................................................................................... 30

4.2.1 Reliability test ..................................................................................... 30

4.2.2 Validity test ......................................................................................... 31

4.3 Respondent Profile .................................................................................... 33

4.4 Descriptive Analysis ................................................................................. 40

4.5. Classical Assumption Testing ................................................................... 41

4.5.1 Normality Test .................................................................................... 41

4.5.2. Multicollinearity Test .......................................................................... 43

4.5.3 Heteroscedascity Test .......................................................................... 44

viii

4.5.4 Testing the Hypothesis ........................................................................ 45

4.5.5 Coefficient of Correlation (R) and Coeffcient of Determination (R2) 46

4.5.6 F-Test .................................................................................................. 47

4.5.7 T-Test .................................................................................................. 48

4.6 Interpretation of Results ............................................................................ 50

4.6.1 Price ..................................................................................................... 51

4.6.2 Inconvenience ..................................................................................... 52

4.6.3 Service Failure .................................................................................... 52

CHAPTER V - CONCLUSION AND RECOMMENDATION ..................... 53

5.1 Conclusion ................................................................................................ 53

5.2 Recommendation ....................................................................................... 54

5.2.1 For XL Axiata ..................................................................................... 54

5.2.2 For Future Researchers ....................................................................... 54

REFERENCES .................................................................................................... 55

APPENDIX .......................................................................................................... 58

1

CHAPTER I

RESEARCH BACKGROUND

1.1 Background

Indonesia’s mobile landscape has seen a significant shift over the past year. Market

conditions of telecommunication industry have become very competitive and

companies are trying increase their market share. Due to intense competition in the

telecommunication industry, customers frequently switch over from one brand to

another.

The number of cellular service users in Indonesia has always been increasing each

year. These are the four biggest mobile telephone service providers in Indonesian

Market:

Telecommunication

Industry

Market

Share

(2014)

Market

Share

(2015)

Change

%

Telkomsel 45% 45% 0%

Indosat 18% 21.6% 3.6%

3 (Hutchison) 11.5% 14.4% 2.9%

XL Axiata 20.6% 14% 6.6%

Figure 1.1: Telecommunication Industry Market Share in Indonesia

Source: GSMA Intelligence (2015)

2

Figure 1.2: Monthly active smartphone users in Indonesia

Source: Emarketer (2015)

With more than 17-year operating experience in Indonesia market, PT XL Axiata

is one of the biggest cellular network provider in Indonesia. Currently, PT XL

Axiata is regarded as one of the leading company in cellular provider for dat and

telephone in Indonesia. XL Axiata entered the business market on 6 October 1989

with the name PT Grahametropolitan Lestari. In 1996, XL entered

telecommunication sector after given the operation permission GSM 900 officially

to launch the GSM service. With that, XL Axiata became the first private company

in Indonesia which serves cellular network service. In September 2005, XL

launched an IPO (Initial Public Offering) in Bursa Efek Indonesia (BEI). In that

time, XL became the subsidiary of Indocel Holding Sdn. Bhd., and now called

3

Axiata Investments (Indonesia) Sdn. Bhd. in 2009, PT Excelcomindo Pratama

changed the name into PT XL Axiata for synergy purpose.

This research is going to find the factors behind brand switching phenomenon in

perspective of telecommunication industry, a case study of XL Axiata in Jakarta.

XL Axiata is the fourth rank in the market share of telecommunication industry in

2016, based on the data from GSMA Intelligence (2015). Meanwhile Hutchison

just became the third replacing XL Axiata, even though the price and other factors

of those telecommunication industry are similar. To find the factors behind the

brand customer switching behavior of telecommunication industry, this research is

necessary.

1.1.1 Problem Identification

While market leader Telkomsel has held on to its top position, with its market share

steady at 45% percent, XL Axiata, number 2 just a year ago, has slipped to fourth

with its share falling from 20.6% to 14 % in Q2. According to GSMA Intelligence

(2015), it has lost more than 17 million connections in 12 months. The sharp drop

in XL’s subscriber numbers has been a huge change for the one-time market

challenger, which took the industry by storm back in 2006 - 2007, when it cut prices

sharply to take share from incumbent Telkomsel, which is owned by Telkom

Indonesia, as well as Indosat. Meanwhile on the decline of XL Axiata market share,

Indosat gain more subscribers by 3.6% from 18% to 21.6%. From figure 1.1, it also

can be seen that the growth of mobile subscriber is around 7.6 million, from the

4

change in market share. Hence it can be concluded that the rest (17 million

subscribers) switch their brands.

1.1.2 Research Questions

1. Is there any significant impact of price towards brand switching for XL Axiata?

2. Is there any significant impact of inconvenience towards brand switching for

XL Axiata?

3. Is there any significant impact of service failure towards brand switching for

XL Axiata?

4. Is there any simultaneously significant impact of price, inconvenience, and

service failure for XL Axiata?

1.1.3 Research Objectives

1. To find out is there any significant impact of price towards brand switching for

XL Axiata.

2. To find out is there any significant impact of inconvenience towards brand

switching for XL Axiata.

3. To find out is there any significant impact of service failure towards brand

switching for XL Axiata.

4. To find out is there any simultaneously significant impact of price,

inconvenience, and service failure for XL Axiata?

1.2 Significance of the study

This research will be important for several subjects.

First, XL Axiata, because as the studied case, the company can find the reason why

their market share declined.

5

Second, telecommunication industry, so they can find the impact of price,

inconvenience, and service failure towards brand switching.

Third, for future researchers so they can continue and refer to this research for the

future research in analyzing the impact of brand switching.

1.3 Limitation

This study will be limited to millennials who are the ex-users of XL Axiata network

service, living in Jakarta area with Price, Inconvenience, and Service failure as the

independent variables and Brand switching as the dependent variable. Due to

limitation of time, the respondents will be taken from population in Jakarta who

used XL Axiata as their last cellular network, and the questionnaire will be

distributed through online questionnaire. Researcher chooses only Jakarta because

it is the most populous city in Indonesia.

1.4 Organization of the skripsi

The organization of this skripsi include: chapter 1, discuss about the background,

problem, and objective of this research. In chapter 2 review of the literature for each

variable used (Price, Inconvenience, Service Failure) were defined and described.

Chapter 3 provides the method used in this research which is quantitative approach

with the use of primary data. Chapter 4 discuss the findings of this research and also

to test the hypothesis. Finally, Chapter 5 present the discussions based on the

findings and its recommendation for future research.

6

CHAPTER II

LITERATURE REVIEW

2.1 Introduction

This chapter will be going to evaluate the impact of brand switching of the

customers and presents work of previous researchers regarding brand switching and

the variables.

2.2 Brand Switching

Brand switching is the process of selecting to change from routine use of a product

or a brand to another different but similar product (Saeed, & Azmi, 2014). Brand

switching could happen to anyone when they feel the other brand’s product has

more advantage than the current brand’s product. According to Mouri, termination

of customer relationship with the current service provider and starting a new

relationship with another service provider is called brand switching, this theory also

applied by Awwad (2014). The customers can choose to end their relationship with

the cellular network providers because of various reasons and change the brand on

temporary or permanent basis. Rajkumar (2011) defines brand switching when

customers change their preferences from one particular brand then onto the next.

Before switching the brand, customer will consider the pro and contra between the

brands. According to Haider et al (2012), the most important factor of switching

behavior of students and professionals is technology aspect. Customer wants to be

in part of the latest technology, like switching to the other brand which already has

7

4G connectivity. Customer brand switching behavior presents danger for a

business. If the service providers do not keep their customer satisfied, there is a

chance for competitors to get benefit, (Kim, 2012).

2.3 Price

In all market aspects, including telecommunication market, price is the biggest

factor that affect brand switching. Sathish (2011) suggest that call rates are the most

influencing factor for brand switching in the telecommunication industry. To

communicate with each other is the main purpose of a mobile phone, hence, call

rates is the most influencing factor if there is another tempting offer from another

brand. Cahyono dan Soesanto (2012) said in his research on Sampoerna cigarrete,

“The price of Sampoerna cigarrete which is more expensive than the other cigarrete

brand will make the customer to switch to another brand. It explains the reason

behind the battle of price and internet packages between cellular provider

companies. In some research, it is stated that higher price means higher quality and

higher status (Nadia, 2012). XL Axiata needs to have a higher quality if they want

to have a high price to meet the customer expectation.

Rajkumar (2011) suggest that price is not always the main influence of brand

switching. He explained that there are customers who are quality conscious who

prefers to pay high prices for high quality. It means the customer prioritizes the

network quality, or the service failure before the price. According to Swastha, the

price of a brand which is too expensive with the same characteristic as the other

brand, would cause the customer to switch brand. Nuraeni (2013) also find the same

idea in her research.

8

2.4 Inconvenience

According to Awan (2016), Inconvenience means feel dissonance or un-prompt

respond regarding associated services or facilitations. Some of them are un-ethical

issues such as packages are activated without customer intention, balance lost is

happening often, etc. Inconvenience includes all incidents where the customer felt

inconvenienced by the service provider's location, hours of operation, waiting time

for operator service (Kouser, Qureshi, Shahzad, & Hasan, 2012). The

inconvenience is perceived by the customer individually to meet with their

expectation. Abdin and Mullick (2016), also have the similar theory, which stated

that such inconvenience includes the factors such as time elapse, long hours of

operations, waiting for the service or location of the operator. The customers feel

inconvenient mostly because of the problem which spends too much time for the

customer. Inconvenience is an important factor affecting service provider users’

switching behaviors (Liang et al., 2013). Hence, Inconvenience become one of the

variable which have big impact on brand switching. These ideas also supported by

the findings of Hasan (2016), that inconvenience have positive effect on brand

switching in service industry.

2.5 Service failure

A service failure occurs when services or products provided by companies do not

meet customers’ needs or standards by Zheng, as cited by Hung and Lee (2015).

Those kinds of service failure will lead the guest to be dissatisfied and shows

negative behavioral intentions. It is the customer who will determine if something

is wrong. When a service provider does not understand the needs and wants of

9

guests, it will lead to service failure as well. Since XL Axiata is a service industry,

which deals with intangibility, inseparability, variability, and heterogeneity, it is

impossible to achieve zero error. This theory is applied by Panda (2014). The core

service failures are those problems which are created by the service provider, such

as poor network or facilities. According to Hess et al, the service failures such as

those might create a huge recovery expectation on the customer. Stratemeyer et al

(2014) also had the same idea.

2.6 Research Gap

Most of the research studies conducted in the past found a significant impact of

price, inconvenience, and service failure variables towards brand switching in the

telecommunication industry. However, the earlier studies have been conducted in

different countries, different case, and different consumer groups. Although some

studies found some variable does not have a significant impact on brand switching.

Thus, this study seeks to find out the impact- Price, Inconvenience, and Service

failure – towards brand switching for XL Axiata in Jakarta area. It would be

interesting to note how the results of Price, Inconvenience, and Service Failure

relate to the previous studies done on the topic.

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CHAPTER III

METHODOLOGY

3.1 Introduction

Research methodology has been considered very important for the whole result

because it can really affect the results of research. This chapter presents

comprehensive methodology of research including theoretical framework,

hypothesis, instruments, and sampling tools.

3.2 Theoretical Framework

Figure 3.1: Theoretical Framework

Source: Awan (2016)

Brand Switching

(Y)

Price

(X1)

Inconvenience

(X2)

Service Failure

(X3)

H1

H2

H3

H4

11

3.3 Hypothesis

HA1: There is significant impact of Price towards Brand Switching

HO1: There is no significant impact of Price towards Brand Switching

HA2: There is significant impact of Inconvenience towards Brand Switching

HO2: There is no significant impact of Inconvenience towards Brand Switching

HA3: There is significant impact of Service failure towards Brand Switching

HO3: There is no significant impact of Service failure towards Brand Switching

HA4: There are simultaneously significant impact between price, inconvenience,

and service failure towards brand switching.

HO4: There are no simultaneously significant impact between price,

inconvenience, and service failure towards brand switching.

3.4 Operational definitions of variables

Table 3.1: Operational definitions of variable

Variable Definition Indicators Author

Price

(X1)

Price occupy the most

affecting variable for

the customer to

switching brands.

Price is an important

factor in the mobile

telecommunication

• Higher price

• Price increasing

overtime

• Unfair pricing

• Call rate price

higher

• Internet rate price

higher

(Nadia,

2012)

(Hasan,

2016)

12

industry, including call

rate, SMS rate, etc.

Inconvenience

(X2)

Inconvenience means

feel dissonance or un-

prompt respond

regarding associated

services or

facilitations.

Inconvenience

indicates the

importance for cellular

network provider to

build an extensive

service network across

the country to serve

customers better.

• Packages activation

is not on time

• Packages activated

without intentions

• Balance lost

• Mistake on the bill

• Insufficient number

of kiosk

(Awan,

2016)

(Liang,

2012)

Service failure

(X3)

Service failure factor

related to many

symptoms like

• Network busy

• Less coverage

(Awan,

2016)

13

network busy, less

coverage, etc. and

customer density

impacted a lot in that

sense.

Service failure is

essentially a failure in

product quality, which

clearly indicates the

utmost importance for

cellular network

provider.

• Low signal quality

in calls

• Too many spam

• Failure in delivering

text messages

(Liang,

2012)

Brand

Switching

(X4)

Brand switching is a

more dependable

source of better

performance,

competitive advantage

and a success factor for

the cellular company in

the rising competitive

marketing.

• First choice

• Continue

relationships

• Recommendation

• Encourage friends

• Importance of

relationship

(Qadri

&

Khan,

2014)

14

3.5 Instrument

In order to examine the impact of brand switching in the telecommunication

industry, two types of data have been used, which are primary data and secondary

data. Primary data means original data that has been collected specially for the

purpose in mind. This data is generally afresh and collected for the first time so it

means the data is new one. The data is useful for current study as well as for future

studies.

3.5.1 Primary Data

Primary data can be collected through observations, surveys and focus groups. For

this research: “Impact of Brand Switching in the Telecommunication Industry (A

case study of XL Axiata in Jakarta)”, the data is obtained directly from the

questionnaire that are used for survey, since this is a quantitative research. A

questionnaire is simply a tool for collecting and recording information about a

particular issue of interest. This questionnaire will be distributed to the number of

sample.

3.5.2 Questionnaire

Table 3.2 Questionnaire

Variables Questionnaires Sources

Price Q1 The price of XL Axiata is higher than

the other brand.

Nadia, (2012)

and

Hasan, (2016) Q2 The price of XL Axiata increased

overtime

15

Q3 The offerings of XL Axiata (internet

package, call package) does not

worth the price.

Q4 The call rate price of XL Axiata is

higher compared to another brand.

Q5 The internet rate price of XL Axiata

is higher compared to another brand.

Inconvenience Q1 The activation of call and internet

package of XL Axiata after

registration is slow

Awan, (2016)

and

Liang, (2012)

Q2 Call or internet packages are

activated automatically without

intentions from customers

Q3 Balance lost usually happens

Q4 XL Axiata often have a mistake on

the bill

Q5 XL Axiata have insufficient number

of kiosk/service center

Service

Failure

Q1 The network of XL Axiata is usually

busy

Awan, (2016)

and

Liang, (2012) Q2 The network signal of XL Axiata

have less coverage

16

Q3 XL Axiata have low signal quality in

making or receiving calls

Q4 XL Axiata have too many spam text

messages

Q5 XL Axiata often have failure in

delivering text messages

Brand

Switching

Q1 If I need another network provider,

XL Axiata would not be my first

choice

Qadri & Khan,

(2014)

Q2 I do not plan to continue my

relationship with XL Axiata in the

future.

Q3 I would not recommend XL Axiata in

the Jakarta area

Q4 I would not encourage my friends and

relatives to use XL Axiata

Q5 The relationship with XL Axiata is

not important for me

17

3.5.3 Data Analysis

The researcher will use some tools that will help to analyze the questionnaire.

1. Microsoft Excel 2016: help researcher to input the data and calculate data using

the formulas.

2. SPSS Version 22.0: help researcher to analyze the data that is prove conclusion

formed as numerical measurement of data gathered and inputted.

3.6 Sampling

Based on the dependent variable in this research which is brand switching, hence

the targeted respondent is people who used XL Axiata as their past network

provider. The researcher used google forms to make questionnaire to the ex-users

of XL Axiata in Jakarta. The link of questionnaires will be distributed by social

media as Facebook, LINE, etc. The sampling method used convenience sampling

from non-probability sampling. For the sample is unknown population. With this,

the researcher divided the respondent in three parts. The first parts consist of two

filtered questions, second parts is a demographic profile and the last parts are for

the variables. The researcher distribute the questionnaire to 143 respondents, and

43 respondents stop filled the questionnaire in filter question because they are not

living in Jakarta Area and did not use XL Axiata as their ex-provider. So, the

researchers just spread the questionnaire to the respondents who are living in

Jakarta and used XL Axiata, and the researchers got 100 respondents. 30

respondents are for the pre-test and if found reliable and valid it will continue to the

remaining 70 respondents for the real test.

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The sample size based on this formula (Hair et al, 2010):

N = 5 x Q

Where: N = number of sample

Q = number of question

From this formula, minimum number of respondent in this research is 100.

19

3.6.1 Research Framework

Source: Constructed by Researcher

Problem Identification

Literature Review

Pre Questionnaire

Validity

Reliability

Real Questionnaire

Data Collection

Data Analysis and Interpretation

Conclusion and Recommendation

No No Yes

20

3.7 Validity & Reliability

3.7.1 Validity

According to (Hair et al, 2010), validity is the extent which a scale or set of

measures accurately represents the concept of interest. According to Cohen et al as

cited again by Adi M, (2016), quantitative research possesses a measure of standard

error which is inbuilt and which has to be acknowledged. In quantitative data,

validity might be improved through careful sampling, appropriate statistical

treatments of data. Each question of the questionnaire can be said valid if the result

of corrected item-total correlation is more than value of r table.

(Source: Maholtra, 2012)

Where:

df = degree of freedom

n = number of respondent

df = n - 2

21

3.7.2 Reliability

Reliability is synonymous with the consistency of a test, survey, observation, or

other measuring device. It is to check the correlation of statement in the

questionnaire. The researcher uses Cronbach’s Alpha formula to determine the

reliability for this study. The Cronbach’s Alpha formula was used to measure this

reliability testing.

(Source: Sugiyono, 2011)

Where:

k = the number of items

r = average correlation between any two items

α = reliability of the average or sum

A rule of thumb for interpreting alpha for dichotomous questions (i.e. questions

with two possible answers) or Likert scale questions is:

• For the Alpha > 0.90 it is mean Perfect Reliability

• Alpha around 0.70-0.90 it is mean High Reliability

• Alpha around 0.50 – 0.70 it is mean Moderate Reliability

• And if alpha <0.50 it mean Low Reliability

(Source: Hair Et All, 2013)

𝛂 =𝒌. 𝒓

𝟏 + (𝒌 − 𝟏)𝒓

22

3.8 Descriptive Testing

3.8.1 Mean

According to (Saylor, 2010), the mean is the sum of the observation divided by

the total number of observations.

(Source: Saylor, 2010)

Where: ΣXi = the sum of the observations

n = the total number of observations

x bar = mean value

23

3.8.2 Standard Deviation

According to (Saylor as cited again by Adi M, 2016), the standard deviation is the

squared root of the variance. Indicates how close the data is to the mean. The

formula or standard deviation is as follows:

(Source: statistics.laerd.com)

Where: s = sample standard deviation

= sum of...

= sample mean

n = number of scores in sample.

3.9 Classical Assumption Testing

3.9.1 Normality Test

Normality as a basic assumption in regression, where residuals are distributed in a

normal and independent way in the case of measuring the normality of a study,

researcher can check whether the distributions are illustrated through a straight line

in the plot or not. The basic indicator that stated if the data is normally distributed

is when the histogram chart shows the bell-shaped curve and if the P Plot of

regression standardized residual shows the residual distributed in the pattern of

diagonal line. According to Ghozali I. as cited again by Adi M.(2016) stated that

24

normality test can be detected through scatter plot performance on the diagonal line

in the graph or by analyze the histogram. Based on:

1. If the data are scattered around diagonal line and come after the line or the

histogram graph perform a normal distributions form, meaning the normality

assumptions is acceptable.

2. If the data are not scattered around diagonal line and or not come after the

line or the histogram graph does not perform a normal distribution form, meaning

that the normality assumptions is not acceptable.

3.9.2 Multicollinearity Test

Multicollinearity inflates the variances of the parameter estimates and hence this

may lead to lack of statistical significance of individual predictor variables even

though the overall model may be significant. Multicollinearity can be occurred

when the coefficient of correlation between independent variables are high or

greater than 0.95, tolerance values are more than 0.1 and VIF value is less than 10

(Santoso as cited again by Adi M, 2015)

(Source: cytel.com)

Where: R2i= coefficient of determination

VIP > 10 means considered unsatisfactory, indicating that the independent

variable should be removed fro the analysis.

VIP < 10 means there is no multicollinearity problem around

25

3.9.3 Heteroscedasticity Test

Heterocedatisity test is to see whether there is inequality of variance of the residuals

of the observation to other observations. Regression models that meet the

requirements are where there is equality of variance of the residual one observation

to another observation fixed.

If Heteroscedasticity exist in the regression model, the variance and standard error

will tend to increase as the t value will not get lower than the actual t-value. The

consequences are the T-test and F-test will be inaccurate and fail to reject the null

hypotheses (David M. Levine, 2012). A simple test for heteroscedasticity is to plot

the standardized residuals (on vertical axis) against the dependent variable

(horizontal axis). If no heteroscedasticity occurs, the plot will appear to spread

randomly. If a systematic pattern (wave, straight, narrow, widen) appears in the

scatter plot then heteroscedasticity exists (David M. Levine, 2012).

26

3.9.4 Multiple Regression Analysis

Multiple regression is a statistical method used to examine the influence between

one dependent variable Y and one or more independent variables Xi. The regression

parameters or coefficients bi in the regression equation are estimated using the

method of least squares (medcalc.org, 2013):

Y = β0 + β1X1 + β2X2+ β3X3

Where,

Y = Brand Switching

X1 = Price

X2 = Inconvenience

X3 = Service Failure

3.9.5 Adjusted Coefficient of Determination (R2)

This test is used to determine how far the independent variables could describe the

dependent variable. If the result of R2 is minus , it means that the ability of

independent variables to describe the dependent variable are limited. If the value of

R2 goes near one, it means that the independent variables give almost all information

that needed to predict the dependent variable (Ghozali as cited again from Adi M,

2016).

27

3.10 Durbin-Watson Test

A test that the residuals from a linear regression or multiple regression are

independent. The test statistic is:

(Sources: tankonyvtar.hu)

3.11 Testing the Hypothesis

A statistical hypothesis is an assumption about a population parameter. This

assumption may or may not be true. Hypothesis testing refers to the formal

procedures used by statisticians to accept or reject statistical hypotheses. The null

hypothesis, denoted by H0, is usually the hypothesis that sample observations result

purely from chance. The alternative hypothesis, denoted by H1 or Ha, is the

hypothesis that sample observations are impacted by some non-random cause.

3.11.1 F-Test

F-Test is used to statistically test the null hypothesis that there is no linear

relationship between X and y variables (β = 0). The value of F-counted will

determine whether the hypothesis is accepted or rejected. The researcher used level

of significant α = 5%. If the significant value is greater than significant level, then

all independent variables has no significant impact to dependent variable.

Otherwise, if the significant value is less than significant level, then all independent

http://stattrek.com/Help/Glossary.aspx?Target=Parameter

28

variables has significant impact to dependent variable. Based on problem identified

and theoretical framework, the hypothesis of this research will be stated as follow:

(H05 : β1 = β2 = β3 = β4 = 0): Price, Inconvenience, Service failure has no significant

impact on consumers attitudes towards brand switching in the telecommunication

industry.

(HA5 : β1 = β2 = β3 = β4 ≠ 0): ): Price, Inconvenience, Service failure has significant

impact on consumers attitudes towards brand switching in the telecommunication

industry.

3.11.2 T-Test

T-test is used to measure the impact of independent variable toward dependent

variable. Simply, T-test will determine and explain the impact of each independent

variable individually explains dependent variable. Hypothesis is a temporary

statement of problem being examined in the study, and to analyze and determine

whether the hypothesis is proven to be accepted or rejected, it will need T-test

analysis. The value of T-counted will determine whether the hypothesis is accepted

or rejected. The significant level being used for the T-Test is 0.05 (5 %). So, if the

significant value is less than 0.05, it means the independent variable will has

significant impact to dependent variable. And if significant value is more than 0.05,

it means the independent variable has no significant impact to dependent variable.

Based on the problem identified and theoretical framework, the hypothesis of this

study will be stated as follows:

29

(HO1 : β1 = 0): Price has no significant impact towards brand switching in the

telecommunication industry.

(HA1 : β1 ≠ 0): Price has significant impact towards brand switching in the


(HO2 : β2 = 0): Inconvenience has no significant impact towards brand switching in

the telecommunication industry.

(HA2 : β2 ≠ 0): Inconvenience has significant impact towards brand switching in the


(HO3 : β3 = 0): Service failure has no significant impact towards brand switching in

the telecommunication industry.

(HA3 : β3 ≠ 0): Service Failure has significant impact towards brand switching in the


30

CHAPTER IV

ANALYSIS AND INTERPRETATION

4.1 Data Analysis

This chapter is an extensive report of the result of the study. It discussed all the

finding through statistical analysis. Research presents here full analysis and

discussion of the gathered data which analyze the impact of brand switching on

telecommunication industry: A Case Study of XL Axiata in Jakarta area.

4.2 Variable Frequency

4.2.1 Reliability test

Reliability test was conducted by employing SPSS and arranged data from

Microsoft Excel to tabulate Cronbach’s Alpha of the research instruments.

According to Hair Et All (2013), alpha more than 0.90 it is mean Perfect

Reliability, Alpha around 0.70-0.90 it is mean High Reliability, Alpha

around 0.50 – 0.70 it is mean Moderate Reliability, and if Alpha <0.50 it

mean Low Reliability. The result of reliability test of each variable in this

study can be seen as follow:

31

Table 4.1 Reliability Test

(Source: Data Processing Result of SPSS 22.0)

Table 4.1 shows reliability coefficient of Cronbach’s Alpha of all variables and

all of the variables are over 0.6 which means that this parameter had a good

reliability rate.

4.2.2 Validity Test

In this study, researcher use the Pearson’s Product Moment Coefficient Correlation

to study item of questionnaire validity, the formula used in this research will check

the validity of questionnaire. The validity variables come from the comparing r

(which is shown in Appendix) with r table (r-value of Pearson Product Moment in

table 4.2). The item is valid if the r is higher than rtable. By using significant level,

(α) = 5% for two tailed and n= 30 (researcher use 30 respondents as the sample pre-

test), the df will be:

Df = n – 2 = 30 – 2 = 28

Variables Cronbach

’s Alpha

Remarks

Price (X1) 0.791 High Reliability

Inconvenience (X2) 0.620 Moderate Reliability

Service Failure (X3) 0.800 High Reliability

Brand Switching (Y) 0.904 Perfect Reliability

32

So, based on the table on appendix, rtable is 0.361. Consequently, the item should

have r greater than 0.361 to be valid. The result of validity test is summarize in

Table 4.2.2:

Table 4.2: Validity Test

Variables Items Pearson correlations rtable

Remarks

Price Q1 .814

0.361 VALID

Q2 .614

0.361 VALID

Q3 .770

0.361 VALID

Q4 .715

0.361 VALID

Q5 .829

0.361 VALID

Inconvenience Q6 .750

0.361 VALID

Q7 .786

0.361 VALID

Q8 .680

0.361 VALID

Q9 .784

0.361 VALID

Q10 .832

0.361 VALID

Service

Failure

Q11 .819 0.361 VALID

Q12 .725

0.361 VALID

Q13 .796

0.361 VALID

33

Q14 .475

0.361 VALID

Q15 .707

0.361 VALID

Brand

Switching

Q16 .722 0.361 VALID

Q17 .737

0.361 VALID

Q18 .804

0.361 VALID

Q19 .823

0.361 VALID

Q20 .754

0.361 VALID


The entire items are valid. Therefore, the researcher decided to choose all

the questions into the questionnaire for real samples.

4.3 Respondent Profile

This research is purposeful to see the impact of brand switching on

telecommunication industry, a case study of XL Axiata in Jakarta. Therefore, the

questionnaire distributed to unknown population and filtered to find the ex-users

of XL Axiata who lives in Jakarta. The questionnaires are applied for both male

and female. There are 143 respondents that have been participated to fill out the

questionnaire.

Out of 143 respondents, author filtered the respondents by looking the ex-users of

XL Axiata, and the result is 111 respondents. From the 111 respondents, author

filtered the respondents by looking the location of the respondents who are living

34

in Jakarta, and the final result is 100 respondents who are qualified to be collected

for this thesis.

4.3.1 Ex-users of XL Axiata

Figure 4.1: Ex-users of XL Axiata

(Source: questionnaire, 2016)

There are 143 respondents had been involved in the analysis. The result shows

there are 111 respondents who are ex-users of XL Axiata (78%) and followed by

users who did not use XL Axiata or currently in use for 32 respondents (22%).

78%

22%

Did you use XL Axiata as your network provider before?

Yes No

35

4.3.2 Respondents’ Location

Figure 4.2: Respondents’ Location

(Source: Questionnaire, 2016)

From the filtered respondents of the current status of their network provider, there

are 111 respondents who are eligible for this research. The result shows there are

100 respondents who are currently living in Jakarta (90%) area and followed by

11 respondents who are living outside Jakarta area (10%).

90%

10%

Do you currently live in Jakarta?

Yes No

36

4.3.3 Respondents’ Gender

Figure 4.3: Gender


After filtered for the current status, there are 100 respondents who had been

involved in the analysis. The result shows the ex-users of XL Axiata who are

living in Jakarta area were 53% or 53 male and followed by 47% or 47 female.

This means that majority of the respondents are male.

53%

47%

Gender

Male Female

37

4.3.4 Respondents’ Age

Figure 4.4: Age


The next group of respondents’ profile is categorized by age which can be seen in

Figure 4.4, it shows the largest number of ex-users of XL Axiata who are living

in Jakarta are in the age group from 21-25 years old (64%) consist of 64

respondents. Then, followed by the age group of 15-20 years old (22%) consist of

22 respondents, whereas the age group of 26-30 years old has become the third

largest (11%) consist of 11 respondents. And for the smallest number are 31-35

years (3%) consist of 3 respondents. This means that majority of the respondents

are 21-25 years old.

22%

64%

11%

3%

Age

15-20 years old 21-25 years 26-30 years 31-35 years

38

4.3.5 Respondents’ Location in Jakarta

Figure 4.5: Location in Jakarta


Jakarta area are divided into 5 for the demographic profile. There are North

Jakarta which have the biggest number of respondents (29%) consist of 29

respondents. Followed by East Jakarta (22%) consist of 22 respondents. Followed

by South Jakarta (21%) consist of 21 respondents. Central Jakarta have (19%)

consist of 19 respondents. And for the smallest number is West Jakarta which

have (8%) consist of 8 respondents. This means that majority of the respondents

are located in East Jakarta.

19%

30%

21%

22%

8%

Location

Central Jakarta North Jakarta South Jakarta East Jakarta West Jakarta

39

4.3.6 Respondents’ Current Cellular Network

Figure 4.6: Current Cellular Network


By being an ex-users of XL Axiata, the respondents are using the current service

provider they have chosen. The biggest number of switching users has moved to

Telkomsel (38%) consist of 38 respondents, followed on second by Indosat (35%)

consist of 35 respondents. And the third, 3 (Tri/Hutchison) for (18%) consist of

18 respondents, and for the Other network (9%) or indicates 9 respondents. This

means that majority of the respondents are using Telkomsel as their cellular

network.

37%

36%

19%

8%

Current Cellular Network

Telkomsel Indosat 3 (Tri/Hutchison) Others

40

4.4 Descriptive Statistics

Table 4.3: Descriptive Analysis

PT IT SFT BST

N Valid 100 100 100 100

Missing 0 0 0 0

Mean 3.5640 3.5360 3.6380 3.7400


Table above shows the respondents’ responses to five statements about the impact

of brand switching toward Price (X1), Inconvenience (X2), Service Failure (X3),

and Brand Switching (Y). Therefore, the most dominant variable in term of

significance is Service Failure (X3) with mean value of 3.6380.

All variable in this study measure with 5 point scales as cited in the table below

which was developed by (Tuan anh, V.C, 2016);

Table 4.4: Five Points Scales

Range Categories

1.00 – 1.80 Strongly Disagree

1.81 – 2.60 Disagree

2.61 – 3.40 Neutral

3.41 – 4.20 Agree

4.21 – 5.00 Strongly Agree

(Source: Tuan anh, V.C, 2016)

41

4.5 Classic Assumption Test

4.5.1 Normality Test

The normality test determine how the data is actually distributed. It means

that the data may be distributed normally or abnormally depending on the

situation. Consequently, P-P Plot (graphic) is used for determining whether the data

is distributed normally.

Figure 4.7 Normality Test: P-P Plot Graph


Graph of normal probability p-plot in figure 4.7 suggest that the data spread in

around the diagonal line and follow the direction of the diagonal line, then the

regression model meet the assumption of normality. In addition, the actual data

plot (represented by the dots) is spreading approximately surrounding the

42

diagonal direction of the line telling the distribution is normal. Moreover, The

P-P above also shows that the data points are not seriously deviated.

Figure 4.8: Normality Test: Histogram


Figure 4.5.2 shows that the curve formed a proper bell shape at the center, either

skewed to the left or to the right. It means that the data have variance of value make

it normally distributed which can be used to approximate various discrete

probability distributions and eligible to conduct study.

43

4.5.2 Multicollinearity Test

Table 4.5: Multicollinearity Test: Tolerance and VIF Value

Model Collinearity Statistics

Tolerance VIF

1

(Constant)

PT .693 1.443

IT .523 1.912

SFT .621 1.611


From the Table 4.5, all of the independent variables show that there is no variable

with Variance Inflation Factor (VIF) value less than 10 and tolerance value less

than 10%, indicating that there is no multicollinearity (Martz, 2013). Hence,

researcher can use the Multiple Regression Model to Analyze.

44

4.5.3 Heteroscedasticity Test

Figure 4.9 Heteroscedasticity Test: Scatterplot Graph


Heteroscedasticity test results on Figure 4.7 indicate that the points are not forming

a certain pattern and the points are spreading above and below the number 0 (Zero)

on the Y axis. Then it means that there is no heteroscedasticity accepted, it means

that the T-Test and F-Test are accurate and valid.

45

Table 4.6: Multicollinearity Test: Coefficient Correlations

Coefficient Correlationsa

Model SFT PT IT

1

Correlations

SFT 1.000 -.114 -.505

PT -.114 1.000 -.410

IT -.505 -.410 1.000

Covariances

SFT .009 -.001 -.004

PT -.001 .007 -.003

IT -.004 -.003 .008

a. Dependent Variable: BST


From the table 4.6, the coefficient correlations are far away below 0.60, indicating

there is no multicollinearity.

Thus, the assumption of normality, heteroscedasticity, and multicollinearity in

the regression model can be met from this model.

4.5.4 Testing the Hypothesis

This study uses multiple linear regression analysis because the model has two

variables. The hypothesis testing is conducted through F-Test and T-Test. The

effect of independent variable individually toward dependent variable will be used

the partial T-Test. F-Test will be used to test the impact of all independent variables

to dependent variable simultaneously. Each independent variable is significant if

value is less than 0.05.

46

4.5.5 Coefficient of Correlation (R) and Coefficient of

Determination (R2)

The score of adjust R square is also called as coefficient determinant. The output

for adjusted coefficient determinant (R²) between dependent variable (Brand

Switching towards telecommunication industry) and independent variables (Price,

Inconvenience, and Service Failure) is presented in Table 4.7 following:

Table 4.7: Coefficient of Correlation (R) and Coefficient of Determination

(R2)

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .665a .443 .425 .50789

a. Predictors: (Constant), SFT, PT, IT

b. Dependent Variable: BST


From the Table 4.7, the adjusted R2 is 0.425 or 42.5%. This mean, there is 42.5%

independent variables: Price, Inconvenience, and Service failure that affect the

dependent variable Brand Switching towards telecommunication industry. On the

other hand, 42.5% of the brand switching as dependent variable is explained by the

independent variables including Brand Switching towards telecommunication

industry whereas the other 57.5% is explained by other factors that are excluded

from model.

47

4.5.6 F-Test

Table 4.8: F-Test (ANOVA)

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 16.682 3 5.561 22.180 .000b

Residual 24.068 96 .251

Total 40.750 99


b. Predictors: (Constant), SFT, PT, IT


Hypothesis:

HA: Price, Inconvenience, and Service Failure have significant impact

towards Brand Switching.

HO: Price, Inconvenience, and Service Failure have no significant impact

towards Brand Switching.

From table 4.8, testing the independent variables together with dependent variable

is done by using the F-Test. The result of this F-test shows the F value = 22.180,

with a significance level of 0.000. The F table value is found on the F table with

df1 = 3 and df2 = 96. Thus, the F table value is 2.70. F value > F table (22.180 >

2.70) and significance level is 0.000 (< 0.005) means that together the Price,

Inconvenience, and Service Failure have significant impact towards Brand

Switching on XL Axiata.

48

4.5.7 T-Test

Table 4.9: T-Test

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.075 .313 3.435 .001

PT .352 .085 .378 4.136 .000

IT .131 .088 .157 1.490 .140

SFT .260 .092 .272 2.813 .006



From the result in Table 4.9, obtained the model multiple linear regression

Unstandardized Coeffcients as follows:

Y = 1.075 + 0.352 X1 + 0.260 X3

Where,

Y = Brand Switching

X1 = Price

X3 = Service Failure

From the above equation, it can be seen that the coefficient from the regression is

positive. And it can be interpreted that:

49

1. Price

Independent variable Price (X1) can impact the dependent variable with 0.352

regression coefficient. It means, each increase of 1 unit of Price (X1), while the

other variables are constant, it will cause an increase in Brand Switching (Y) equal

to 0.352.

2. Inconvenience

Independent variable Inconvenience (X2) can impact the dependent variable with

0.131 regression coefficient. It means, each increase of 1 unit of Inconvenience

(X2), while the other variables are constant, it will cause an increase in Brand

Switching (Y) equal to 0.131.

3. Service failure

Independent variable Service Failure (X3) can impact the dependent variable with

0.260 regression coefficient. It means, each increase of 1 unit of Service Failure

(X3), while the other variables are constant, it will cause an increase in Brand

Switching (Y) equal to 0.260.

From the model in table 4.9, it can be further described as follows:

1. Price

The first independent variable Price (X1) has significant (sig) value of 0.000 which

is less than p-value (0.05). It means the hypothesis H01 is rejected and hypothesis

HA1 is accepted. This mean that Price has significant impact toward Brand

Switching.

50

2. Inconvenience

The first independent variable Inconvenience (X2) has significant (sig) value of

0.140 which is less than p-value (0.05). It means the hypothesis H01 is rejected and

hypothesis HA1 is accepted. This mean that Inconvenience has no significant impact

toward Brand Switching.

3. Service Failure

The first independent variable Service Failure (X3) has significant (sig) value of

0.006 which is less than p-value (0.05). It means the hypothesis H01 is rejected and

hypothesis HA1 is accepted. This mean that Service Failure has significant impact

toward Brand Switching.

4.6 Interpretation of Results

The researcher conducted a study about the impact of brand switching in the

telecommunication industry, a case study of XL Axiata in Jakarta area.

Independent variables studied in this research consist of price, inconvenience, and

service quality, while dependent variable is brand switching towards

telecommunication industry. The main objective of this research is to find out

whether the price, inconvenience, and service failure have significant and

simultaneous significant impact on brand switching in the telecommunication

industry.

From the Table 4.7., the adjusted R2 is 0.425 or 42.5%. This mean, there is 42.5%

independent variables, Price, Inconvenience, and Service failure affect the

dependent variable, Brand switching towards XL Axiata. On the other hand, 42.5%

of the brand switching as dependent variable is explained by the independent

51

variables including Price, Inconvenience, and Service failure whereas the other

57.5% is explained by other factors are excluded from model.

Population in this research were people who are living in Jakarta. The total

population is unknown. Sample size or the number of the sample has been taken

and calculated using sample formula in Chapter III. With the unknown number of

population and the margin of error tolerance is 5% (0.05), the total sample of this

research is minimum 100 respondents. The 30 respondents are for pre-test, because

the result of the pre-test is valid and reliable, therefore the researcher continue the

respondent for the real test.

Based on the ANOVA result on Table 4.8, it is shown that F Calculated around

22.180 with its level of significant is 0.000 because the number of probability is

0.000 < 0.05. It means that price, inconvenience, and service failure has significant

impact on brand switching in the telecommunication industry.

4.6.1 Price

The probability value of price is 0.000 which is lower than p-value 0.05. So its

means that price has a significant value towards brand switching for XL Axiata.

This result is similar with the research conducted by Hasan (2016), about price

towards brand switching in the telecommunication industry with reference to

Bangladesh people living in Pabna district. The research conducted by Hasan

(2016) indicated that Price, Inconvenience, and Service failure have significant


52

4.6.2 Inconvenience

The probability value of Inconvenience is 0.140 which is lower than p-value 0.05.

So it means that Inconvenience has no significant impact towards brand switching

for XL Axiata. This result of Inconvenience has a significant impact towards brand

switching is different with the research conducted by Awan (2016) about

inconvenience towards brand switching in mobile service provider with reference

to people living in Southern Punjab-Pakistan. It is different because the research

from Awan (2016) show the results indicated that Price, Inconvenience, and Service

failure have significant impact on brand switching in the telecommunication

industry.

4.6.3 Service Failure

The probability value of Service failure is 0.006 which is lower than p-value 0.05.

So its means that service failure has a significant impact towards brand switching

for XL Axiata. This result of service failure has a significant impact towards brand

switching is similar with the research conducted by (Hasan, 2016) about service

failure towards brand switching in the telecommunication industry with reference

to Bangladesh people living in Pabna district. The research conducted by Hasan,

(2016), indicated that Price, Inconvenience, and Service failure have significant


53

CHAPTER V

CONCLUSION AND RECOMMENDATION

5.1 Conclusion

The purpose of this study is to identify whether there is correlation between three

independent variables (Price, Inconvenience, and Service Failure) towards

dependant variable (Brand Switching). Regarding from the result and discussion

on Analysis and Interpretation, the conclusion would be drawn as follow:

1. Based on the result of this study, it was determined that there is a significant

impact of Price towards Brand Switching for XL Axiata.

2. Based on the result of this study, it was determined that there is no significant

impact of Inconvenience towards Brand Switching for XL Axiata.

3. Based on the result of this study, it was determined that there is a significant

impact of Service Failure towards Brand Switching for XL Axiata.

4. Based on the result of this study, it was determined that there is a

simultaneously significant impact of Price, Inconvenience, and Service

Failure towards Brand Switching for XL Axiata.

54

5.2 Recommendation

After conducting the study, the researchers have several recommendations that

can be used as consideration regarding the impact of Price, Inconvenience, and

Service Failure towards Brand Switching (A case study of XL Axiata in Jakarta

area)

5.2.1 For XL Axiata

There are two independent variables which have significant impact towards brand

switching. The variables are Price and inconvenience. Based on data collected and

developed using SPSS, the researcher recommends for XL Axiata to keep their

price rate, especially the call rate price to be able to compete with the competitors’

price. This can be achieved not only by lowering the price, but also creating a new

internet package which also have call package for free. XL Axiata also need to

develop the network signal to have more coverage in Jakarta Area, and also

increasing their network from 4G to 4.5G.

5.2.2 For the future researchers

1. For future research, it is needed doing a further research in other factors

besides Price, Inconvenience, and Service failure towards brand switching

in the telecommunication industry, thus, it will grasp more information

about the impact of brand switching in the telecommunication industry.

2. Future studies are advised to examine the other brands with take another

example of the Price, Inconvenience, and Service failure. Hence, the

variable that impact brand switching is also different. It can be used as a

comparison and complements in this research.

55

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58

APPENDIX

Appendix 1 Questionnaire

Dear Sir or Madam,

I am a student of President University concentrating in Management. I am

conducting a study to find out what are the impact that contributing in brand

switching of XL Axiata in Jakarta. I need your help to fill this questionnaire as the

data for my skripsi. Please kindly fill this questionnaire with objective. Thank you.

Did you use XL Axiata as your network provider before?

□ Yes

□ No

Do you currently live in Jakarta?

□ Yes

□ No

1. Age

□ 15-20 years old

□ 21-25 years old

□ 26-30 years old

□ 31-35 years old

□ 36-40 years old

2. Gender

□ Male □ Female

3. Address

□ Central Jakarta

□ North Jakarta

□ South Jakarta

□ East Jakarta

□ West Jakarta

4. What is your current cellular network?

□ Telkomsel

□ Indosat

59

□ 3 (Tri/Hutchison)

□ Others

This questionnaire is using Likert-Scale consist of 20 statements to respond to. In

this section you are asked to give an opinion on how much the following statement

in accordance to the price, inconvenience, service failure, and brand switching.

Please rate the following statement according to

1 = Strongly Disagree

2 = Disagree

3 = Neutral

4 = Agree

5 = Strongly Agree

PRICE

No. Statements 1 2 3 4 5

1. The price of XL Axiata is higher than the

other brand.

2. The price of XL Axiata increased overtime

3. The offerings of XL Axiata (internet package,

call package) does not worth the price.

4. The call rate price of XL Axiata is higher

compared to another brand.

5. The internet rate price of XL Axiata is higher

compared to another brand.

INCONVENIENCE


1. The activation of call and internet package

of XL Axiata after registration is slow

2. Call or internet packages are activated

automatically without intentions from

customers

3. Balance lost usually happens

4. XL Axiata often have a mistake on the bill

5. XL Axiata have insufficient number of

kiosk/service center

SERVICE FAILURE


1. The network of XL Axiata is usually busy

60

2. The network signal of XL Axiata have less

coverage

3. XL Axiata have low signal quality in making

or receiving calls

4. XL Axiata have too many spam text messages

5. XL Axiata often have failure in delivering

text messages

BRAND SWITCHING


1. If I need another network provider, XL

Axiata would not be my first choice

2. I do not plan to continue my relationship

with XL Axiata in the future.

3. I would not recommend XL Axiata in the

Jakarta area

4. I would not encourage my friends and

relatives to use XL Axiata

5. The relationship with XL Axiata is not

important for me

Appendix 2 Data Tabulation

No. Price Inconvenience Service Failure Brand Switching

1 2 2 5 4 4 3 3 3 3 2 1 1 1 1 1 4 2 1 1 1

2 4 5 4 3 4 5 4 3 5 4 3 4 3 4 5 4 4 5 4 4

3 1 2 2 2 2 2 4 4 3 4 5 5 4 3 3 3 3 2 4 4

4 4 3 4 5 4 4 3 5 4 5 5 4 5 3 5 4 5 4 5 4

5 3 3 2 1 2 3 3 2 2 2 3 4 3 2 2 4 4 3 3 3

6 3 5 5 4 3 5 4 3 4 5 4 3 3 4 5 4 3 4 5 4

7 3 4 4 5 4 3 4 4 5 4 4 4 4 3 4 5 4 3 4 5

8 4 4 3 4 4 4 4 3 3 5 4 4 3 4 4 5 5 4 4 3

9 3 4 4 5 4 4 4 4 4 4 4 3 3 4 5 4 4 4 3 4

10 5 4 5 3 4 5 4 3 4 4 4 3 3 3 4 3 5 4 5 4

11 4 5 4 3 4 5 4 4 5 5 4 3 3 4 4 5 4 4 3 5

12 5 3 4 5 3 4 3 5 5 4 3 4 3 4 5 4 4 4 3 5

13 5 3 4 4 5 3 4 3 5 3 5 4 5 4 5 4 5 3 4 5

14 3 3 3 3 3 2 2 2 2 2 4 4 4 5 4 3 3 3 3 3

15 2 3 1 2 2 3 2 4 3 3 4 4 5 4 4 5 5 4 5 5

16 5 4 4 4 3 4 5 4 4 4 5 4 3 3 4 5 4 4 5 5

17 2 4 2 2 2 3 2 4 3 3 4 4 4 3 3 2 2 3 3 3

18 4 3 3 3 5 4 3 4 4 5 4 3 3 4 3 4 4 5 4 4

19 2 3 3 3 3 3 3 1 2 3 3 2 3 3 4 2 3 3 3 3

20 4 5 4 3 3 4 5 4 5 5 4 4 3 3 4 5 5 4 4 5

61

21 3 2 2 2 2 4 3 2 3 3 4 5 4 3 3 3 3 2 3 2

22 5 4 5 4 4 5 4 5 3 4 5 3 4 5 4 4 5 4 3 4

23 4 5 3 4 3 4 5 4 4 5 3 4 3 4 5 3 4 4 5 4

24 5 4 4 3 5 4 5 3 4 4 4 3 5 4 4 3 3 5 4 5

25 4 3 3 3 4 4 3 2 2 2 3 4 3 3 3 2 4 3 3 3

26 2 4 3 3 2 5 5 5 4 4 4 4 4 4 3 4 3 3 4 3

27 3 4 5 4 3 3 5 5 4 4 4 4 4 4 3 4 3 3 3 3

28 4 5 4 3 2 1 1 3 1 2 1 1 1 4 2 4 1 1 4 5

29 4 5 3 3 3 4 3 5 2 2 2 4 4 3 4 3 3 2 2 2

30 4 3 2 4 4 4 3 4 2 3 4 5 5 5 3 5 5 3 5 4

31 2 3 2 5 2 3 2 4 1 3 2 4 2 5 2 3 2 2 3 4

32 4 5 4 3 4 5 4 5 5 5 4 3 4 5 4 5 4 3 4 5

33 4 5 3 4 4 4 3 5 4 4 3 5 4 5 5 5 3 4 5 4

34 5 3 4 3 5 4 3 5 4 4 3 3 5 4 5 3 4 3 5 4

35 3 2 3 3 4 3 3 2 4 4 5 4 3 5 4 4 2 3 3 2

36 5 3 5 4 5 3 4 3 4 4 5 4 4 5 5 4 3 5 4 5

37 4 5 5 5 4 4 4 4 3 4 4 4 4 5 5 5 4 3 5 4

38 3 4 4 3 4 5 5 5 4 4 5 5 4 4 4 4 5 4 5 5

39 3 3 2 3 3 2 2 3 3 3 3 3 3 3 3 4 4 3 3 3

40 2 2 2 3 2 3 1 3 4 3 4 4 4 4 5 5 5 5 5 5

41 4 4 2 3 2 4 2 3 2 3 2 3 4 3 2 4 4 3 3 3

42 3 5 4 3 4 4 5 3 4 4 3 5 4 3 4 5 3 5 4 5

43 4 4 4 5 4 2 2 2 2 2 2 2 2 2 2 4 4 3 4 5

44 4 5 3 5 4 5 3 4 5 4 4 3 4 5 4 4 5 3 4 3

45 3 3 2 3 3 4 3 3 3 4 3 3 3 3 3 2 3 3 3 3

46 3 3 4 4 4 3 3 4 4 3 4 4 3 4 3 4 4 4 4 3

47 3 3 2 2 3 2 4 5 2 2 5 5 5 3 2 3 3 3 3 3

48 4 4 3 4 3 5 4 4 3 4 5 5 3 2 2 4 1 3 4 5

49 3 3 4 4 3 3 4 4 4 3 2 3 2 3 2 5 5 4 4 5

50 3 3 4 3 2 3 4 3 4 3 3 4 4 4 4 4 4 4 4 4

51 4 5 4 3 4 3 5 4 3 4 4 3 5 4 3 4 3 4 5 4

52 4 3 3 5 4 4 4 4 3 3 5 4 4 3 5 4 3 5 4 4

53 4 5 4 4 3 5 4 3 4 5 4 5 4 4 3 4 5 3 4 4

54 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 4 3 5 4

55 3 4 3 4 3 2 3 3 3 4 3 2 2 3 3 3 2 3 3 3

56 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

57 3 4 5 2 4 5 2 2 1 3 4 4 2 5 2 4 4 5 5 4

58 5 4 5 5 4 4 4 3 5 5 4 5 5 3 3 3 4 4 3 5

59 4 4 3 5 5 3 4 4 4 4 4 5 4 5 1 5 2 5 5 4

60 4 3 5 4 3 3 3 3 4 4 4 4 4 4 3 3 3 3 4 4

61 4 3 4 3 4 2 5 5 2 2 3 3 3 4 2 3 3 4 4 4

62 3 5 5 4 4 2 1 2 1 1 3 5 5 4 2 3 3 3 3 3

63 4 4 4 5 5 2 2 2 2 2 4 4 4 2 2 5 5 5 5 5

64 4 4 2 2 2 2 2 2 1 2 2 2 2 4 2 4 3 2 3 4

65 4 3 5 4 5 4 4 5 5 4 4 4 3 3 4 5 4 4 3 3

62

66 4 4 4 3 4 4 4 4 4 3 5 4 4 4 4 4 5 4 3 5

67 4 3 4 3 5 4 3 4 5 4 4 4 5 5 4 4 4 3 3 3

68 4 3 3 4 4 5 5 4 4 5 4 3 3 5 5 4 4 4 5 5

69 4 3 4 4 4 5 4 4 3 4 4 4 5 4 5 5 5 4 4 3

70 4 5 4 3 5 4 4 4 4 5 5 4 3 5 4 4 5 4 4 4

71 2 2 2 2 2 2 3 2 2 2 2 4 2 2 2 2 4 2 2 4

72 4 4 4 4 5 4 4 2 4 2 2 2 2 4 2 5 5 4 5 4

73 3 2 4 4 4 4 4 4 3 4 3 3 4 3 4 4 4 3 4 3

74 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

75 2 2 3 3 2 2 2 2 1 3 3 3 3 3 3 3 3 3 3 5

76 2 3 4 4 3 3 4 3 4 3 3 3 3 3 3 4 2 2 3 3

77 2 4 2 2 2 2 2 5 1 1 1 1 3 5 2 2 2 3 3 4

78 4 5 3 5 5 4 5 5 4 5 4 3 4 5 4 4 5 4 5 3

79 2 3 4 2 2 4 2 4 3 4 3 2 2 3 3 2 4 3 3 4

80 5 4 3 4 4 3 5 4 4 4 5 4 3 3 4 4 5 4 4 3

81 4 3 5 4 4 3 3 4 5 5 4 4 5 3 4 3 3 4 4 5

82 2 3 1 5 3 4 2 4 1 4 4 3 4 5 2 4 3 1 3 2

83 2 4 4 2 2 2 5 5 4 5 5 5 4 5 4 5 3 3 3 2

84 4 4 4 3 4 3 3 5 3 2 5 4 3 4 4 3 3 5 4 3

85 5 3 4 5 5 4 5 4 5 5 5 4 3 4 5 4 5 4 4 5

86 5 4 5 5 4 4 3 5 4 5 5 4 5 3 4 4 5 4 4 5

87 5 3 4 4 5 4 3 3 4 5 4 3 4 5 4 3 3 4 5 4

88 5 4 3 4 5 4 4 4 3 4 3 4 5 3 4 4 3 4 5 4

89 4 3 5 4 4 5 4 5 5 4 5 5 4 4 3 4 5 5 4 4

90 5 3 4 5 3 4 4 5 3 4 3 3 5 4 5 4 3 4 5 4

91 3 3 2 4 2 2 1 1 5 2 2 4 4 5 2 4 3 2 3 3

92 4 3 4 5 4 4 5 4 3 4 5 4 4 3 4 5 4 4 5 4

93 3 4 4 5 4 3 4 4 3 5 5 5 5 5 4 4 5 4 4 4

94 2 3 2 1 3 3 3 3 2 4 3 3 2 3 3 3 3 2 2 3

95 3 2 3 2 2 4 4 2 2 4 3 4 2 3 2 2 4 4 3 3

96 4 3 4 5 4 3 4 5 4 3 4 5 4 3 4 4 4 3 4 5

97 4 3 4 4 4 4 4 5 3 3 4 4 5 4 3 4 4 5 4 4

98 3 3 4 4 4 5 4 5 4 4 4 5 4 5 4 4 4 5 5 4

99 2 2 3 2 1 2 3 2 3 3 2 3 2 2 3 2 3 2 3 3

100 5 4 5 3 5 4 4 4 5 4 4 4 5 5 3 4 3 4 3 4

impact of brand switching in the telecommunication

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