Perceived value, service quality, customer satisfaction, trust and loyalty on blackberry user (2011)

PERCEIVED VALUE, SERVICE QUALITY, CUSTOMER SATISFACTION,
TRUST AND CUSTOMER LOYALTY ON BLACKBERRY USER
CASE STUDY : CIPUTAT UNIVERSITY STUDENT
By:
HATTA HARRIS RAHMAN
NIM: 107081103905
DEPARTMENT OF MANAGEMENT
INTERNATIONAL CLASS PROGRAM
FACULTY OF ECONOMICS AND BUSINESSES
SYARIF HIDAYATULLAH STATE ISLAMIC UNIVERSITY
JAKARTA
1432 AH /2011 AD

v
CURRICULUM VITAE
I. PERSONAL INFORMATION
Name : Hatta Harris Rahman
Place/Date of Birth : Jakarta, December 13rd
, 1988
Address : Blok A/1 No. 23, Permata Pamulang
Baktijaya, Cisauk, Tangerang Selatan
Father : Dr. Usman Yatim M.Pd, M.Sc
Mother : Rahmi Mulyati
Phone Number : 085719853343
E-mail : arisrahmanhhr@gmail.com
arisrahmanhhr@yahoo.co.id
Website : www.madina.co.id
Religion : Islam
Gender : Male
Status : Single
II. FORMAL EDUCATION
• Former Education
1994 : TK Pertiwi, Tangerang
1995 – 2000 : SD Babakan IV, Tangerang
2000 – 2006 : Ponpes/MAS Al- zaytun

vi
2006 – 2007 : Faculty of Science and Technology, Major in Physic, State
Islamic University Syarif Hidayatullah Jakarta.
• Current Education
2007-2011 : Faculty of Economics and Businesses, Major in
Management, State Islamic University Syarif
Hidayatullah Jakarta.
III.INFORMAL EDUCATION
• ICDL (International Computer Driving Licence ) from AGICT (2004)
• ICCS (International Certificate in Computer Studies) from NCC (National
Computing Center ) (2005)
IV.ORGANIZATIONAL EXPERIENCE
• Room leader in Al-Zaytun (2002)
• Member of PWI (Persatuan Wartawan Indonesia / Indonesia Journalist
Association)
• Online Redactor at MADINA (Masyarakat Dinamis Nasionalis) 2007 -
now

vii
Abstract
Hatta Harris Rahman. “Perceived Value, Service Quality, Customer
Satisfaction, Trust and Customer Loyalty on Blackberry”. Skripsi untuk strata
satu (S1) Jurusan Manajemen (Program International) Fakultas ekonomi dan
bisnis Universitas Islam Negeri (UIN) Syarif Hidayatullah Jakarta, 2011 M/1432
H. Tujuan penelitian untuk menganalisis hubungan antara persepsi nilai, kualtas
layanan, kepuasan pelanggan, kepercayaan dan kesetiaan pelanggan dalam sudut
pandang mahasiswa. Hasil dari penelitian ini untuk mengetahui faktor apa saja
yang mempengaruhi kesetiaan pelanggan. Responden adalah mahasiswa yang
sedang dalam masa studi di daerah Ciputat. Sampel yang diteliti berjumlah 115
mahasiswa dengan menggunakan metode Judgment sampling. Data diolah melalui
tes validitas, reliabilitas, dan Structure Equation Modeling. Hasil dari penelitian
ini adalah, 1) persepsi nilai tidak berpengaruh signifikan terhadap kepuasan
pelanggan, 2) kualitas layanan berpengaruh signifikan terhadap kepuasan
pelanggan, 3) Hubungan antara persepsi nilai dengan kualitas layanan mempunyai
pengaruh yang positif terhadap kepuasan pelanggan, 4) kepuasan pelangan
berpengaruh signifikan terhadap kepercayaan, 5) kepuasan pelanggan tidak
berpengaruh signifikan terhadap kesetiaan pelanggan, 6) kepercayaan
berpengaruh signifikan terhadap kesetiaan pelanggan, 7) kepercayaan dapat
menjadi variabel intervening dalam hubungan antara kepuasan pelanggan dengan
kesetiaan pelanggan.
Keywords: Perceived Value, Service Quality, Satisfaction, Trust, Loyalty,
Blackberry

viii
Abstract
Hatta Harris Rahman. “Perceived Value, Service Quality, Customer
Satisfaction, Trust and Customer Loyalty on Blackberry”. Thesis of Stratum one
(S1). Major in Management (International Program) Faculty of Economics and
Business State Islamic University (UIN) Syarif Hidayatullah Jakarta, 2011
M/1432 H. The objective of this research is to analyze the Relationship between
perceived value, service quality, customer satisfaction, trust and customer loyalty
in university student perspective. The result of this research is to know what
factors affected to customer loyalty.The respondents were all element of Ciputat
University student. The samples of this research are 115 university students . Field
of research is using judgement sampling method. Data has been analyzed use
validity test, reliability test, and Structure Equation Modeling. The result of this
research are, 1) perceived value has no significant relationship toward customer
satisfaction, 2) service quality has significant relationship toward customer
satisfaction, 3) there is relationship between perceived value and service quality in
order to form customer satisfaction 4) customer satisfaction has significant
relationship toward trust, 5) customer satisfaction has no significant relationship
toward customer loyalty, 6) trust has significant relationship toward customer
loyalty, 7) trust become intervening variable between customer satisfaction and
customer loyalty.
Keywords: Perceived Value, Service Quality, Satisfaction, Trust, Loyalty,
Blackberry

ix
Preface
Assalamu’alaikum Wr. Wb.
Alhamdulillah, Praise and thanks I give to Allah SWT which blessing its
mercy that give guidance to me from unknowing become know something about
research until I could finishing my thesis on healthy condition. This thesis has
purpose as requirement to achieved Stratum One (S1) title in economic at Faculty
of Economic and Business, Management Major, Human Resource Concentration,
State Islamic University, Syarif Hidayatullah Jakarta.
On this research, I have many experiencing difficulties, but favor aid from
many side I could finish my thesis although still much shortage on my thesis. At
the moment researcher want to say “Thank You” to all of people that was assist
researcher on finishing my thesis, especially to:
1. My mother and Father that always support me every time to doing best job
in this thesis, give me enough care, and loving me. Hopefully, I can make
you proud to me.
2. Prof. Dr Abdul Hamid, MS as Academic Supervisor 1 and Cut Erika A.F.,
MBA as Academic Supervisor 2 which always be ready to guide and
support me, give me more research knowledge, full patient, never tired,
and always friendly to me. Thanks for your advice and knowledge that you
give to me, hopefully, can helpful to me in the present and future time.
3. Mr. Arief Mufraini as Head of International Program and Dr. Ahmad
Dumyathi Bashori, MA as secretary of International Program, that always
aid me if I have difficulties, teach me something that I do not know, advice
me if I make mistake, and very friendly.

x
4. My thesis Examiner, Prof. Dr. Ahmad Rodoni, Prof. Dr. Margareth
Gfrerer, Dr. Ahmad Dumyathi Bashori, MA, thanks, you were pass me in
this thesis examination.
5. All my Family (Dad, Mom, Sisters). You all are the reason why I have to
finish this.
In the last point, researcher aware that on arranging this thesis still have
limitation on all aspect, so the researcher expecting construct suggestion for
improvement and achieving excellent writing in future. Thank you, and I hope I
can make some contribution to FEB UIN Syarif Hidayatullah Jakarta.
Wassalamu’alaikum Wr. Wb.
Jakarta, June 27, 2011
Author and Researcher
Hatta Harris Rahman

xi
TABLE OF CONTENT
LECTURER LEGALIZATION SHEET
SHEET STATEMENT AUTHENTICITY SCIENTIFIC WORKS
ENDORSEMENT SHEET COMPREHENSIVE EXAMS
CERTIFICATION OF THESIS EXAM SHEET
CURRICULUM VITAE
ABSTRACT
PREFACE
TABLE OF CONTENT
LIST OF TABLE
LIST OF PICTURE
i
ii
iii
iv
v
vi
ix
xi
xiv
xvi
CHAPTER I INTRODUCTION
A Background 1
B Problem Formulation 7
C Objective of the Research 8
D Benefit of the Research 9
CHAPTER II LITERATURE REVIEW
A Marketing
1. Concept of Marketing
2. Definition of Marketing
3. Marketing Mix
11
13
15

xii
B Perceived Value 18
C Service Quality 20
D Satisfaction 24
E Trust 26
F Loyalty 30
G Previous Research 31
H
I
Logical Framework
Relationship Between Variable
35
36
J Research Hypothesis 37
CHAPTER III RESEARCH METHOD
A Research Scope 39
B Sampling Method 39
C Data Collection Method 40
D Analysis Method
1. Structural Equation Modelling
2. Steps in Performing Analysis
a. Model Specification
b. Estimation of free Parameters
c. Assessment of Fit
d. Model Modification
42
43
3. Research Design 50
4. Classification of Variable 52

xiii
5. Validity and Reliability Test 54
CHAPTER IV ANALYSIS
A Blackberry Profile 57
B Respondent Profile 65
C Reliability and Validity Test 69
D Structure Equation Modelling
1. Estimate Degree of Freedom
2. Normality and Outlier Data
3. Measurement Model Test
4. The Analysis of Relationship Between Indicators and
Construct
5. Model Structural Test
6. Model Modification
7. Hypothesis
71
CHAPTER V CONCLUSION AND RECOMMENDATION
A Conclusion 92
B Implication 93
C Recommendation 94
REFERENCES 96
ATTACHMENT

xiv
LIST OF TABLE
N0 Name of Table Page
3.1 Likert Scale 41
3.2 Operational Variable 52
4.1 Respondent Statistics 65
4.2 Gender 66
4.3 Age 66
4.4 University 65
4.5 Operator 67
4.6 Income 68
4.7 Reliability Score 69
4.8 Validity Score 69
4.9 Assessment of Normality 73
4.10 Observations farthest from the centroid 74
4.11 Assessment of Normality 76
4.12 CMIN 78
4.13 RMR, GFI 79
4.14 Baseline Comparisons 80
4.15 Parsimony-Adjusted Measures 81
4.16 Standardized Regression Weights 82

xv
4.17 Correlations 83
4.18 Squared Multiple Correlations 83
4.19 Regression weights 85
4.20 Covariances 86
4.21 Correlations after modifications 87
4.22 Regression Weights after modifications 87
4.23 Hypothesis 89

xvi
List of Figure
No Title of Figure Page
1.1 Monthly Growth in Traffic Since Jan 2009 3
1.2 Mobile Web Usage 4
2.1 Concept of Marketing 11
2.2 Marketing Definition 13
2.3
2.4
The four P Component of the Marketing Mix
Factors of Customer Satisfaction
17
25
2.5 Trust Indicators 29
2.6 Logical Framework 35
3.1
3.2
4.1
4.2
Logical Framework
Logical Framework with Indicators
Computation of Degrees of freedom
Result
49
51
72
78

1
CHAPTER I
INTRODUCTION
A. Background
In recent years, company face their hardest competition ever. Good product
and high sales cannot guaranteed the business can perform well in next years.
They realize the market need something more than traditional marketing has
offered before. Strong customer relationship become hot issue and it can’t be
compromized in modern marketing.
In modern era, a customer has thousands places where they can buy
products or service for their necessity. Marketers must connect with
customers—informing, engaging, and maybe even energizing them in the
process. John Chambers, CEO of Cisco Systems:
"Make your customer the center of your culture."
Bernd Pischetsrieder, ex Chairman of the Board of Management,
Volkswagen AG:
“Become success always means hear the customer dan understand their
necessity”.
Alvin Toffler, best-selling author and futurist :
“ Don’t make mistakes, the world has changed and companies can’t work on
advertising to control perception or customer behavior”.

2
Alfin Toffler in his book Powershift:
“Information era has change basic of power deeply. Customer is no longer user
who act passively, they have become a new power by internet and information.
The voice of customer nowadays is louder and clearer than before and company
should keep attention to them”.
Indonesia, the world’s fourth most populous nation (inmobi:2009), has
been a contrarian market for smartphones. It is one of the few markets worldwide
where the Blackberry beats the iPhone as a consumer smartphone.
Generally, the Blackberry is seen more as a device that companies issue to
their employees because push e-mail feature, while iPhone is the one that people
choose for themselves.
BlackBerry is a line of mobile e-mail and smartphone devices developed
and designed by Canadian company Research In Motion (RIM) since 1999.
In 2009, InMobi, the largest mobile ad network in Asia, Africa and
Indonesia, released data showing that RIM’s Blackberry device may be leading
the handset race in Indonesia. From January 2009 to June 2009, mobile ad
requests on Blackberry phones increased by 842%, compared to mobile ad
requests on Indonesia iPhones, which increased only by 205%.
RIM’s Blackberry device was released three months before the iPhone in
the country in January of 2009. Although Blackberry and iPhone had similar

3
growth patterns after the iPhone launch, the two handsets took dramatically
different growth paths beginning in April 2009 per the graph below.
Figure 1.1
Source : www.inmobi.com
Indonesia is predicted to be the third largest mobile market after China and
India by 2010 according to the ROA Group. Already, mobile users in Indonesia
far outnumber active Internet users by 5 to 1, and the country boasts a 56.8%
mobile penetration rate verses a 10.4% according to Internet World Stats.
Also according to data on the InMobi network, Indonesia’s mobile Internet
user base has more than doubled within the last 12 months. InMobi estimates 9
million mobile Internet users currently in Indonesia, with 591 page views per
user, exceeding the approximate global average of 250 page views per user

4
(source: Opera, 2009). Handset manufacturers are taking notice, as 80% of
handsets sold in Indonesia are web enabled. Costly ISP plans, unreliable fixed
line infrastructure, and inexpensive mobile data plans with unlimited mobile web
usage are also encouraging the adoption of mobile Internet browsing.
Specifically, 53% of mobile web users are between the ages of 18 and 27,
and 82% of the total number of mobile web users are male.
Figure 1.2
Source : www.inmobi.com
In January 2011 Communications and information technology minister of
Indonesia claims RIM (Blackberry company) does not pay taxes or contribute to
the Southeast Asian country's booming economy (including Indonesia) and also
they gave RIM an ultimatum to remove pornographic content from its web
services for its two million customers in Indonesia within two weeks or lose its
operating license in the rapidly growing market.

5
Research in Motion (RIM) Southeast Asia managing director Gregory
Wade said he would "like to clarify that it always has and will continue to
operate within the laws set by governments around the world, including
Indonesia. RIM dutifully pays all applicable taxes that are exercised from its
business within the region in the same manner as all other importing
manufacturers," he said at a conference in Bali. (Jakarta Globe, January 13,
2011).
A day before its deadline, Research In Motion was able to install the filters
necessary to block access to pornography through its ubiquitous BlackBerry
devices in Indonesia. (Jakarta Globe, January 20, 2011).
RIM’s regional managing director Gregory Wade:
“BlackBerry currently leads the smartphone market in Indonesia, the Philippines
and Thailand. Asia accounted for 11 percent of RIM’s global shipments in the
first quarter of 2011, compared to eight percent for all of 2010.” (Jakarta Globe,
June 24, 2011)
Byan Ma, an analyst with IDC:
“If you look at the countries he (Wade) mentioned, those are good success stories
for them despite the beating they are getting globally. In Indonesia, everyone
wants to have a BlackBerry.” (Jakarta Globe, June 24, 2011)
Blackberry in Indonesia has not just already become handset or cellphone
but also lifestyle. When we watch TV or Indonesia movie the actor or actress

6
often show the blackberry as their cellphone. The TV ads or Newspaper ads also
show strength of Blackberry and when there is promotion Blackberry is one of
thefavourite thing as a prize to customer.
The role of Blackberry as a smartphone to support the activities of people
in Indonesia become main reason why this research created and university
student will become the respondent because youth segment has biggest
percentage of total Blackberry user. The writer want measure the performance
from customer perspective and she wants look the role of service quality and
perceived value towards customer satisfaction and also the relationship in
making trust and loyalty.
This paper has two main objectives. First, it consider the linkage between
satisfaction, trust, and loyalty on BB user. Second, in the more explorative part of
the study it examine whether the parent brand has an effect on the consumer’s
satisfaction, trust, or loyalty. The paper is structured as follows. The main
constructs of the study are reviewed next, and this discussion forms the basis
upon which the research hypotheses are built. The sample and measures used are
then introduced, and the results of the study are presented. Finally, the findings
are discussed and future research directions are suggested.
This research have different with previous research which this research try
to get information and data based on primary and secondary data on Ciputat
university Student. This research take the variable based on some journal of

7
economic, business, and marketing. Furthermore, I will combine those become
one scientific writing..
This research is conducted for the academic purpose of the researcher to
meet the partial fulfillment of the requirements for the undergraduate Degree
Program in Management at Faculty Economic and Business on State Islamic
University “Syarif Hidayatullah” Jakarta. This research will be important to
internal parties to find the key success why the product can be “trendsetter” for
some people because perceived value and service quality. Then, this research is
also important to external parties which definitely have strong relationship
I hope my research can give contribution to marketing sience especially, on
knowing the effect of perceived value and service quality towards customer
loyalty by customer satisfaction and trust. Then, hopefully this research can give
some contribution to implement marketing in other educational institutions in
this country generally.
B. Problem Formulation
Business competition in cellphone industry is getting tighter from time to
time. So the company should have good strategy in running business. Related in
these things, so the problem will be researches are:
1. Is customer satisfaction influenced by perceived value?
2. Is customer satisfaction influenced by service quality?

8
3. Are perceived value and service quality have positive relationship in order to
form customer Satisfaction
4. Is trust influenced by level of customer satisfaction?
5. Is loyalty influenced by level of customer satisfaction?
6. Is trust influenced by level of trust?
7. Is Variable trust is an interveining variable between customer satisfaction and
loyalty?
C. Objective of the Research
The objectives of this research are:
1. To analyze the relationship between perceived value and customer
satisfaction.
2. To analyze the relationship between service quality and customer satisfaction.
3. To analyze the relationship between perceived value and service quality in
order to form customer satisfaction
4. To analyze the relationship between customer satisfaction and trust.
5. To analyze the relationship between customer satisfaction and loyalty.
6. To analyze the relationship between trust and loyalty .
7. To analyze the direct and indirect effect of loyalty by customer satisfaction
through trust.

9
D. Benefit of the Research
1. The Benefit of this research are:
a. For Researcher
The researcher hopes that the research was conducted can give benefit to
myself to implementing all knowledge that was got in learning process at
university to real life.
b. For Academician and Management of University
Theoretically, this research can have a function in knowledge development
especially in marketing and management subject. Beside that can be use as
a reference to next research in marketing and management. The researcher
hopes that the research can give benefit to academic society and
management of university in the following capability:
1) Become a reference tools for perceived value and service qaulity
understanding as marketing element.
2) Become a tool to developing science of management generally and
marketing specifically.
c. For Student
1) Student will know what factors that influence the trend to use blackbery
in university environment.
2) Student will have opportunity to assess all of the research by the result in
this research.

10
d. For Company
1). Give explanation why customer can be loyal to the product in marketing
perspective.
2). As reference to plan the marketing strategy to young segment in the
future.

11
CHAPTER II
LITERATURE REVIEW
A. Marketing
1. Concept of Marketing
The concept of marketing has changed and evolved over time. Whilst in
today’s business world, the customer is at the forefront, not all businesses in
the past followed this concept. Their thinking, orientation or ideology put
other factors rather then the customer first. www.learnmarketingnet describe
concept of marketing consist of 4 factors. Those are:
Figure 2.1
Concept of Marketing
Source : www.learnmarketing.net

12
a. Production Oriented
The focus of the business is not the needs of the custobmer, but of reducing
costs by mass production. By reaching economies of scale the business will
maximize profits by reducing costs.
b. Product Orientation
The company believes that they have a superior product, based on quality
and features, and because of this they feel their customers will like it also.
c. Sales Orientation
The focus here is to make the product, and then try to sell it to the target
market. However, the problem could be that consumers do not like what is
being sold to them.
d. Market Orientation
Puts the customer at the heart of the business. The organization tries to
understand the needs of the customers by using appropriate research
methods, Appropriate processes are developed to make sure information
from customers is fed back into the heart of the organisation. In essence all
activities in the organisation are based around the customer. The customer
is truly king!
In today’s competitive world putting the customer at the heart of the
operation is strategically important. Whilst some organizations in certain
industries may follow anything other then the market orientation concept, those

13
that follow the market orientation concept have a greater chance of being
successful.
2. Definition of Marketing
Figure 2.2
Marketing Defnition
Source : www.learnmarketing.net
According to a social definition, marketing is a societal process by which
individuals and groups obtain what they need and want through creating,
offering, and exchanging products and services of value freely with others.

14
As a managerial definition, marketing has often been described as “the art
of selling products.” But Peter Drucker in Kotler (2003 : xii), a leading
management theorist, says that “the aim of marketing is to make selling
superfluous. The aim of marketing is to know and understand the customer so
well that the product or service fits him and sells itself.
Ideally, marketing should result in a customer who is ready to buy.” The
American Marketing Association (www.marketingpower.com) offers this
managerial definition: Marketing is the activity, set of institutions, and processes
for creating, communicating, delivering, and exchanging offerings that have
value for customers, clients, partners, and society at large.
Coping with exchange processes—part of this definition—calls for a
considerable amount of work and skill. We see marketing management as the art
and science of applying core marketing concepts to choose target markets and
get, keep, and grow customers through creating, delivering, and communicating
superior customer value.
Kotler (2003 : xiii) Marketing is the business function that identifies
unfulfilled needs and wants, defines and measures their magnitude and potential
profitability, determines which target markets the organization can best serve,
decides on appropriate products, services, and programs to serve these chosen
markets, and calls upon everyone in the organization to think and serve the
customer.

15
Marketing is important to all types of organizations because it focuses on
satisfying the needs of customers. Marketing activities are performed by people
in various positions at different organizations. Interacting with people is a major
component of most marketing positions.
David Packard of Hewlett-Packard observed,
“Marketing is much too important to leave to the marketing department. In a
truly great marketing organization, you can’t tell who’s in the marketing
department. Everyone in the organization has to make decisions based on the
impact on the customer.”
The same thought was well-stated by Professor Philippe Naert:
“You will not obtain the real marketing culture by hastily creating a marketing
department or team, even if you appoint extremely capable people to the job.
Marketing begins with top management.
3. Marketing Mix
Marketers use numerous tools to elicit the desired responses from their
target markets. These tools constitute a marketing mix: Marketing mix is the set
of marketing tools that the firm uses to pursue its marketing objectives in the
target market. As shown in Figure 2-3, McCarthy in Kotler (2000 : 9) classified
these tools into four broad groups that he called the four Ps of marketing:
product, price, place, and promotion.

16
a. Product
A product can be either a good or a service that is sold either to a commercial
customer or an end consumer.
b. Price
The price is the amount a customer pays for the product. It is determined by a
number of factors including market share, competition, material costs, product
identity and the customer’s perceived value of the product.
c. Promotion
Promotion represents all of the communications that a marketer may use in the
marketplace. Promotion has four distinct elements: advertising, public
relations, word of mouth and point of sale.
d. Place
Place represents the location where a product can be purchased. It is often
referred to as the distribution channel.

17
Figure 2.3
Source : Kotler (2000)

18
B. Perceived Value
The marketing job is to create, deliver, and capture customer value. Value
primarily is the putting together of the right combination of quality, service, and
price (QSP) for the target market.
Louis J. De Rose, head of De Rose and Associates, Inc., says:
“Value is the satisfaction of customer requirements at the lowest possible cost of
acquisition, ownership, and use.”
Michael Lanning in Kotler (2003) holds that winning companies are those
that develop a competitively superior value proposition and a superior value-
delivery system. A value proposition goes beyond the company’s positioning on
a single attribute. It is the sum total of the experience that the product promises to
deliver backed up by the faithful delivery of this experience.
Jack Welch put this challenge to GE:
“The value decade is upon us. If you can’t sell a top quality product at the
world’s lowest price, you’re going to be out of the game.”
A company’s ability to deliver value to its customers is closely tied with its
ability to create satisfaction for its employees and other stakeholders. Value
ultimately depends on the perceiver.
Smart companies not only offer purchase value but also offer use value as
well. Companies worry about spending more money to satisfy their customers.
They need to distinguish between value-adding costs and non-value-adding costs.

19
BlackBerry devices, which are manufactured by Research in Motion
(RIM), rank highest in overall customer satisfaction among business wireless
smartphone users, according to the J.D. Power and Associates 2007
(www.jdpower.com) Business Wireless Smartphone Customer Satisfaction
Study.
The inaugural study measures business customer satisfaction with their
wireless smartphone, which is a mobile phone offering advanced capabilities,
often with personal computer-like functionality such as a BlackBerry or Treo.
Overall satisfaction is examined across six key factors. In order of importance,
they are: ease of operation (22%); operating system (21%); physical design
(20%); audio (14%); battery aspects (13%); and utility features (10%).
The study finds that satisfaction is critical to future sales and profitability
of smartphone manufacturers, as highly satisfied owners are more than 50
percent more likely to repurchase the same brand than those who are not satisfied
with their smartphone. Additionally, owners who are “delighted” with their
smartphone are 80 percent more likely to recommend a particular brand than an
unsatisfied owner.

20
C. Service Quality
In an age of increasing product commoditization, service quality is one of
the most promising sources of differentiation and distinction. Giving good
service is the essence of practicing a customer orientation.
Yet many companies view service as a pain, a cost, as something to
minimize. Companies rarely make it easy for customers to make inquiries,
submit suggestions, or lodge complaints. They see providing service as a duty
and an overhead, not as an opportunity and a marketing tool.
Every business is a service business. Theodore Levitt said:
“There is no such things as service industries. There are only industries whose
service components are greater or less than those of other industries. Everybody
is in service.”
American educator observed
“Businesses planned for service are apt to succeed; businesses planned for profit
are apt to fail,”
Nicholas Murray Butler in Kotler (2003). What service level should a
company deliver? Good service is not enough. Nobody talks about good service.
Sam Walton, founder of Wal-Mart, set a higher goal:
“Our goal as a company is to have customer service that is not just the best, but
legendary.”
The three Fs of service marketing are be fast, flexible, and friendly.

21
Zeithaml, 1988; Parasuraman et al.,1988 in Azman Ismail & Norashyikin
Alli (2009 : 72). Service quality has been defined as a form of attitude – a long-
run overall evaluation. Perceived service quality portrays a general; overall
appraisal of service, i.e. a global value judgement on the superiority of the
overall services and it could occur at multiple levels in an organization .Many
scholars such as Parasuraman et al. highlight that responsiveness; assurance and
empathy are the most important service quality features. Responsiveness is often
defined as the willingness of service provider to provide service quickly and
accurately. Assurance refers to credibility, competence and security in delivering
services. Empathy is related to caring, attention and understanding the customer
needs when providing services.
Extant research in this area shows that properly implementing such service
quality features may increase customer satisfaction (Gronroos, 1984; in Azman
Ismail & Norashyikin Alli, 2009 : 72). In a quality management context,
customer satisfaction is defined as a result of comparison between what one
customer expects about services provided by a service provider and what one
customer receives actual services by a service provider. If services provided by
an organization meet a customer’s needs, this may lead to higher customer
satisfaction.
Surprisingly, a thorough investigation of such relationships reveals that
effect of service quality features on customer satisfaction is not consistent if

22
perceive value is present in organizations. Perceive value is considered as
customer recognition and appreciation the utility of a product that is given by a
service provider which may fullfil his/her expectation. In a service management
context, the ability of an organization to use responsiveness, assurance and
empathy in delivering services will increase customers’ perceptions of value; this
may lead to higher customer satisfaction.
Service quality model, image – on a company and/or local level – was
introduced by Gronroos (1983, 1984) in Ruben Chumpitaz Caceres and Nicholas
G. Paparoidamis, (2005 : 40) in the model as a filter between the two quality
dimensions called functional (how the service process functions) and technical
(what the service process leads to for the customer in a “technical” sense), that
influences the quality perception either favourably, neutrally or unfavourably,
depending on whether the customer considers the service good, neutral or bad.
As image perceptions change over time depending on customers’ quality
perceptions, it adds a dynamic aspect to the model, which in other respects is
static
The model states that the consumer is not interested only on what he/she
receives as an outcome of the production process, but also on the process itself.
The perception of the functionality of the technical outcome (technical quality) is
a major determinant of the way he/she appreciates the effort of the service
provider. Functional quality corresponds to the expressive performance of a

23
service. Hence, those two distinct quality dimensions conceptualise the “what”
(is offered) and “how” of the service offering. Obviously, the functional quality
dimension (subjective in nature) cannot be evaluated as objectively as the
technical one. The “perceived service” is the result of a customer’s view of a
bundle of service dimensions, some of which are technical and some of which
are functional in nature. Perceived service quality is the outcome of perceived
service when compared with expected service.
Services are commodities that cannot be stored or disappear in use, or as
activities that require personal contact. The distinct characteristics of services are
intangibility, perishability, heterogeneity of the product, and simultaneity of
production and consumption.
Two economic units are required for a service to be produced – the
consumer and the producer. While the consumer cannot retain the actual service
after it is produced, the effect of the service can be retained.
J.D. Power and Associates Survey (2009) studied the mobile phone users’
satisfaction in the United Kingdom. The study used a sample of 3325 mobile
phone customers throughout United Kingdom. Important dimensions of service
quality included in the survey were coverage, call quality, promotions and
offerings of incentives and rewards, prices of service, billing, customer, bundled
services. The study showed rising customer expectations with regard to the
additional features and services from the mobile operators.

24
D. Satisfaction
Many researchers have looked into the importance of customer satisfaction.
Kotler in Harkiranpal Singh (2006 : 1) defined satisfaction as: a person’s feelings
of pleasure or disappointment resulting from comparing a product’s perceived
performance (or outcome) in relation to his or her expectations. Hoyer and
MacInnis in Harkiranpal Singh (2006 : 1) said that satisfaction can be associated
with feelings of acceptance, happiness, relief, excitement, and delight.
Hansemark and Albinsson in Harkiranpal Singh (2006 : 1), satisfaction is
an overall customer attitude towards a service provider, or an emotional reaction
to the difference between what customers anticipate and what they receive,
regarding the behavior of some need, goal or desire”.
There are many factors that affect customer satisfaction. According to
Hokanson in Harkiranpal Singh (2006 : 2), these factors include friendly
employees, courteous employees, knowledgeable employees, helpful employees,
accuracy of billing, billing timeliness, competitive pricing, service quality, good
value, billing clarity and quick service.

25
Figure 2.4
Factors of Customer Satisfaction
Source : Hokanson (1995)
In these two decades, discussion on drivers from customer satisfaction is
never ended. Various articles and literatures theoretically and practically explain
about customer satisfaction. According to Handi Irawan, who has become the
consultant in many companies in Indonesia, Mcom (2002:37) in Fitry Amry
(2009 : 24), Marketing & Research Consultant from Frontier says there are five
primary driver of customer satisfaction.
1. Product Quality
Consumer satisfied after buying and using the product, where actually
the product is fine.

26
2. Price
For sensitive customer usually low price is an important source of
satisfaction because they will get satisfaction from high value of
money. This price component is not important for those who are not
sensitive towards price.
3. Service Quality
Service quality is always depends on three things, i.e. system,
technology and people. This factor of human being is giving into
contributions is about 70%. The concept of service quality is believed
that have five dimensions those are reliability, responsiveness,
assurance, empathy, and tangible.
4. Emotional
Customer satisfaction can come from feeling of proud, confidence,
symbol of success.
5. Easy way to get product and service
Consumer can satisfied when they got cheap price, but if it is difficult
to get service or to use the product the satisfaction can feel nothing.
E. Trust
Trust has been defined according to Rousseau et al., in Norizan Kassim and
Nor Asiah Abdullah (2009 : 355) as a psychological state composing the

27
intention to accept vulnerability based on expectations of the intentions or
behavior of another. Trust is an important construct catalyst in many
transactional relationships.
The phenomenon of trust (www.beyondintractability.org) has been
extensively explored by a variety of disciplines across the social sciences,
including economics, social psychology, and political science. The breadth of
this literature offers rich insight, and this is noted in the common elements that
appear in the definition of trust.
Trust has been identified as a key element of successful conflict resolution
(including negotiation and mediation). This is not surprising insofar as trust is
associated with enhanced cooperation, information sharing, and problem solving.
Early theories of trust described it as a unidimensional phenomenon that
simply increased or decreased in magnitude and strength within a relationship.
However, more recent approaches to trust suggests that trust builds along a
continuum of hierarchical and sequential stages, such that as trust grows to
'higher' levels, it becomes stronger and more resilient and changes in character.
This is the primary perspective we adopt in the remainder of these essays.
At early stages of a relationship, trust is at a calculus-based level. In other
words, an individual will carefully calculate how the other party is likely to
behave in a given situation depending on the rewards for being trustworthy and
the deterrents against untrustworthy behavior. In this manner, rewards and

28
punishments form the basis of control that a trustor has in ensuring the trustee's
behavioral consistency. Individuals deciding to trust the other mentally
contemplate the benefits of staying in the relationship with the trustee versus the
benefits of 'cheating' on the relationship, and the costs of staying in the
relationship versus the costs of breaking the relationship. Trust will only be
extended to the other to the extent that this cost-benefit calculation indicates that
the continued trust will yield a net positive benefit.
Researcher have confrmed that higher levels of trust in business
relationship reduce transaction costs and improve most measures of business
performance. Yet repeated studies indicate low levels of customer and investor
trust in business. That gap suggests that significant opportunities may exist for
businesses to improve their performance by building trust with their key
stakeholders, specifically their customers and investors.
Management should adopt practises and implement business processes that
improve the means by which trust is developed and protected. Business today
needs a complementary offensive strategy to develop trust, which means that
management needs to become competent at defining strategies that optimize the
conditions that create trust. Trust has been widely associated with reducing
transaction costs and enhancing business and economic value. For growth
companies, customers are king and their trust is critical for sustained revenue

29
growth. Optimizing the trust of customers and sales channel partners is critical
for most companies relying on revenue growth.
Trust is a valuable business objective. It is an amorphous psychological
condition that is difficult to accurately isolate and manage. There are three types
of trust indicators as proxies:
1. Assertions – Perception indicators for trust : What the relying party says.
2. Actions – Outcome indicators for trust : How the relying party behaves.
3. Conditions – Affecting indicators for trust : The conditions that make it
possible for a persOn to trust
Figure 2.5
Trust Indicators
Source : Alex Tood (2007)

30
F. Loyalty
The term customer loyalty is used to describe the behavior of repeat
customers, as well as those that offer good ratings, reviews, or testimonials.
Some customers do a particular company a great service by offering favorable
word of mouth publicity regarding a product, telling friends and family, thus
adding them to the number of loyal customers (www.wisegeek.com). However,
customer loyalty includes much more. It is a process, a program, or a group of
programs geared toward keeping a client happy so he or she will provide more
business.
Customer loyalty can be achieved in some cases by offering a quality
product with a firm guarantee. Customer loyalty is also achieved through free
offers, coupons, low interest rates on financing, high value trade-ins, extended
warranties, rebates, and other rewards and incentive programs. The ultimate goal
of customer loyalty programs is happy customers who will return to purchase
again and persuade others to use that company's products or services. This
equates to profitability, as well as happy stakeholders.
Customer loyalty (Gremler and Brown 1996, 173) is defined as “the
degree to which a customer exhibits repeat purchasing behavior from a
service provider, possesses a positive attitudinal disposition toward the provider,
and considers using only this provider when a need for this service arises”

31
Loyal customers are more likely to tell others about their loyalty than just
satisfied customers. Excited customers tell other people about their experiences
and create ambassadors for the company. They become loyal customers and they
keep returning.
Customer loyalty has been defined as “a deeply held commitment to rebuy
or repatronize a preferred product/service consistently in the future, thereby
causing repetitive same-brand or same brand-set purchasing, despite situational
influences and marketing efforts having the potential to cause switching
behavior” (Oliver, 1999, p. 34).
Customer satisfaction is a comparison between customer expectation with
the perceived quality (Kotler, 2000 in Hatane Samuel and Nadya Wijaya: 25).
Customer satisfaction also influenced by perceived value. Trust also believed to
be a fundamental element for success of the relationship. With the achievement
of customer satisfaction and trust, the loyalty of customer can be achieved by
company and the customer will intent to choose product in the future and
recommend the product to other people.
G. Previous research
1. Perceive Value as a Moderator on the Relationship between Service Quality
Features and Customer Satisfaction (Azman Ismail & Norashyikin Alli,
2009)Quality management (QM) literature highlights that service quality is a

32
critical determinant of organizational competitiveness. The ability of an
organization implements service quality program will positively motivate
customers’ perceive value; this may lead to increased their satisfaction. The
nature of this relationship is less emphasized in service quality service models.
In this study, a survey research method was used to gather 102 usable
questionnaires from academic staffs who have studied in one Malaysian
public institution of higher learning in East Malaysia (HIGHINSTITUTION).
The outcomes of hierarchical regression analysis showed three important
findings: firstly, interaction between perceive value and responsiveness
insignificantly correlated with customer satisfaction. Secondly, interaction
between perceive value and assurance insignificantly correlated with customer
satisfaction and thirdly, interaction between perceive value and emphathy
significantly correlated with customer satisfaction. This result demonstrates
that perceive value has increased the effect of emphathy customer satisfaction,
but perceive value has not increased the effect of responsiveness and
assurance on customer satisfaction. Further, this study confirms that perceive
value does act as a partial moderating variable in the service quality models of
the organizational sample. In addition, implications and limitations of this
study, as well as directions for future research are discussed.
2. The Importance of Customer Satisfaction in Relation to Customer Loyalty and
Retention (Harkiranpal Singh, 2006) : To be successful, organizations must

33
look into the needs and wants of their customers. That is the reason why many
researchers and academicians have continuously emphasized on the
importance of customer satisfaction, loyalty and retention. Customer
satisfaction is important because many researches have shown that customer
satisfaction has a positive effect on an organisation’s profitability. Due to this,
the consequences of customer satisfaction and dissatisfaction must be
considered. There is also a positive connection between customer satisfaction,
loyalty and retention. Therefore, customer satisfaction, loyalty and retention
are all very important for an organization to be successful.
3. An empirical study on the effect of e-service quality on online customer
satisfaction and loyalty (Tianxiang Sheng and Chunlin Liu, 2010): A new
conceptual model of customer satisfaction and loyalty in online purchases is
developed, where four dimensions of e-service quality – efficiency,
requirement fulfillment, system accessibility, and privacy – are the four
predictors from Parasuraman’s E-S-QUAL. A partial least square estimation
algorithm was then applied to analyze data from a sample of 164 online
buyers from a range of backgrounds. Goods purchased include furniture,
books, clothes, software, and digital products.
The results indicate that efficiency and fulfillment have positive effects on
customer satisfaction, and fulfillment and privacy have positive effects on
customer loyalty. However, the remaining factors have no significant effect on

34
either customer satisfaction or customer loyalty. In addition, customer loyalty
is positively affected by customer satisfaction.
The paper finds that the service quality must be analyzed from different
aspects only to find that the requirement fulfillment has relatively great effect
on customers’ satisfaction and loyalty, the system accessibility has no effect
on both, the efficiency has positive effect on customers’ satisfaction and the
privacy has positive effect on customers’ loyalty. As these results are
inconsistent with previous research achievements to some extent, this paper
tends to provide some explanation.
4. Service Quality, Perceive Value, Satisfaction and Loyalty on PT. Kereta Api
Indonesia Based on Scoring from Surabaya Customer (Hatane Semuel and
Nadya Wijaya, 2009) : The research is to analyze service performance of PT
Kereta Api Indonesia (KAI) from five dimensions of SERVQUAL. It is also
to analyze the relationship among service quality, perceived value, customer
satisfaction, trust and customer loyalty. The populations of this research are
all train passengers who have used the service of PT KAI in Surabaya
station.The writer uses convenience sampling by distributing questionnaires to
400 respondents from some departing train stations in Surabaya. The results
show that service performance of PT KAI, according to its customers, is good.
In addition to this, the research also shows that SRVQUAL and perceived
value has direct positive influences on customer satisfaction, and customer

35
satisfaction has a direct positive influence on trust and customer loyalty. In the
analysis, it also shows that trust has a positive influence on customer loyalty,
eventhough it is not significant. Thus, customer satisfaction has become an
intervening variable between SERVQUAL and perceived value towards
customer loyalty. It also serves as an intervening variable between
SERVQUAL and perceived value towards trust. However, trust cannot serve
as an intervening variable between customer satisfaction and customer loyalty.
H. Logical Framework
Figure 2.6
Logical Framework of Customer Loyalty
Source : processed data

36
I. Relationship Between Variable
The result from some research shows positive relationship significantly
between perceived value and satisfaction (Lai lai,2004, Palilati, 2007 in Hatane
Samuel and Nadya Wijaya : 26).
Service quality has relatively great effect on customers’ satisfaction and
loyalty (Tianxiang Sheng and Chunlin Liu : 281). Their research has surveyed
the positive relationship between service quality and customers’ satisfaction and
loyalty only to find that good service quality is the basis of customers’
satisfaction.
Customer satisfaction does not guarantee repurchase on the part of the
customers but still it plays a very important part in ensuring customer loyalty and
retention. This point has been echoed by Gerpott et al. (2001 in Harkiranpal
Singh : 26) when they said “customer satisfaction is a direct determining factor in
customer loyalty, which, in turn, is a central determinant of customer retention”.
Therefore, organisations should always strive to ensure that their customers are
very satisfied.
Trust feeling toward company or insitution will influence customer loyalty.
When customer trust the company they will commitment in building relationship.
Commitment will make them care with the relationship that represented by loyal,
(Disney, 1999 in Hatane Samuel and Nadya Wijaya: 27). Customer commitment
to the relatonship because they believe or trust to the company so there will

37
rebuy action of the product rom same company. (Kotler:2000 in Hatane Samuel
and Nadya Wijaya: 27).
J. Research Hypothesis
A hypothesis can be defined as logically conjectured relationship between
two or more variables expressed in the form of a testable statement.
Statistical hypothesis is a statement about the unknown value of a
parameter for a random experiment. The statement is either true or false. One can
think of a statistical test as a procedure for evaluating the truth or falsity of the
hypothesis. The test is usually based on the outcomes of several trials of the
experiment. Other factors, such as the cost of making a wrong evaluation and the
experimenter subjective feelings about the hypothesis, can be involved in the test.
1. H0: There is no relationship between perceived value and customer
satisfaction
Ha: There is relationship between perceived value and customer satisfaction
2. H0: There is no relationship between service quality and customer satisfaction
Ha: There is relationship between service quality and customer satisfaction
3. H0: There is no relationship between customer satisfaction and trust in order
to form Customer Satisfaction
Ha: There is relationship between customer satisfaction and trust in order to
form Customer Satisfaction

38
4. H0: There is no relationship between customer satisfaction and trust
Ha: There is relationship between customer satisfaction and trust
5. H0: There is no relationship between customer satisfaction and customer
loyalty
Ha: There is relationship between customer satisfaction and customer loyalty
6. H0: There is no relationship between trust and customer loyalty
Ha: There is relationship between trust and customer loyalty
7. H0: Variable trust is not an interveining variable between satisfaction and
loyalty
Ha: Variable trust is an interveining variable between satisfaction and loyalty

39
CHAPTER III
RESEARCH METHOD
1. Research Scope
This research is descriptive conclusive research that has objective to
analyse performance quality of Blackberry by measure customer satisfaction and
watch the influence and the relationship to trust and customer loyalty.
In this research, research is done by collecting secondary data coming
from written and digital literature found in books, journals, surveys and research
by research company and the internet (ebook and ejournal). Primary data is
obtained from questionnaires that distributed to respondent. The population of
this research is the university student in Ciputat area who use Blackberry
cellphone in daily activities. The reason why researcher selected university of
student because most of mobile web users are people between 18 – 27 years old
and Ciputat selected because there are universities that be able to represent the
research.
2. Sampling Method
The sampling method used is judgment sampling. Judgment sampling
involves the choice of subjects who are most advantageously placed or in the best
position to provide the information required. Thus the judgment sampling design

40
is used when a limited number or category of people have the information that is
sought.
The criteria for the respondents are:
1. University Student in Ciputat area
2. Blackberry user
3. The age between 18 – 27
The level of sampling in this research is accounted based on the opinion of
Singgih Santoso (2011) for SEM model with 5 variables and each variables
explained by three or more indicators, 100 – 150 samples can be considered valid
amd Hair and Augusty Ferdinand (2002) in Buonowikarto (2009:18) that the
minimum sample measure applied in Structural Equation Modelling (SEM) is to
be counted by 5 observations for every estimated parameter. So, because this
research using 23 indicators the sample should be based on formula
23 x 15 = 115 samples
3. Data Collection Method
Data collection is done through questionnaires given to student of Ciputat
university student. Questions are ordered systemically while answers are in the
form of multiple choices. Questions are made to be simple and easy to
understand to avoid ambiguity.

41
Questionnaire analysis is done by giving value from every answer to
questions of the questionnaire based on Likert Scale method. The instrument of
the question will end result the total score for every member of sample that
represent by every score that already write down, on the below:
Table 3. 1
Likert Scale
Likert Scale Score
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
1
2
3
4
5
Source: Freddy Rangkuti (2003)
Data that already collected by the respondent, and then will be selected,
edit, suitable with the researcher necessary. The result of the questionnaire are
compiled into the form of a table which will be tabulated systemically.

42
4. Analysis Method
1. Structural Equation Modelling
Structural equation modeling (SEM) is a statistical technique for testing
and estimating causal relations using a combination of statistical data and
qualitative causal assumptions. This definition of SEM was articulated by the
geneticist Sewall Wright (1921), the economist Trygve Haavelmo (1943) and
the cognitive scientist Herbert Simon (1953), and formally defined by Judea
Pearl (2000) in www.wikipedia.com using a calculus of counterfactuals.
Structural Equation Models (SEM) allow both confirmatory and
exploratory modeling, meaning they are suited to both theory testing and
theory development. Confirmatory modeling usually starts out with a
hypothesis that gets represented in a causal model. The concepts used in the
model must then be operationalized to allow testing of the relationships
between the concepts in the model. The model is tested against the obtained
measurement data to determine how well the model fits the data. The causal
assumptions embedded in the model often have falsifiable implications which
can be tested against the data.
With an initial theory SEM can be used inductively by specifying a
corresponding model and using data to estimate the values of free parameters.
Often the initial hypothesis requires adjustment in light of model evidence.

43
When SEM is used purely for exploration, this is usually in the context of
exploratory factor analysis as in psychometric design.
Among the strengths of SEM is the ability to construct latent variables:
variables which are not measured directly, but are estimated in the model from
several measured variables each of which is predicted to 'tap into' the latent
variables. This allows the modeler to explicitly capture the unreliability of
measurement in the model, which in theory allows the structural relations
between latent variables to be accurately estimated. Factor analysis, path
analysis and regression all represent special cases of SEM.
In SEM, the qualitative causal assumptions are represented by the missing
variables in each equation, as well as vanishing covariances among some error
terms. These assumptions are testable in experimental studies and must be
confirmed judgmentally in observational studies.
2. Steps in performing SEM analysis
a. Model specification
When SEM is used as a confirmatory technique, the model must be
specified correctly based on the type of analysis that the researcher is
attempting to confirm. When building the correct model, the researcher
uses two different kinds of variables, namely exogenous and endogenous
variables. The distinction between these two types of variables is whether
the variable regresses on another variable or not. As in regression the

44
dependent variable (DV) regresses on the independent variable (IV),
meaning that the DV is being predicted by the IV. In SEM terminology,
other variables regress on exogenous variables. Exogenous variables can be
recognized in a graphical version of the model, as the variables sending out
arrowheads, denoting which variable it is predicting. A variable that
regresses on a variable is always an endogenous variable, even if this same
variable is also used as a variable to be regressed on. Endogenous variables
are recognized as the receivers of an arrowhead in the model.
It is important to note that SEM is more general than regression. In
particular a variable can act as both independent and dependent variable.
Two main components of models are distinguished in SEM: the
structural model showing potential causal dependencies between
endogenous and exogenous variables, and themeasurement model showing
the relations between latent variables and their indicators. Exploratory and
Confirmatory factor analysis models, for example, contain only the
measurement part, while path diagrams can be viewed as an SEM that only
has the structural part.
In specifying pathways in a model, the modeler can posit two types of
relationships: (1) free pathways, in which hypothesised causal (in fact
counterfactual) relationships between variables are tested, and therefore are
left 'free' to vary, and (2) relationships between variables that already have

45
an estimated relationship, usually based on previous studies, which are
'fixed' in the model.
A modeller will often specify a set of theoretically plausible models in
order to assess whether the model proposed is the best of the set of possible
models. Not only must the modeller account for the theoretical reasons for
building the model as it is, but the modeller must also take into account the
number of data points and the number of parameters that the model must
estimate to identify the model. An identified model is a model where a
specific parameter value uniquely identifies the model, and no other
equivalent formulation can be given by a different parameter value. A data
point is a variable with observed scores, like a variable containing the
scores on a question or the number of times respondents buy a car. The
parameter is the value of interest, which might be a regression coefficient
between the exogenous and the endogenous variable or the factor loading
(regression coefficient between an indicator and its factor). If there are
fewer data points than the number of estimated parameters, the resulting
model is "unidentified" , since there are too few reference points to account
for all the variance in the model. The solution is to constrain one of the
paths to zero, which means that it is no longer part of the model.

46
b. Estimation of free parameters
Parameter estimation is done by comparing the actual covariance
matrices representing the relationships between variables and the
estimated covariance matrices of the best fitting model. This is obtained
through numerical maximization of a fit criterion as provided by
maximum likelihood estimation, weighted least squares or asymptotically
distribution-free methods. This is often accomplished by using a
specialized SEM analysis program of which several exist.
c. Assessment of fit
Assessment of fit is a basic task in SEM modeling: forming the basis
for accepting or rejecting models and, more usually, accepting one
competing model over another. The output of SEM programs includes
matrices of the estimated relationships between variables in the model.
Assessment of fit essentially calculates how similar the predicted data are
to matrices containing the relationships in the actual data.
Formal statistical tests and fit indices have been developed for these
purposes. Individual parameters of the model can also be examined
within the estimated model in order to see how well the proposed model
fits the driving theory. Most, though not all, estimation methods make
such tests of the model possible.

47
Of course as in all statistical hypothesis tests, SEM model tests are
based on the assumption that the correct and complete relevant data have
been modeled. In the SEM literature, discussion of fit has led to a variety
of different recommendations on the precise application of the various fit
indices and hypothesis tests.
Measures of fit differ in several ways. Traditional approaches to
modeling start from a null hypothesis, rewarding more parsimonious
models (i.e. those with fewer free parameters), to others such as AIC that
focus on how little the fitted values deviate from a saturated model (i.e.
how well they reproduce the measured values), taking into account the
number of free parameters used. Because different measures of fit capture
different elements of the fit of the model, it is appropriate to report a
selection of different fit measures.
Some of the more commonly used measures of fit include:
1) Chi-Square
A fundamental measure of fit used in the calculation of many other fit
measures. Conceptually it is a function of the sample size and the
difference between the observed covariance matrix and the model
covariance matrix.

48
2) Akaike information criterion (AIC)
A test of relative model fit: The preferred model is the one with the
lowest AIC value.
where k is the number of parameters in the statistical model, and L is
the maximized value of the likelihood of the model.
3) Root Mean Square Error of Approximation (RMSEA)
Another test of model fit, good models are considered to have a
RMSEA of .05 or less. Models whose RMSEA is .1 or more have a
poor fit.
4) Standardized Root Mean Residual (SRMR)
The SRMR is a popular absolute fit indicator. A good model should
have an SRMR smaller than .05.
5) Comparative Fit Index (CFI)
In examining baseline comparisons, the CFI depends in large part on
the average size of the correlations in the data. If the average
correlation between variables is not high, then the CFI will not be very
high.
6) For each measure of fit, a decision as to what represents a good-
enough fit between the model and the data must reflect other
contextual factors such as sample size (very large samples make the

49
Chi-square test overly sensitive, for instance), the ratio of indicators to
factors, and the overall complexity of the model.
d. Model modification
The model may need to be modified in order to improve the fit,
thereby estimating the most likely relationships between variables.
Many programs provide modification indices which report the
improvement in fit that results from adding an additional path to the
model. Modifications that improve model fit are then flagged as
potential changes that can be made to the model. In addition to
improvements in model fit, it is important that the modifications also
make theoretical sense.
Figure 3.1
Logical Framework

50
The model uses Trust as an intervening variables. The intervening
variable is a hypothetical internal state that is used to explain relationship
between observed variables, such as independent and dependent variables, in
empirical research. An intervening variables facilitates a better understanding
of the relationship between the independent and dependent variables when the
variables appear to not have a definite connection.
3. Research Design
The researcher uses two different kind of variables, namely exogenous and
endogenous variables, also known as independent and dependent variables. It
also involves two intervening variables, a hypothetical internal state thai is
used to explain relationships between observed variables, such as independent
and dependent variables, in empirical research.

51
Figure 3.2
Logical Framework With Indicators
1. Exogenous / Independent Variables:
X1 = Perceived Value
X2 = Service Quality
2. Intervening Variables:
Y2 = Trust

52
3. Endogenous / Dependent Variable:
Y1 = Customer Satisfaction
Z = Customer loyalty
It is hypothesized that Perceived Value (X1) and Service Quality (X2) have direct
effect to Customer Satisfaction while Customer Loyalty influenced by Trust
directly and Customer Satisfaction both directly and indirectly.
4. Classification of Variables
Table 3.2
Operational Variable
No Variable Indicator
1
Perceived Value
J.D. Power and Associates Survey
(2007)
1. ease of operation
2. operating system
3. physical design
4. audio
5. battery aspects
6. utility features

53
2
Service Quality
J.D. Power and Associates Survey
(2009)
1. call quality
2. coverage;
3. offerings and
promotions;
4. cost of the service;
5. billing or topping up
6. customer service;
7. handset/bundled
services
3
Customer Satisfaction
Handi Irawan (2002)
Fitry Amri (2009)
1. Product quality
2. Price
3. Service quality
4. Emotional
5. The ease to get.
4
Trust
Alex Todd (2007)
1. Assertions
2. Actions
3. Conditions
5
Customer loyalty
Hatane Samuel and Nadya Wijaya
(2009)
1. Future Intention
2. Recommendation

54
5. Validity and Reliability Test
Validity test is used to measure the available statement in the
questionnaire. A certain statement is considered valid the statement could
show how far those tools of measurement measure what is to be measure
(Sugiono, 1999:109 cited in Fitry Amri, 2008:40).
Validity test used for measure valid or not a questionnaire, a questionnaire
called valid if the question on questionnaire able to express a measured at
those questionnaires (Ghozali, 2005 on Adi Faqdhi Akbar, 2010:42).
According to Akdon, 2008 validity test has formula as follow:
Explanation:
= Coefficient correlation
N = Number of respondent
= Number of score items
= Number of total score (all item)
Then we calculating t test, with formula as follow:
Explanation:
T = value of t calculate
R = coefficient correlation r calculate

55
Distribution (t table) for α = 0.05 and freedom degree (dk = n-2) decision
rule are:
Valid if t calculate > t table.
Not valid if t calculate < t table.
Validity test of data used for measure valid or not valid a questionnaire
validity test by using item to total correlation orientation or on SPSS 16.0
output that knew as corrected item-total correlation. A questionnaire called
valid if r calculate that constitute item of correlated value (Ghozali, 2006:45
on Siti Fatimah, 2010:41). SPSS giving facilitate for measure validity test
with level significance below 0.05.
Reliability test of data is used for measure a questionnaire that constitute
indicator of variable or construct. A questionnaire called reliable or rely on if
answers someone toward question is consistent or stable from time to time
(Ghozali, 2006: 42 on Siti Fatimah, 2010:41). For measure reliability is used
Cronbach Alpa statistic test (Ghozali, 2006: 42 on Siti Fatimah, 2010:41).
Arbaadi Aditya, 2009 wrote on his thesis standardized formula of Cronbach's
Alpha can be defined as:
Where N is the number of components (items or testlets), equals the
average variance and is the average of all covariances between the
components (Cronbach, 1951). SPPS giving facilitate for measure reliability

56
test by Chonbach alpha (α). A construct called reliable if giving Cronbach
Alpha value > 0.60 (Ghozali, 2006: 42).In this research writers use AMOS
18 to process the statistic data.
Amos is short for Analysis of MOment Structures. It implements the
general approach to data analysis known as structural equation modeling
(SEM), also known as analysis of covariance structures, or causal modeling.
This approach includes, as special cases, many well-known conventional
techniques, including the general linear model and common factor analysis.

57
CHAPTER IV
ANALYSIS
A. Blackberry Profile
BlackBerry is a line of mobile e-mail and smartphone devices
developed and designed by Canadian company Research In Motion (RIM)
since 1999.
BlackBerry phones function as a personal digital assistant and portable
media player (www.wikipedia.com). BlackBerry phones are primarily known
for their ability to send and receive (push) Internet e-mail wherever mobile
network service coverage is present, or through Wi-Fi connectivity.
BlackBerry phones support a large array of instant messaging features,
including BlackBerry Messenger.
1. History
The first BlackBerry device, the 850, was introduced in 1999 as a two-
way pager in Munich, Germany. In 2002, the more commonly known
smartphone BlackBerry was released, which supports push e-mail, mobile
telephone, text messaging, Internet faxing, Web browsing and other
wireless information services. It is an example of a convergent device. The
original BlackBerry devices, the RIM 850 and 857, used the DataTac
network.

58
BlackBerry first made headway in the marketplace by concentrating on
e-mail. RIM currently offers BlackBerry e-mail service to non-BlackBerry
devices, such as the Palm Treo, through its BlackBerry Connect software.
The original BlackBerry device had a monochrome display, but all
current models have color displays. All models except for the Storm, series
had a built-in QWERTY keyboard, optimized for "thumbing", the use of
only the thumbs to type. The Storm 1 and Storm 2 include a SureType
keypad for typing. Originally, system navigation was achieved with the
use of a scroll wheel mounted on the right side of phones prior to the 8700.
The trackwheel was replaced by the trackball with the introduction of the
Pearl series which allowed for 4 way scrolling. The trackball was replaced
by the optical trackpad with the introduction of the Curve 8500 series.
Models made to use iDEN networks such as Nextel and Mike also
incorporate a push-to-talk (PTT) feature, similar to a two-way radio.
2. Operating System
The operating system used by BlackBerry devices is a proprietary
multitasking environment developed by RIM. The operating system is
designed for use of input devices such as the track wheel, track ball, and
track pad. The OS provides support for Java MIDP 1.0 and WAP 1.2.
Previous versions allowed wireless synchronization with Microsoft
Exchange Server e-mail and calendar, as well as with Lotus Domino e-
mail. The current OS 5.0 provides a subset of MIDP 2.0, and allows
complete wireless activation and synchronization with Exchange e-mail,

59
calendar, tasks, notes and contacts, and adds support for Novell
GroupWise and Lotus Notes. Blackberry Torch features Blackberry 6.
Third-party developers can write software using these APIs, and
proprietary BlackBerry APIs as well. Any application that makes use of
certain restricted functionality must be digitally signed so that it can be
associated to a developer account at RIM. This signing procedure
guarantees the authorship of an application but does not guarantee the
quality or security of the code. RIM provides tools for developing
applications and themes for BlackBerry. Applications and themes can be
loaded onto BlackBerry devices through BlackBerry App World, Over The
Air (OTA) through the BlackBerry mobile browser, or through BlackBerry
Desktop Manager.
May 2011: Since BlackBerry 7, RIM will use Bing search engine and
also dropped support for Adobe Flash (ADBE) and instead opted to use
the QNX operating system to support any Flash content in devices' web
browsers.
3. Connectivity
BlackBerry handhelds are integrated into an organization's e-mail
system through a software package called BlackBerry Enterprise Server
(BES).
BES acts as an e-mail relay for corporate accounts so that users always
have access to their e-mail. The software monitors the user's local Inbox,
and when a new message comes in, it picks up the message and passes it to

60
RIM's Network Operations Center (NOC). The messages are then relayed
to the user's wireless provider, which in turn delivers them to the user's
BlackBerry device.
The primary alternative to using BlackBerry Enterprise Server is to use
the BlackBerry Internet Service. BlackBerry Internet Service, or BIS is
available in 91 countries internationally. BlackBerry Internet Service was
developed primarily for the average consumer rather than for the business
consumer. BlackBerry Internet Service allows POP3 and IMAP email
integration for an individual personal user. BlackBerry Internet Service
allows up to 10 email accounts to be accessed, including many popular
email accounts such as Gmail, Hotmail, Yahoo and AOL. BlackBerry
Internet Service also allows for the function of the push capabilities in
various other BlackBerry Applications. Various applications developed by
RIM for BlackBerry utilize the push capabilities of BIS, such as the Instant
Messaging clients, Google Talk, ICQ, Windows Live Messenger and
Yahoo Messenger. Social Networks Facebook, Myspace and Twitter's
notification system is accessed through BIS, allowing for push
notifications for them.
4. Supported Software
a. Blackberry App World
BlackBerry App World is an application distribution service and
application by Research In Motion (RIM) for a majority of
BlackBerry devices. The service provides BlackBerry users with an

61
environment to browse, download, and update third-party
applications. The service went live on April 1, 2009.
b. BlackBerry Messenger
Newer BlackBerry devices use the proprietary BlackBerry
Messenger, also known as BBM, software for sending and receiving
instant messages via BlackBerry PIN. Blackberry Messenger is one of
the fastest messengers on a smartphone.
c. Third-party software
Third-party software available for use on BlackBerry devices
includes full-featured database management systems, which can be
used to support customer relationship management clients and other
applications that must manage large volumes of potentially complex
data.
5. BlackBerry PIN
BlackBerry PIN is an eight character hexadecimal identification
number assigned to each BlackBerry device. PINs cannot be changed
manually on the device (though BlackBerry technicians are able to reset or
update a PIN server-side), and are locked to each specific BlackBerry.
BlackBerrys can message each other using the PIN directly or by using the
BlackBerry Messenger application. BlackBerry PINs are tracked by
BlackBerry Enterprise Servers, and the BlackBerry Internet Service, and
are used to direct messages to a BlackBerry device. Emails and any other
messages, such as those from the BlackBerry Push Service, are typically

62
directed to a BlackBerry's PIN. The message can then be routed by a RIM
Network Operations Center, and sent to a carrier, which will deliver the
message the last mile to the device.
6. Government regulation
Some countries have expressed reservations about BlackBerry's
strong encryption and the fact that data is routed through Research In
Motion's servers, which are outside the legal jurisdictions of those
countries. The United Arab Emirates considering the BlackBerry as a
"security threat" for this reason, with the former having earlier been
reported as trying to get users to install an "update" on their BlackBerry
devices, ostensibly for performance enhancement, but which turned out to
be spyware that allowed phone call and email monitoring. The update and
subsequent performance deteriorating spyware were reportedly generated
by UAE company Etisalat, about which it commented minimally. When
questioned in a BBC Click interview about how Research in Motion has
responded to the demands of India and other governments in the Middle
East, RIM co-CEO Mike Lazaridis objected to the questioning and said the
interview was over.
a. United Arab Emirates
On August 1, 2010 Telecommunication Regulatory Authority
(TRA) of The United Arab Emirates officially announced the
suspension of BlackBerry Messenger, BlackBerry Email, and
BlackBerry Web browsing services in the country as of October 11,

63
2010. This measure was taken due to failed attempts in having the
service hosted locally as per the UAE Telecommunication regulations.
On October 8, 2010 the TRA officially announced that the
BlackBerry services such as BBM, e-mail, and web browsing will
continue to work as before.
b. Indonesia
On January 10, 2011 RIM agreed to install web filters in the
Indonesian market, following the request by Indonesia's Ministry of
Communication and Information Technology to filter pornographic
websites.On January 17, 2011 RIM met Indonesia's Communications
and Information Technology minister and signed a commitment to
abide the law. The deadline was January 21, 2011. Shortly before the
deadline, Blackberry filtered all adult content in Indonesia.
Furthermore, RIM is in discussions with the Indonesian Ministry of
Information to build a local server network of aggregrators to cut
communications costs, to hire more local workers, and plans to
establish 40 service centers in Indonesia.
c. India
Indian authorities have asked RIM to provide means to access the
encrypted data for calls to, from, or within India, following concerns
that it could be used by terrorist and rebel groups to carry out attacks
on India. In the November 2008 Mumbai attacks, terrorists used
mobile and satellite phone technologies after which security agencies

64
and the Indian government have become more strict and alert towards
communication within the country. BlackBerry has indicated
willingness to set up a server in India by October, 2010 and giving the
country limited access to its encryption technology. However, this will
only apply to personal devices which route via RIM's infastructure:
organisations providing their own BlackBerry Enterprise Server will
continue to have encrypted message flow, to which even RIM
themselves will not have access. On January 31, 2011 India refused
limited access offer and demanded full access.
d. Saudi Arabia
Saudi Arabia has since reportedly continued its service of
BlackBerry Messenger. Saudi Arabia has also threatened to ban the
service, but it was reported close to reaching an agreement with RIM
to set up a server for the service inside the Kingdom.
e. Barbados
In 2010 the government officials of Barbados announced a sharp
increase in crime due to thefts of cell phones, with BlackBerrys being
the usual target. The Commissioner of police in the country
announced steps were being taken to make stolen BlackBerry devices
less attractive in the country.

65
B. Respondent Profile
Youth segment in Indonesia according to Mix Interactive, Group of SWA
Media Inc. in Brand Activation Workshop Series currently reaches 40% of
the total population of Indonesia. No wonder that many brands competing to
work on this segment. They perform a variety of ways to interact with groups
that vulnerable of brand switching.
Youth segment usually are university student. The respondent are Ciputat
university students. The reason why researcher choose Ciputat because
Ciputat has some good universities and the location can be accessed easily.
Those are Universitas Islam Negeri Jakarta, Universitas Muhammadiyah
Jakarta, Sekolah Tinggi Ilmu Ekonomi Ahmad Dahlan, etc.
Researcher distibute 115 questionnaires to 115 Ciputat university student
but according to AMOS there are 3 outlier data that have to be eliminated. So,
the data that will be processed are 112 data. The explanation will given in
SEM analysis.
Table 4.1
Respondent Statistics
Gender Age University Operator Income
N Valid 112 112 112 112 112
Missing 3 3 3 3 3

66
1. Gender
Table 4.2
Gender
Frequency Percent Valid Percent
Cumulative
Percent
Valid Male 58 50.4 51.8 51.8
Female 54 47.0 48.2 100.0
Total 112 97.4 100.0
Missing System 3 2.6
Total 115 100.0
From the table we can see the total number of male are 58 (50,4%)
while female are 54 (47%). Missing system are outlier data. We can
conclude there is no dominant user from gender perspective.
2. Age
Table 4.3
Age
Cumulative
Percent
Valid 18 - 22 years old 99 86.1 88.4 88.4
> 22 years old 13 11.3 11.6 100.0
Total 112 97.4 100.0
Total 115 100.0
From the table we can see the total number of 18 - 22 years old are 99
(86,1%) while > 22 years old are 54 (11,3%). Missing system are outlier

67
data. We can conclude that younger people in university dominated the
number of Blackberry user.
3. University
Table 4.4
University
Cumulative
Percent
Valid UIN Jakarta 48 41.7 42.9 42.9
UMJ 44 38.3 39.3 82.1
Others 20 17.4 17.9 100.0
Total 112 97.4 100.0
Total 115 100.0
From the table we can see the total number of UIN Jakarta Students are
48 (41,7%), UMJ are 44 students (38,3%) while others student are 20
(17,4%). Missing system are outlier data. We can conclude that bigger
university will affected to the number of Blackberry user.
4. Operator
Table 4.5
Operator
Cumulative
Percent
Valid Telkomsel 25 21.7 22.3 22.3
Indosat 59 51.3 52.7 75.0
XL 27 23.5 24.1 99.1
Others 1 .9 .9 100.0
Total 112 97.4 100.0

68
Total 115 100.0
From the table we can see the total number of Telkomsel customers are
25 (21,7%), Indosat are 59 customers (51,3%), XL are 27 customers (23,5
%) while others is 1 customers (0,9%). Missing system are outlier data.
We can conclude in youth segment Indosat is market leader.
5. Income
Table 5.6
Income
Cumulative
Percent
Valid < Rp. 1.000.000,- 63 54.8 56.3 56.3
Rp. 1.000.000,- – Rp.
2.000.000,-
39 33.9 34.8 91.1
Rp. 2.000.000,- - Rp.
3.000.000,-
5 4.3 4.5 95.5
> Rp. 3.000.000,- 5 4.3 4.5 100.0
Total 112 97.4 100.0
Total 115 100.0
From the table we can see the total income of student: < Rp.
1.000.000,- are 63 students (54,8%), Rp. 1.000.000,- – Rp. 2.000.000,-
are 39 students, Rp. 2.000.000,- - Rp. 3.000.000,- are 5 students (4.3 %),
and > Rp. 3.000.000,- are 5 students (4,3%). Missing system are outlier
data. We can conclude most of student that use Blackberry has income

69
below <1,000,000. It is acceptable because usually they still in parent’s
responsibility.
C. Reliability and Validity
1. Reliability
Table 4.7
Reliability Score
No Variable Score Status
1 Perceived Value ( Value) 0.631 Reliable
2 Service Quality (Servqual) 0.675 Reliable
3
Customer Satisfaction
(Satisfaction)
0.691 Reliable
4 Trust 0.633 Reliable
5 Customer Loyalty 0.639 Reliable
From the table, we can see all valiable are reliable because all variable
have score > 0.60. So, next we can do validity test.
2. Validity
Table 4.8
Validity Score
No Indicator Score Status
1 Ease ,440 Valid
2 OS ,392 Valid

70
3 Design ,404 Valid
4 Audio ,327 Valid
5 Battery ,247 Valid
6 Feature ,361 Valid
7 Network ,343 Valid
8 Coverage ,488 Valid
9 Promotion ,279 Valid
10 Cost ,329 Valid
11 Topup ,353 Valid
12 CS ,441 Valid
13 Bundled ,464 Valid
14 Quality ,320 Valid
15 Price ,502 Valid
16 Access ,380 Valid
17 Service ,606 Valid
18 Emotional ,442 Valid
19 Assertion ,468 Valid
20 Action ,590 Valid
21 Condition ,301 Valid
22 Intention ,469 Valid
23 Recommendation ,469 Valid

71
In validity test, score of corrected iten total correlation used as valid
score. Because in this research there are 23 items dan it use likert scale, so the
indikator is valid if R score > r table. r table for 5 % is 0.1840. Because all
indicator has score > 0.1840. So all of indicators are valid.
D. Structure Equation Modeling
1. Estimate Degree of Freedom
In statistics, the number of degrees of freedom is the number of values
in the final calculation of a statistic that are free to vary.Estimates of
statistical parameters can be based upon different amounts of information or
data. The number of independent pieces of information that go into the
estimate of a parameter is called the degrees of freedom (df). In general, the
degrees of freedom of an estimate is equal to the number of independent
scores that go into the estimate minus the number of parameters used as
intermediate steps in the estimation of the parameter itself (which, in sample
variance, is one, since the sample mean is the only intermediate step).
In SEM model, df can be known by formula:
df = ½ [(p) . (p+1)} – k]
where :
df = number of distinct sample moment – number of distinct parameters
to be estimated
p = Total number of manifest variable
k = The number of parameter that will be estimated

72
Figure 4.1
Computation of degrees of freedom (Default model)
Number of distinct sample moments: 276
Number of distinct parameters to be estimated: 52
Degrees of freedom (276 - 52): 224
This portion of the output shows how Amos arrives at degrees of
freedom as the difference between the number of distinct sample moments
and the number of distinct parameters that have to be estimated.
The number of distinct sample moments always includes variances and
covariances. It also includes sample means when estimate means and
intercepts.
In counting up the number of distinct parameters to be estimated,
several parameters that are constrained to be equal to each other count as a
single parameter. Parameters that are fixed at a constant value do not count at
all. This is why the 'number of distinct parameters to be estimated' can be less
than the total number of regression weights, variances, covariances, means
and intercepts in the model.
In the analysis of data from several groups, the number of distinct
sample moments and the number of distinct parameters to be estimated are
grand totals over all groups.
2. Normality and Outlier Data
In statistics, an outlier is an observation that is numerically distant from
the rest of the data. The step to detect it by comparing cr skweness or kurtosis
with certain standar.

73
The comparison tool is z number. Generally, z table that used in 99%
level. In that level, the significant number is 100 % - 99 % = 1 %, and z
number is ± 2.58. So, the disribution is normal if cr skweness or cr kurtosis
between – 2.58 and + 2.58.
Table 4.9
Assessment of normality (Group number 1)
Variable min max skew c.r. kurtosis c.r.
Network 1,000 5,000 -,493 -2,156 -,114 -,250
Coverage 1,000 5,000 -,241 -1,055 -,592 -1,295
Promotion 1,000 5,000 -,671 -2,939 ,996 2,180
Cost 1,000 5,000 -,285 -1,249 -,780 -1,707
Topup 2,000 5,000 -,729 -3,190 ,100 ,219
CS 2,000 5,000 -,689 -3,016 1,025 2,243
Bundled 2,000 5,000 -,364 -1,595 -,545 -1,192
Feature 3,000 5,000 -,086 -,377 -,725 -1,587
Battery 3,000 5,000 -,348 -1,524 -,712 -1,559
Audio 2,000 5,000 -,259 -1,133 -,053 -,116
Design 2,000 5,000 ,081 ,356 -,597 -1,306
OS 2,000 5,000 -,040 -,176 -,272 -,595
Ease 2,000 5,000 -,250 -1,095 ,014 ,031
Access 1,000 5,000 -,826 -3,618 ,374 ,819
Emotional 1,000 5,000 -,882 -3,860 1,768 3,871
Service 1,000 5,000 -,528 -2,313 -,433 -,949
Price 1,000 5,000 -,451 -1,974 -,632 -1,384
Quality 1,000 5,000 -,574 -2,513 ,207 ,452
Condition 2,000 5,000 -,063 -,274 -,269 -,589
Action 2,000 5,000 -,226 -,988 ,366 ,802
Assertion 2,000 5,000 -,292 -1,279 1,298 2,841
Intention 1,000 5,000 -,032 -,139 -,569 -1,247
Recommendation 1,000 5,000 -,365 -1,599 ,110 ,240
Multivariate 49,692 7,857
From the table we can see there are abnormal distribution. That are
emotional (3.871) and assertion (2.841). So we have to data which are outlier
data.

74
Table 4.10
Observations farthest from the centroid (Mahalanobis distance) (Group number 1)
Observation number Mahalanobis d-squared p1 p2
51 51,072 ,001 ,074
89 50,534 ,001 ,004
43 50,117 ,001 ,000
40 43,278 ,006 ,007
41 42,194 ,009 ,003
44 41,252 ,011 ,002
65 39,265 ,019 ,006
106 37,220 ,031 ,026
104 37,175 ,031 ,010
42 36,739 ,035 ,007
68 35,980 ,041 ,008
56 35,743 ,044 ,005
9 34,443 ,059 ,018
14 33,173 ,078 ,065
83 33,121 ,079 ,038
58 32,630 ,088 ,044
32 32,561 ,089 ,026
70 32,527 ,090 ,014
92 32,415 ,092 ,009
78 31,720 ,106 ,018
107 30,688 ,131 ,070
60 30,436 ,137 ,065
62 30,434 ,137 ,040
19 30,331 ,140 ,028
57 29,941 ,151 ,036
18 29,824 ,155 ,027
64 29,634 ,160 ,024
2 29,457 ,166 ,021
69 29,241 ,172 ,020
34 29,068 ,178 ,017
55 28,494 ,198 ,038
81 27,524 ,234 ,158
12 27,087 ,252 ,225
75 26,855 ,262 ,236
102 26,677 ,270 ,232
17 26,673 ,270 ,175
48 26,504 ,278 ,170
90 25,658 ,317 ,415

75
45 25,531 ,324 ,394
50 25,314 ,334 ,413
27 25,012 ,350 ,474
1 24,856 ,358 ,468
84 24,845 ,358 ,397
82 24,676 ,367 ,400
47 24,005 ,404 ,639
37 23,000 ,461 ,920
88 22,772 ,474 ,934
13 22,743 ,476 ,912
24 22,687 ,479 ,891
35 22,652 ,481 ,862
31 22,432 ,494 ,882
73 22,371 ,498 ,859
71 22,223 ,507 ,860
61 22,051 ,517 ,868
23 21,811 ,532 ,893
63 21,776 ,534 ,864
115 21,757 ,535 ,826
11 21,749 ,535 ,777
91 21,375 ,558 ,858
114 21,158 ,571 ,879
5 21,080 ,576 ,861
96 21,069 ,577 ,820
52 21,007 ,581 ,791
98 20,985 ,582 ,742
16 20,950 ,584 ,695
110 20,862 ,589 ,670
113 19,729 ,658 ,963
79 19,581 ,667 ,964
67 19,449 ,675 ,963
74 19,290 ,684 ,966
30 19,090 ,696 ,972
109 18,882 ,708 ,977
7 18,799 ,713 ,972
46 18,480 ,731 ,985
112 18,452 ,733 ,978
53 18,186 ,747 ,985
97 18,072 ,754 ,984
93 17,960 ,760 ,982

76
54 17,945 ,760 ,972
72 17,749 ,771 ,976
29 17,702 ,773 ,967
94 17,601 ,779 ,962
28 17,258 ,796 ,979
95 17,086 ,805 ,981
39 16,622 ,827 ,994
86 16,444 ,836 ,994
3 16,439 ,836 ,990
100 16,210 ,846 ,992
87 16,156 ,848 ,988
22 16,000 ,855 ,987
38 15,965 ,857 ,980
85 15,943 ,858 ,967
59 15,864 ,861 ,956
8 15,273 ,885 ,988
111 15,213 ,887 ,982
66 15,021 ,894 ,982
15 14,943 ,897 ,973
80 14,677 ,906 ,978
99 14,230 ,920 ,990
10 14,199 ,921 ,981
Data can be mentioned as outlier data if it has p1 and p2 number below
0.05. From the table we can see data 51, 89 and 43 are outlier because their
p1 and p2 number below 0.05. So, that data must be eliminated.
Table 4.11
Assessment of normality (Group number 1)
Network 1,000 5,000 -,507 -2,190 -,128 -,277
Coverage 2,000 5,000 -,150 -,648 -,749 -1,618
Promotion 2,000 5,000 -,336 -1,451 -,015 -,032
Cost 1,000 5,000 -,260 -1,122 -,794 -1,714
Topup 2,000 5,000 -,752 -3,250 ,182 ,393
CS 2,000 5,000 -,734 -3,170 1,132 2,446
Bundled 2,000 5,000 -,365 -1,576 -,459 -,993

77
Feature 3,000 5,000 -,085 -,368 -,694 -1,499
Battery 3,000 5,000 -,332 -1,434 -,714 -1,542
Audio 2,000 5,000 -,284 -1,227 -,026 -,057
Design 2,000 5,000 ,076 ,328 -,563 -1,217
OS 2,000 5,000 ,054 ,233 -,383 -,827
Ease 2,000 5,000 -,276 -1,193 ,130 ,280
Access 2,000 5,000 -,670 -2,894 -,183 -,395
Emotional 2,000 5,000 -,506 -2,188 ,481 1,039
Service 2,000 5,000 -,428 -1,849 -,775 -1,675
Price 2,000 5,000 -,369 -1,595 -,910 -1,966
Quality 2,000 5,000 -,407 -1,760 -,113 -,245
Condition 2,000 5,000 -,082 -,354 -,151 -,326
Action 2,000 5,000 -,276 -1,193 ,588 1,271
Assertion 3,000 5,000 ,034 ,148 ,495 1,070
Intention 1,000 5,000 ,015 ,065 -,640 -1,383
Recommendation 2,000 5,000 -,101 -,438 -,465 -1,005
Multivariate 35,224 5,496
Now, the data already normal because all of the data has cr skweness or
cr kurtosis between – 2.58 and + 2.58.
3. Measurement Model Test
Measurement model is part of SEM model that consist of laten variable
(construct) and some indicators. The reason why we must do test is to know
how much indicators can explain laten variable.
There are 3 tools :
a. Absolute Fit Indices
1) Chi Square
The objective is to know is sample matriks
covariance is different significantly with estimated matriks

78
covariance. But, because the number of indicators is many.
The model must be accompanied by others.
Figure 4.2
Result (Default model)
Minimum was achieved
Chi-square = 412,430
Degrees of freedom = 224
Probability level = ,000
2) CMIN
Minimum value of the discrepancy function C
Table 4.12
CMIN
Model NPAR CMIN DF P CMIN/DF
Default model 52 412,430 224 ,000 1,841
Saturated model 276 ,000 0
Independence model 23 835,417 253 ,000 3,302
- Default model is current model
- Saturated model is the result of test in condition where
just identified happened
- Independence model is the result in condition indicator
be estimated has no relationship to construct variable.
So, good model is model with default model
number between saturated model number and
independence model number.

79
We can see on the table, 4 tools (NPAR, CMIN,
DF) show default model number between saturated model
number and independence model number.
3) RMR (root mean square residual) and The GFI
(goodness of fit index)
The RMR (root mean square residual) is the square
root of the average squared amount by which the sample
variances and covariances differ from their estimates
obtained under the assumption that the model is correct
Table 4.13
RMR, GFI
Model RMR GFI AGFI PGFI
Default model ,053 ,753 ,696 ,611
Saturated model ,000 1,000
Independence model ,101 ,506 ,461 ,464

80
We can see on the table, 2 tools (RMR, GFI)
show default model number between saturated model
b. Incremental Fit Indices
1) NFI (Normed Fit Index)
The Bentler-Bonett (Bentler & Bonett, 1980) normed fit
index ( NFI), or in the notation of Bollen (1989b) can
be written.
,
Table 4.14
Baseline Comparisons
Model
NFI
Delta1
RFI
rho1
IFI
Delta2
TLI
rho2
CFI
Default model ,506 ,442 ,692 ,635 ,676
Saturated model 1,000 1,000 1,000
Independence model ,000 ,000 ,000 ,000 ,000

81
We can see on the table, 3 tools (NFI, IFI, CFI)
show default model number between saturated model
c. Parsimony Fit Indices
James, Mulaik and Brett, 1982 suggested multiplying the
NFI by a "parsimony index" so as to take into account the
number of degrees of freedom for testing both the model being
evaluated and the baseline model. Mulaik, et al. (1989)
suggested applying the same adjustment to the GFI. Amos also
applies a parsimony adjustment to the CFI.
Table 4. 15
Parsimony-Adjusted Measures
Model PRATIO PNFI PCFI
Default model ,885 ,448 ,599
Saturated model ,000 ,000 ,000
Independence model 1,000 ,000 ,000
So, good model is model with default model number
between saturated model number and independence model
number.

82
We can see on the table, 3 tools (PRATIO, PNFI, PCFI)
show default model number between saturated model number
and independence model number.
4. The Analysis of Relationship Between Indicators and Construct
Next, after model has valid, we see are indicators in construct variable
are it’s part or be able to explain the construct. That process named construct
validity test and can be done by:
If the indicator explain the construct, so the indicator will has high
factor loading and high variance extracted.
Table 4. 16
Standardized Regression Weights: (Group number 1 - Default model)
Estimate
Satisfaction <--- Value -,099
Satisfaction <--- Servqual ,678
Satisfaction <--- ea ,789
Trust <--- Satisfaction ,291
Trust <--- eb ,957
Loyalty <--- Satisfaction ,292
Loyalty <--- Trust ,357
Loyalty <--- ec ,852
Recommendation <--- Loyalty ,656
Intention <--- Loyalty ,637
Assertion <--- Trust ,694
Action <--- Trust ,868
Condition <--- Trust ,426
Quality <--- Satisfaction ,289
Price <--- Satisfaction ,683
Service <--- Satisfaction ,800
Emotional <--- Satisfaction ,575
Access <--- Satisfaction ,389
Ease <--- Value ,670
OS <--- Value ,670
Design <--- Value ,456
Audio <--- Value ,392

83
Estimate
Battery <--- Value ,224
Feature <--- Value ,434
Bundled <--- Servqual ,620
CS <--- Servqual ,618
Topup <--- Servqual ,419
Cost <--- Servqual ,527
Promotion <--- Servqual ,338
Coverage <--- Servqual ,544
Network <--- Servqual ,387
Column estimate explain factor loadings each indicator. The higher
score shows the strong relationship. Value influenced most by the ease and
OS. Servqual by bundled. Satisfaction by service, trust by action and loyalty
by recomendation.
Table 4. 17
Correlations: (Group number 1 - Default model)
Estimate
Value <--> Servqual ,682
The table shows the relationship between construct variable is good
enough (>0.5) and the value is positive. It means the higher value affected
servqual getting higher and the loer value affected servqual getting lower.
Table 4. 18
Squared Multiple Correlations: (Group number 1 - Default model)
Estimate
Satisfaction ,378
Trust ,085
Loyalty ,273
Network ,150
Coverage ,296

Perceived value, service quality, customer satisfaction, trust and loyalty on blackberry user (2011)

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