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THE ANALYSIS OF RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND WILLINGNESS TO PAY
Case Study of Pre-Paid GSM University Student Market in Bogor Area
PAPER SCRIPT
By : MUHAMMAD GALUH PRAYOGA
NRP : 05120049
MARKETING MANAGEMENT PROGRAM STUDY KESATUAN SCHOOL OF ECONOMICS
BOGOR 2009
THE ANALYSIS OF RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND WILLINGNESS TO PAY
Case Study of Pre-Paid GSM University Student Market in Bogor Area
Paper Script
submitted in fulfillment of the requirement for the S1 degree in Marketing Management Program Study
Kesatuan School of Economics
By : MUHAMMAD GALUH PRAYOGA
NRP : 05120049
MARKETING MANAGEMENT PROGRAM STUDY KESATUAN SCHOOL OF ECONOMICS
BOGOR 2009
THE ANALYSIS OF RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND WILLINGNESS TO PAY
Case Study of Pre-Paid GSM University Student Market in Bogor Area
PAPER SCRIPT
Performed and approved in the S1 examination of
Kesatuan School of Economics on,
Day : Saturday
Date : July 18, 2009
Authorized,
President of STIE Kesatuan Head of Management Program Study
Dr. H. Moermahadi S. Djanegara, SE., Ak., MM. Sutarti, SE., MM
THE ANALYSIS OF RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND WILLINGNESS TO PAY
Case Study of Pre-Paid GSM University Student Market in Bogor Area
PAPER SCRIPT
Approved by Supervisor,
Dr. Adi S. Widjojo, DMS
Performed in the S1 degree examination
and confirmed PASSED on the date shown below
Bogor, July 18, 2009
Examiner I Examiner II
Dr. Saefudin Zuhdi, Drs., MM. Dr. Yulia Nurendah, SE., MM.
v
ABSTRACT
MUHAMMAD GALUH PRAYOGA. 05120049. The Analysis of Relationship between Customer Satisfaction and Willingness to Pay. Case Study of Pre-Paid GSM University Student Market in Bogor Area. Under supervisory of ADI S. WIDJOJO
The research is performed to analyze the relationship between customer satisfaction and willingness to pay, with the case study of pre-paid GSM university student market in Bogor area. The regression calculation obtained from empirical data results in equation 17.1 57 . The coefficient is different from zero, which means that the relationship between customer satisfaction and willingness to pay is exist and positive. The hypothesis test shows that the relationship is significant with the value of statistics (40.345) > table (1.943). Moreover, the graphical plots of residuals reveal that the regression model for the relationship is appropriate, since the assumptions of residual analysis are fulfilled by the equation.
The second analysis is to examine the strength of the relationship between customer satisfaction and willingness to pay. The result shows that the relationship is strong and positive with the value of 99.6%. The hypothesis test of the correlation coefficient results in the rejection of null hypothesis with the value of statistics (38.671) > table (1.943). Thus, the author concludes that the relationship between customer satisfaction and willingness to pay in pre-paid GSM university student exist significantly.
Keywords: Customer Satisfaction, Willingness to Pay
vi
PREFACE
Alhamdulillah, by the blessing of Allah SWT., the author is given strength
and ease to accomplish the paper script in time. This paper, by the title “The
Analysis of Relationship between Customer Satisfaction and Willingness to Pay”
is submitted in fulfillment of the requirement for the S1 degree of Economics at
Kesatuan School of Economics.
The author realizes that this task was not done by a one man’s efforts, but
it was also supported by all sorts of sides surrounding the author. Therefore, the
author would like to deliver the deepest gratitude to the following for their sincere
help and participation.
1. Dr. H. Moermahadi Soerja Djanegara, SE.,Ak., MM. and Mrs. Sutarti,
SE.,MM. for the opportunity to compose a paper in English writing.
2. Dr. Adi S. Widjojo, DMS. as the research supervisor for his guidance in the
process of composing the paper.
3. Drs. Enjang Tachyan B., Ak., Msi. for the inspiration to make an English
paper script, as well as inspiring the author to accomplish the paper.
4. Dr. Saefudin Zuhdi, Drs., MM., Dr. Yulia Nurendah, SE.,MM., and Mrs.
Ratih Puspitasari, SE., MBA. for a joyful moment in the examination and
contributions in perfecting the paper.
5. Drs. J. Sukadi for the aid in making the paper more feasible as English
paper writing.
6. Mr. Sujana, SE., MM., Drs. Aang Munawar, MM., Ms. Yayuk Nurjanah, SE.,
MM., Mr. Agus Pranamulia (STIE Bina Niaga), and Mr. Toni Kurniawan
(IPB) for their assists and opportunities to perform the research.
vii
7. Mamah “Enin” Elly Djuhariah for her incomparable love, patience and
prayers. “Apa” Dr. Yusuf Jafarsidik, MSc (Alm), for the valuable memories,
thoughts, and faith.
8. Brothers, sisters, the “Ghemsyut” nephews and nieces for their love,
supports, and happiness in the family.
9. Ibu Husnul, Kang Firman, Kang Dadan, and someone who doesn’t want to
be mentioned, for their help and kindness in library service.
10. Ade Yusuf (Pemirsa!), Agus A., Riana H.(Pada Ukurannya..), Alyn, Nancy,
Vina, and many other friends who always present cheerfulness at campus.
11. Halida Dyah, Arif Lunardi, Mas Didit, Mas Agus S., Mas Yatna, Mas
Rojikun, Mas Nur Zakaria, Teteh Trina, and all friends in PT Nutrifood for
their help, support and spirit boost to the author.
12. Bang Sudin for the statistics software, Yani and other statistics students of
IPB who has given the author insights about statistics knowledge.
13. Ultimately, Ratih “Adek” Hatmaninggita for the love, caring, and faith.
This is a path to our dreams…
Bogor, July 2009
Muhammad Galuh Prayoga
viii
TABLE OF CONTENT
ABSTRACT .......................................................................... v PREFACE ............................................................................. vi TABLE OF CONTENT .......................................................... viii LIST OF TABLES .................................................................. x LIST OF FIGURES .............................................................. xi
CHAPTER I INTRODUCTION .................................................................. 1 1.1 Background.................................................................. 1 1.2 Problem Identification .................................................. 4 1.3 Research Objectives .................................................... 4 1.4 The Use of Research ................................................... 5
CHAPTER II LITERATURE REVIEW ........................................................ 6 2.1 Theoretical Framework .................................................. 6
2.1.1 Marketing ............................................................ 6 2.1.2 Marketing Management ...................................... 7 2.1.3 Product ............................................................... 7 2.1.4 Service ............................................................... 10 2.1.5 Consumer Behavior ............................................ 12 2.1.6 Customer Expectations ...................................... 15 2.1.7 Customer Value and Satisfaction ....................... 18
2.1.7.1 Customer Value .................................... 18 2.1.7.2 Customer Satisfaction .......................... 19 2.1.7.3 Determinants of Satisfaction and
Dissatisfaction ...................................... 20 2.1.8 Price ................................................................... 21 2.1.9 Pricing of Services .............................................. 22 2.1.10 Willingness to Pay .............................................. 27
2.2 Conceptual Framework .................................................. 28 2.3 Premise and Hypothesis ................................................ 29
2.3.1 Premises ............................................................ 29 2.3.2 Hypotheses ........................................................ 30
CHAPTER III RESEARCH METHODOLOGY ............................................. 31 3.1 The Overview of Mobile Telecommunication
Industry in Indonesia ...................................................... 31 3.1.1 Mobile Telecommunication Technologies in Indonesia ............................................................ 37 3.1.2 GSM Providers in Indonesia ............................... 39
3.1.2.1 PT Telkomsel ........................................ 39 3.1.2.2 PT Indosat ............................................ 40 3.1.2.3 PT Excelcomindo Pratama ................... 42 3.1.2.4 PT Natrindo Telepon Seluler ................ 44
ix
3.1.2.5 Hutchison Charoen Pokphand Telecom (HCPT) ................................... 46
3.1.3 Market Share of Pre-Paid GSM Provider ........... 47 3.2 Site and Period of Research .......................................... 47 3.3 Research Methods ......................................................... 47
3.3.1 Variables Operational ......................................... 48 3.3.2 Types and Source of Data .................................. 48 3.3.3 Data Collecting Method ...................................... 49 3.3.4 Analysis Method ................................................. 50
3.3.4.1 Validity Test .......................................... 50 3.3.4.2 Reliability Test ...................................... 51 3.3.4.3 Regression Analysis ............................. 52 3.3.4.4 Coefficient of Correlation ...................... 53
CHAPTER IV RESULT AND DISCUSSION ................................................ 55 4.1 Number of Samples ....................................................... 57 4.2 Validity Test ................................................................... 57 4.3 Reliability Test ................................................................ 60 4.4 Respondents Profile ....................................................... 62 4.5 Regression Analysis: Customer Satisfaction and Willingness to Pay .......................................................... 65
4.5.1 Residual Analysis ............................................... 71 4.5.1.1 Plot of the Residual versus Values of Customer Satisfaction .......... 72 4.5.1.2 Plot of the Residual versus Values of Willingness to Pay ................ 73 4.5.1.3 Plot of the Standardized Residual versus Values of Customer Satisfaction .......................... 73
4.6 Correlation Analysis: Customer Satisfaction and Willingness to Pay .......................................................... 74
CHAPTER V CONCLUSION AND SUGGESTION .................................... 78 5.1 Conclusion ..................................................................... 78 5.2 Suggestion ..................................................................... 79
REFERENCES
APPENDIX
x
LIST OF TABLES
2.1 Ways Services Marketers can Influence Factors .................................. 17
3.1 List of Cellular Providers with the Number of Subscribers .................... 35
3.2 List of FWA Providers with the Number of Subscribers ........................ 35
3.3 Milestone of PT Excelcomindo Pratama ............................................... 44
3.4 Variables Operational: Customer Satisfaction and Willingness to Pay . 48
3.5 Quantitative Data .................................................................................. 49
3.6 Qualitative Data ..................................................................................... 49
4.1 Customer Satisfaction Manipulation ...................................................... 56
4.2 Scenarios of Provider’s Offerings .......................................................... 56
4.3 Validity Test of First Scenario ............................................................... 57
4.4 Validity Test of All Questions in Scenario One ...................................... 59
4.5 Reliability Test of First Scenario ............................................................ 60
4.6 Respondents Profile: Range of Age ...................................................... 62
4.7 Respondents Profile: Gender ................................................................ 62
4.8 Respondents Profile: City of Origin ....................................................... 63
4.9 Respondents Profile: University / College ............................................. 63
4.10 Respondents Profile: Employment Status ............................................. 64
4.11 Respondents Profile: In-Use Brands of Cellular Products .................... 64
4.12 Respondents Profile: Range of Expenditure ......................................... 65
4.13 Means of Customer Satisfaction and Willingness to Pay Value ............ 66
4.14 Linear Regression ................................................................................. 66
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LIST OF FIGURES
2.1 The Consumer Decision-Making Process ............................................. 13
2.2 Possible Levels of Customer Expectations ........................................... 16
2.3 Customer Satisfaction Outcomes .......................................................... 20
2.4 Conceptual Framework ......................................................................... 28
3.1 Price War Competition .......................................................................... 36
3.2 Market Share of Pre-paid GSM Providers ............................................. 47
3.3 Strength and Direction of the Coefficient of Correlation ........................ 54
4.1 Regression Calculation from Minitab .................................................... 68
4.2 Hypothesis Test of Regression Analysis ............................................... 70
4.3 Relationship between Customer Satisfaction and Willingness to Pay .. 71
4.4 Plot of the Residual versus Values of Customer Satisfaction ............... 72
4.5 Plot of the Residual versus Predicted Values of Willingness to Pay ..... 73
4.6 Plot of the Standardized Residual versus Values of
Customer Satisfaction ........................................................................... 74
4.7 Scatterplot of Willingness to Pay and Customer Satisfaction ............... 75
4.8 Correlation Calculation from Minitab ..................................................... 76
4.9 Hypothesis Test of Coefficient of Correlation ........................................ 77
1
CHAPTER I
INTRODUCTION
1.1 Background
Business is now in the era of globalization, which means that every industry
faces a tougher competition. Every company does their best strategies and
tactics to win the heart of customers so they will put their buying decision on the
products that the company provides. Hence, a company must have competitive
advantages in every aspect of their operational function to survive and improve
their business, otherwise they will be in a direction to collapse.
In every industry, customers play an important role for the life of the
company, and by that reason, company must satisfy customers’ needs and wants
through their products or services. One of the functions in a company that deals
in identifying and meeting human and social needs is marketing (Kotler, 2003, 3).
Marketing is a market-oriented management concept, with its main goal to
achieve company’s objectives through customer satisfaction.
Customer satisfaction defined as a post purchase evaluation a customer
has through a comparison of perception (actual) and expectation of a product or
service provided by a company. A company that put a high focus in customer
satisfaction will develop their products or services so it can meet customers’
expectations, or further, beyond it. They do believe that an expected product or
service satisfies customers and thus, “… satisfied customers are more likely to
become or remain repeat purchasers…” (Mittal and Kamakura, 2001, in Hawkins,
Best, and Coney, 2004, 645). Eventually, satisfied customers will increase
company’s profit.
2
Anderson, Fornell, and Lehmann (1994, p.63, as mentioned by Homburg,
Koschate, and Hoyer 2005) analyze the link between customer satisfaction and
financial performance on data obtained from the Swedish Customer Satisfaction
Index, and they find that “firms that actually achieve high customer satisfaction
also enjoy superior economic returns”. With this finding, it is not an astonishing
situation that every industry in countries faces a highly business competition
among the companies, with the main purpose to gain or retain customers and
satisfy their needs and wants in order to achieve company profitability.
Telecommunication is one of the industries in Indonesia that has a
tremendous growth of business, especially in cellular telecommunication industry.
Nowadays, the needs of communication increase since their first existence in this
country. In 2008, the number of customers using a cellular telecommunication
service reaches 106,701,141 (www.postel.go.id). With this number, every cellular
telecommunication provider strive their best to increase market share of their
service and obtain a high profit for the company. A research finds that
telecommunication industry development in global view shows that Indonesia is
one of the most attractive telecommunication investment markets. (Majalah
Marketing, 12th Edition, 2007).
Initially, the competition of cellular telecommunication takes place on the
Global Satellite for Mobile Communication (GSM) based technology providers.
Afterwards, Fix Wireless Access (FWA) providers, which employ a Code Division
Multiple Access (CDMA) technology, appear in industry. Although it is not a head-
to-head comparison, this brings an impact to the cellular telecommunication
service competition, since CDMA based providers offer lower tariffs. (Majalah
SWA, April 3, 2008). Ever since, cellular telecommunication business competition
emphasize on price war. Some cellular telecommunication companies offer a
3
lower talk tariffs than their competitors do. As a result, customer will have the
benefit for the lower price of the service. In addition, for the company itself, they
might increase their market share by gaining new customers or by taking over
customers from the competitors.
Practitioner in cellular telecommunication industry noticed that the price war
among the providers is undeniable, especially for the newcomers, because the
newcomers tend to offer low tariffs in order to attract customers (Majalah SWA,
November 24, 2008). Substantively, a low tariff policy is not the only competitive
advantage for this industry, however, the climate is heading to a price competition
and thus, every provider follows the same path. Even though, a lower tariff is not
a guarantee to win the market. In fact, the market leader in this industry still
achieves the same growth, compared to other companies that offer a lower price
for the talk tariff. Furthermore, providers need to consider another competitive
advantage to satisfy the need of customers, such as quality of service, coverage,
the ease of conditions, and transparency. (Majalah SWA, November 24, 2008)
Observing the competition in cellular telecommunication industry, author
interested to study the market of this industry. Since price become the only focus
in competition, it is interesting to explore whether customers will pay more for the
service if providers offer other attributes that potentially increase customer’s level
of satisfaction. Recent research finds that there is a positive correlation between
changes in satisfaction and changes in willingness to pay in a hospitality industry
(Huber, Herrmann, and Wricke, 2001; and Homburg, Koschate, and Hoyer,
2005).
Homburg, Koschate, and Hoyer (2005) suggest that further research of this
study could examine whether there are potential moderators that strengthen or
weaken the relationship between customer satisfaction and willingness to pay.
4
The notion is that the relationship is weaker in highly competitive markets than in
low competitive markets. However, because of the author’s limitations, this
research is not following previous research suggestion mentioned above. The
main idea that underlies this research is to find out whether there is still a
relationship between customer satisfaction and willingness to pay in a highly
competitive market, in this case, the pre-paid GSM services market.
1. 2 Problem Identification
Based on the research background mentioned, the author would like to
identify the problems of this research, which is as follows:
1. Whether there is a positive relationship between customer
satisfaction and willingness to pay in cellular telecommunication
industry
2. Whether the assumed regression model of the relationship is
appropriate.
3. Whether the strength of relationship is strong or weak.
1. 3 Research Objectives
The objectives of this research are as follows:
1. To ascertain the relationship between customer satisfaction and
willingness to pay in cellular telecommunication industry.
2. To examine whether the assumed regression model is appropriate for
the relationship.
3. To find out whether the strength of relationship is strong or weak.
5
1. 4 The Use of Research
The author intends to dedicate the findings of this research especially to
civitas academica and companies in cellular telecommunication industry, which is
this research object. Therefore, the use of this research is as follows:
1. Theoretical Use
To provide and to improve Marketing Science especially in the
relationship between customer satisfaction and willingness to pay.
Additionally, this research gives information to other researcher who
intend to perform further research in consumer behavior study.
2. Operational use
a. To the industry
To provide insights to the cellular telecommunication industry
regarding the topic of this research, which is the relationship between
customer satisfaction and willingness to pay.
b. To the readers
To provide information to the readers regarding the findings of
the research in the research conclusion, as well as giving suggestions
needed in further research related to the consumer behavior study.
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CHAPTER II
LITERATURE REVIEW
2.1 Theoretical Framework
2.1.1 Marketing
Marketing has become a very crucial function in a company. Marketing is
the only function in a company that directly deals with customer’s needs and
wants. Based on the role of marketing, Huber, Herman, and Wricke (2001)
having a notion that “Marketing places the problems and wishes of actual and
potential customers at the center of all operational consideration.”
Marketing definition changes from time to time in relation with business
competitive situation and increase in customer’s expectations. From 1985 until
2005, the American Marketing Association (AMA) in Ferrel, and Hartline (2008, 7)
define marketing as “… a societal process of planning and executing the
conception, pricing, promotion, and distribution of ideas, goods, and services to
create exchanges that satisfy individual and organizational objectives”
Analogously with the AMA definition, Cannon, Perreault, Jr, and McCarthy
(2008, 6) define that,
Marketing is the performance of activities that seek to accomplish an organizational objective by anticipating customer or client needs and directing a flow of need-satisfying goods and services from producer to customer or client.
From the definitions mentioned above, it can be said that marketing is a market-
oriented concept, which has a main goal to accomplish organizational objectives
through customer satisfaction.
In 2005, the AMA changed the definition of Marketing to reflect better
concerning the realities competing in today’s marketplace,
7
Marketing is an organizational function and a set of processes for creating, communicating, and delivering value to customers and for managing customer relationship in ways that benefit the organization and it stakeholders. (Ferrel, and Hartline, 2008, p.7)
This new definition emphasizes two critical success factors of today’s marketing,
namely value and customer relationship. The difference is that the former
definition stresses on a transactional focus, whereas the new definition
accentuates long-term relationship that provide value for both customers and the
firm.
2.1.2 Marketing Management
A company needs to manage their marketing effort, so that the programs
they performed would effectively accomplish the desired objectives. The
mentioned below is the definition of marketing management from Kotler in Peter,
and Donelly, Jr (2004, 14),
Marketing management can be defined as the process of planning and executing the conception, pricing, promotion, and distribution of goods, services, and ideas to create exchanges with target groups that satisfy customer and organizational objectives.
It should be noted that this definition is entirely consistent with the
marketing concept, since it emphasizes the serving of target market needs as the
key to achieving organizational objectives. (Peter and Donelly, Jr. 2004. 14)
2.1.3 Product
Product is anything produced by a company in order to achieve their
business objectives through an exchange to a customer need or want. A very
simple definition is that a product is something that can be acquired via exchange
to satisfy a need or a want. (Ferrel, and Hartline, 2008, 11)
Kotler in Marketing Management, Eleventh Edition (2003, 407), defines that
a product ” ... is anything that can be offered to a market to satisfy a want or
8
need. Products that are marketed include physical goods, services, experiences,
events, persons, places, properties, organizations, information, and ideas”. In a
more simple definition, product is “Everything that the customer receives that is of
value in terms of perceived want, need, or problem.” (Addock, Halborg, and
Ross, 2001.183)
Ferrel and Hartline (2008, 11) classify a lot of ‘things’ as products;
1. Goods
Goods are tangible items ranging from canned food to fighter jets,
from sports memorabilia to used clothing. The marketing of tangible
goods is arguably one of the most widely recognizable business
activities in the world.
2. Services
Services are intangible products consisting of acts or deeds directed
towards people or their possessions. Banks, hospitals, lawyers,
package-delivery companies, airlines, hotels, repair technicians,
nannies, housekeepers, consultants, and taxi drivers all offer
services. Services, rather than tangible goods, dominate modern
economies like the U.S. economy.
3. Ideas
Ideas include platforms or issues aimed at promoting a benefit for the
customer. Examples include cause-related or charitable organization
such as the Red Cross, the American Cancer Society, Mothers
Against Drunk Drivers, or the American Legacy Foundation’s
campaign against smoking.
9
4. Information
Marketers of information include websites, magazine and book
publisher, schools and universities, research firms, churches, and
charitable organizations. In the digital age, the production and
distribution of information has become a vital part of our economy.
5. Digital products
Digital products, such as software, music, and movies, are among the
most profitable in our economy. Advancements in technology have
also wreaked havoc in these industries because pirates can easily
copy and redistribute digital products in violation of copyright law.
Digital products are interesting because content producers grant
customers a license to use them, rather than outright ownership.
6. People
The individual promotion of people, such as athletes or celebrities, is
a huge business around the world. The exchange and trading of
professional athletes takes place in a complex system of drafts,
contracts, and free agency. Other professions, such as politicians,
actors, professional speaker, and news reporters, also engage in
people marketing.
7. Places
When we think of the marketing of a place, we usually think of
vacation destinations like Rome or Orlando. However, the marketing
of places is quite divers. Cities, states, and nations all market
themselves to tourists, businesses and potential residents.
8. Experiences and Events
Marketer can bring together a combination of goods, services, ideas,
information, or people to create one of a kind experiences or single
10
event. Good examples include theme park such as Disney World and
Universal Studios, athletics events like the Olympics or the Super
Bowl, or stage and musical performances like The Phantom of the
Opera or a concert by Madonna.
9. Real or financial property
The exchange of stock, bonds, and real estate, once marketed
completely offline via real estate agents and investment companies,
now occurs increasingly online. For example, Realtor.com is the
nation’s largest real estate listing service, with over 2.5 million
searchable listings. Likewise, Schwab.com is the world’s largest and
top-rated online brokerage.
10. Organizations
Virtually all organizations strive to create favorable images with the
public not only to create sales or inquiries but also to generate
customer goodwill. In this sense, General Electric is no different than
the United Way: Both seek to enhance their images in order to attract
more people (customers, volunteers, and clients) and money (sales,
profit, and donations).
2.1.4 Service
Service businesses dominate in the modern economies, even in developing
economies, the contribution made by services to both employment and the gross
domestic product is growing rapidly. In recent years, the phenomenal growth of
services has become one of the megatrends in global economy.
Below is the definition of service from Lovelock (1999, 5),
A service is an act or performance offered by one party to another. Although the process may be tied to a physical product, the performance is essentially intangible and does not normally result in ownership of any of the factors of production.
11
Analogously with the definition above, Kotler (2003, 444) defined that,
A service is any act or performance that one party can offer to another that is essentially intangible and does not result in the ownership of anything. Its production may or may not be tied to a physical product.
Both of definitions say that there is no ownership transfer in service, although the
process tied to a physical product, it is still essentially intangible.
The American Marketing Association (Peter, and Donelly, Jr. 2004, 175)
has defined services as follows:
1. Service products, such as a bank loan or home security, that are
intangible, or at least substantially so. If totally intangible, they are
exchanged directly from producer to user, cannot be transported or
stored, and are almost instantly perishable. Service products are
often difficult to identify, since they come into existence at the same
time they are bought and consume. They are composed of intangible
elements that are inseparable; they usually involve customer
participation in some important way, cannot be sold in the sense of
ownership transfer, and have no title. Today, however, most products
are partly tangible and partly intangible, and the dominant form is
used to classify them as either goods or services (all are products).
These common, hybrid forms, whatever they are called, may or may
not have the attributes just given for totally intangible services.
2. Services, as a term, is also used to describe activities performed by
seller and others that accompany the sale of a product and that aid in
its exchange or its utilization (e.g., shoe fitting, financing, an 800
number). Such services are either presale or postsale and
supplement the product but do not comprise it.
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2.1.5 Consumer Behavior
A company crucially needs the understanding of consumer behavior. Many
companies fail to perform a long-term business because of their lack of
understanding about consumer behavior.
The AMA defines consumer behavior as “The dynamic interaction of affect
and cognition, behavior, and the environment by which human beings conduct
the exchange aspects of their lives.” (Peter, and Olson, 1999, 6)
In other words, consumer behavior involves the thoughts and feelings
people experience and the actions they perform in consumption processes. It
also includes all the things in environment that influence these thoughts, feelings,
and actions. These include comments from other consumers, advertisements,
price information, packaging, product appearance, and many others. It is
important to recognize from this definition that consumer behavior is dynamic,
involves interactions, and involves exchanges.
The definition given by Schiffman, and Kanuk (2004, 8), involves things that
consumer does in their consumption process, “The term consumer behavior is
defined as the behavior that consumers display in searching for, purchasing,
using, evaluating and disposing of products and service that they expect will
satisfy their needs.”
Generally, consumer uses stages of act (see figure 2.1) in their decision
making to consume a product or service, which are need recognition, alternative
search, alternative evaluation, purchase decision, and postpurchase evaluation.
Although not every consumer uses all stages in this model, it provides steps for a
consumer who has highly involvement with their buying decision.
13
Source: Peter and Donelly, Jr. 2004. 48
Figure 2.1
The Consumer Decision-Making Process
1. Need Recognition
The starting point in the buying process is the recognition of an unsatisfied
need by the consumer. Some number of either internal or external stimuli may
activate needs or wants and recognition of them. Internal stimuli are such things
as feeling hungry and wanting some food, feeling a headache coming on and
wanting some Excedrin, or feeling bored and looking for a movie to go to.
External stimuli are such things as seeing a McDonald’s sign and then feeling
hungry or seeing a sale sign for winter parkas and remembering that last year’s
coat is worn out.
2. Alternative Search
Once a need is recognized, the individual then searches for alternatives to
satisfy the need. There are five basic sources from which the individual can
collect information for a particular purchase decision.
a. Internal sources. In most cases, the individual has had some previous
experience in dealing with a particular need. Thus, the individual will
usually “search” through whatever stored information and experience
is in his or her mind for dealing with the need.
b. Group sources. A common source of information for purchase
decisions comes from communication with other people, such as
family, friends, neighbors, and acquaintances.
14
c. Marketing source. Marketing sources of information include such
factors as advertising, salespeople, dealers, packaging, and displays.
d. Public sources. Public sources of information include publicity, such
as newspaper article about the product, and independent rating of the
product, such as Consumer Reports.
e. Experiential sources. Experiential sources refer to handling,
examining, and perhaps trying the products while shopping. This
usually requires an actual shopping trip by the individual and may be
the final source consulted before purchase.
3. Alternative Evaluation
During the process of collecting information or, in some cases, after
information is acquired, the consumer evaluates alternatives on the basis of what
he or she has learned. One approach about a number to describing the
evaluation is as follows:
a. The consumer has information about a number of brands in a
products class.
b. The consumer perceives that at least some of the brands in a product
class are viable alternatives for satisfying a recognized need.
c. Each of these brands has a set of attributes (color, quality, size, and
so forth).
d. Each of these brands is relevant to the consumer, and the consumer
perceives that different brands vary in how much of each attributes
they possess.
e. The brand that is perceived as offering the greatest number of
desired attributes in the desired amounts and desired order will be the
brand the consumer will like best.
15
f. The brand the consumer likes best is the brand the consumer will
intend to purchase.
4. Purchase Decision
If no other factors intervene after the consumer has decided on the brand
that is intended for purchase, the actual purchase is a common result of search
and evaluation. Actually, a purchase involves many decisions, which include
product type, brand, model, dealer selection, and method of payment, among
other factors. In addition, rather than purchasing, the consumer may make a
decision to modify, postpone, or avoid purchase based on an inhibitor to
purchase or a perceived risk.
5. Postpurchase Evaluation
In general, if the individual finds that a certain response achieves a desired
goal or satisfies a need, the success of this cue-response pattern will be
remembered. The probability of responding in a like manner to the same or
similar situation in the future increases. In other words, the response has a higher
probability of being repeated when the need and cue appear together again, and
thus it can be said that learning has taken place. Frequent reinforcement
increases the habit potential of the particular response. Likewise, if a response
does not satisfy the need adequately, the probability that the same response will
be repeated reduces.
2.1.6 Customer Expectations
Zeithaml and Bitner (2004, 60) define customer expectations as follows.
“Customer expectations is beliefs about service delivery that function as
standards or reference points against which performance is judged.”
16
Because customers compare their perception of performance with these
reference points when evaluating service quality, thorough knowledge about
customer expectations is critical to services marketer. Knowing what the
customer expects is the first and possibly most critical step in delivering quality
service. Being wrong about what customers want can mean losing customers’
business when another company hits the target exactly. Being wrong is also
mean expending money, time, and other resources on things that do not count to
the customer. Being wrong can even mean not surviving in a fiercely competitive
market.
Source: Zeithaml and Bitner, 2004. 61
Figure 2.2
Possible Levels of Customer Expectations
Because of expectations play such a critical role in customer evaluation of
services, marketers need and want to understand the factors that shape them.
High
Low
Ideal expectations of desires
Normative “should” expectations
Experience-based norms
Acceptable expectations
Minimum tolerable expectations
“Everyone says this restaurant is as good as one in France and I
want to go somewhere very special for my anniversary”
“As expensive as this restaurant is, it ought to have excellent food
and service.”
“Most times this restaurant is very good, but when it gets busy the
service is slow.”
“I expect this restaurant to serve me in an adequate manner.”
“I expect terrible service from this restaurant but come because the
price is low.”
17
Marketers would also like to have control over these factors as well, but many of
the forces that influence customer expectations are uncontrollable. Table 2.1
shows ways services marketers can influence factors that shape customer
expectations.
Table 2.1
Ways Services Marketers Can Influence Factors
Controllable Factors Possible Influence Strategies
Explicit service promises
Make realistic and accurate promises that reflect the service actually delivered rather than an idealized version of the service
Ask contact people for feedback on the accuracy of promises beyond the level at which they can be met.
Formalize service promises through a service guarantee that focuses company employees on the promise and that provides feedback on the number of times promises are not fulfilled.
Implicit service promises
Ensure that service tangibles accurately reflect the type and level of service provided.
Ensure that price premiums can be justified by higher level of performance by the company on important customer attributes.
Less Controllable Factors Possible Influence Strategies
Enduring service intensifiers
Use market research to determine sources of derived service expectations and their requirements. Focus advertising and marketing strategy on ways the service allows the focal customer to satisfy the requirements of the influencing customer.
Use market research to profile personal service philosophies of customers and use this information in designing and delivering services.
Personal needs Educate customers on ways the service addresses their needs.
Transitory service intensifiers Increase service delivery during peak periods or in emergencies.
18
Table 2.1 (Continued)
Perceived service alternative Be fully aware of competitive offerings and, where possible and appropriate, match them.
Self-perceived service role Educate customers to understand their roles and perform them better.
Word-of-mouth
communications
Simulate word of mouth in advertising by using testimonials and opinion leaders.
Identify influencers and opinion leaders for the service and concentrate marketing efforts on them.
Use incentives with existing customers to encourage them to say positive things about the service.
Past experience Use marketing research to profile customers’ previous experience with similar service.
Situational factors Use service guarantees to assure customers about service recovery regardless of the situational factors that occur.
Predicted service Tell customers when service provision is higher than what can normally be expected so that predictions of future service encounters will not be inflated.
Source: Zeithaml and Bitner, 2004. 75
2.1.7 Customer Value and Satisfaction
2.1.7.1 Customer Value
Generally, customer will consider value of the products or services before
they decided to consume the offering. It is a company’s effort to survive in the
competition by providing target customers more value than its provided by
competitors.
19
Cannon, Perreault, Jr., and McCarthy (2008, 19) define that customer value
is “… the difference between the benefits a customer sees from a market offering
and the costs of obtaining those benefits.” This definition is similar with Schiffman
and Kanuk (2004, 14), “Customer value is defined as the ratio between the
customer’s perceived benefits (economic, functional and psychological) and the
resources (monetary, time, efforts, psychological) used to obtain those benefits.”
Jobber (2004,12) says that customer value is dependent on how the
customer perceives the benefits of an offering and the sacrifice that is associated
with its purchase. Therefore:
Because of customer is a value-maximizer, they are likely to be more
satisfied when the customer value is higher. Some people think that low price is
the only aspect of a high customer value, however, a low price product or service
may result in low customer value if it does not meet customer’s expectations.
Conversely, a high price may be more than acceptable when it obtain the desired
benefits.
2.1.7.2 Customer Satisfaction
Customer satisfaction has become a central focus of every company in
industries. It is simply because the greater the satisfaction of customer leads to
the greater of profits.
“Satisfaction is the customer’s evaluation of a product or service in terms of
whether that product or service has met their needs and expectations.” (Zeithaml
and Bitner, 2004, 86). When a product or service fails to meet customer’s needs
and expectations, it is assumed to result in dissatisfaction.
20
The level of customer satisfaction varies among customers, this difference
occurs because every customer has their own perception about a product or
service. “Customer satisfaction is the individual’s perception of the performance
of the product or service in relation to his or her expectations.” (Schiffman and
Kanuk, 2004, 14)
It is generally that customer satisfaction able to generate outcomes that
benefit a company’s business. In figure 2.3, Hawkins, Best, and Coney (2004,
650) draw a concept of customer satisfaction outcomes.
Source: Hawkins, Best, and Coney. 2004. 650
Figure 2.3
Customer Satisfaction Outcomes
2.1.7.3 Determinants of Satisfaction and Dissatisfaction
Because of performance expectations and actual performance are major
factors in the evaluation process, we need to understand the dimensions of
product and service performance. A major study of the reasons customers switch
service providers found competitor actions to be a relatively minor cause. Most
customers did not switch from a satisfactory provider to a better provider. Instead,
they switched because of perceived problems with their current service provider.
21
Below are several reasons customers change service provider sorted from the
major cause (Hawkins, Best, and Coney. 2004. 639):
1. Core service failure. Mistakes (booking an aisle rather than requested
window seat), billing errors, and service catastrophes that harm the
customer (the dry cleaners ruined a customer’s wedding dress).
2. Service encounter failures. Service employees were uncaring,
impolite, unresponsive, or unknowledgeable.
3. Pricing. High prices, price increases, unfair pricing practices, and
deceptive pricing.
4. Inconvenience. Inconvenient location, hours of operation, waiting time
for service or appointments.
5. Responses to service failures. Reluctant responses, failure to
respond, and negative responses (customer’s fault).
6. Attraction by competitors. More personable, more reliable, higher
quality, and better value.
7. Ethical problems. Dishonest behavior, intimidating behavior, unsafe
or unhealthy practices, or conflicts of interest.
8. Involuntary switching. Service provider or customer moves, or a third-
party payer such as an insurance company requires a change.
2.1.8 Price
“Price is the amount of money one must pay to obtain the right to use the
product.” (Hawkins, Best, and Coney. 2004. 21). One can buy ownership of a
product or, for many products, limited usage rights (i.e., one can rent or lease the
product such as video).
Economists often assume that lower prices for the same product will result
in more sales than higher prices. However, price sometimes serves as a signal of
22
quality. A product priced “too low” might be perceived as having low quality.
Owning expensive items also provides information about the owner. If nothing
else, it indicates that the owner can afford the expensive items. This is a
desirable feature to some consumers. Therefore, setting a price requires a
thorough understanding of the symbolic role that price plays for the product and
target market in question.
It is important to note that the price of a product is not the same as the cost
of the product to the customer. Consumer cost is everything the consumer must
surrender in order to receive the benefits of owning/ using the product. One of the
ways firms seek to provide customer value is to reduce the non-price costs of
owning or operating a product. If successful, the total cost to the customer
decreases while the revenue to the marketer stays the same or even increases.
2.1.9 Pricing of Services
Pricing in services is more difficult than pricing of goods. Service
companies must understand how pricing works, but first they must understand
how customers perceive prices and price changes. The following sections:
Customer knowledge of service prices, the role of non-monetary costs, and price
as an indicator of service quality, describe the ways customers perceive services,
and each is central to effective pricing. (Zeithaml and Bitner. 2004. 478)
1. Customer Knowledge of Service Prices
When customers are able to estimate prices of services based on their
memory, it means that they have internal reference prices for the services. A
reference price is a price point in memory for a good or a service, and can consist
of the price last paid, the price most frequently paid, or the average of all prices
customers have paid for similar offerings. However, customers might not have an
23
accurate reference prices for the services. Several reasons for the customers’
inaccuracy of reference prices are as follows.
a. Service heterogeneity limits knowledge. Because services are
intangible and are not created on a factory assembly line, service
firms have great flexibility in the configurations of services they offer.
Firms can conceivably offer an infinite variety of combinations and
permutations, leading to complex and complicated pricing structures.
As an example, consider how difficult it is to get comparable price
quotes when buying life insurance. With the multitude of types (such
as whole life versus terms), features (different deductibles), variations
associated with customers (age, health risk, smoking or nonsmoking),
few insurance companies offer exactly the same features and the
same prices. Only an expert customer, one who knows enough about
insurance to completely specify the options across providers, is likely
to find prices that are directly comparable.
b. Providers are unwilling to estimate prices. Another reason customers
lack accurate reference prices for services is that many providers are
unable or unwilling to estimate price in advance. Consider most
medical or legal services. It is rarely legal or medical service
providers are willing–or even able–to estimate a price in advance.
c. Individual customer needs vary. Another factor that results in the
inaccuracy of reference prices is that individual customer needs vary.
Some hairstylists’ service prices vary across customers on the basis
of length of hair, type of haircut, and whether conditioning treatment
and style are included. Therefore, if you were to ask a friend what cut
24
costs from a particular stylist, chances are that your cut from the
same stylist may be a different price
d. Price information is overwhelming in services. Still another reason
customers’ lack accurate reference price for services is that
customers feel overwhelmed with information they need to gather.
With most goods, retail stores display the products by category to
allow customers to compare and contrast the price of different brands
and sizes. It is rarely there is a similar display of services in a single
outlet. If customers want to compare prices (such as for dry cleaning),
they must drive to or call individual outlets.
e. Prices are not visible. One requirement for the existence of customer
reference prices is price visibility –the price cannot hidden or implicit.
In many services, particularly financial services, most customers
know about only the rate of return and not the costs they pay in the
form of fund and insurance fees. IDS Financial Services recently
discovered how little customers know about prices of company’s
services. After being told by the independent agents who sell their
services to customers that IDS was priced too high, the company did
research to find out how much customers know about what they pay
for financial services and how much price factors into customer value
assessments.
For all of the reasons just listed, many customers do not see the price at all
until after they receive certain services. Of course, in a situation of urgency, such
as in accident or illness, customers must make decision to purchase without
respect to cost at all. And if cost is not known to the customer before purchase, it
cannot be used as a key criterion for purchase as it often is for goods. Price is
25
likely to be an important criterion in repurchase, however. Furthermore, in
repurchase monetary price may be an even more important criterion than in initial
purchase.
2. The Role of Nonmonetary Costs
In recent years economist have recognized that monetary is not the only
sacrifice customers make to obtain products and services. Demand, therefore, is
not just a function of monetary price but is influenced by other costs as well.
Nonmonetary costs represent other sources of sacrifice perceived by consumers
when buying and using a service. Time costs, search costs, and psychological
costs often enter into the evaluation of whether to buy or rebuy a service, and
may at times be more important concerns than monetary price. Eventually,
customers will trade money for these other costs.
a. Time cost. Most services require direct participation of the consumer
and thus consume real time: Time waiting as well as time when the
customer interacts with the service provider. Waiting time for a
service is virtually always longer and less predictable than waiting
time to buy goods. Second, customers often wait for an available
appointment from a service provider. Virtually all of us have expended
waiting time to receive services.
b. Search cost. Search costs–the effort invested to identify and select
among services a customer desire–are also higher for services than
for physical goods. Prices for services are rarely displayed on the
shelves of service establishments for customers to examine as they
shop, so these prices are often known only when a customer has
decided to experience the service.
26
c. Convenience costs. There are also convenience (or perhaps more
accurately inconvenience) costs of service. If customers have to
travel to a service, they incur a cost, and the cost becomes greater
when travel is difficult, as it is for elderly persons. Further, if service
hours do not coincide with the customers’ available time, they must
arrange their schedules to correspond to the company’s schedule.
And if consumers have to expend effort and time to prepare to
receive a service (such as removing all food from kitchen cabinet in
preparation for an exterminator’s spraying), they make additional
sacrifice.
d. Psychological costs. Often the most painful nonmonetary costs are
the psychological costs incurred in receiving some services. Fear of
not understanding (insurance), fear of rejection (bank loans), fear of
uncertainty (including fear of high cost), all of these constitute
psychological costs that customers experience as sacrifice when
purchasing and using services. All change, even positive change,
brings about psychological costs that consumers factor into the
purchase of services.
3. Price as an Indicator of Service Quality
One of the intriguing aspects of pricing is that buyers are likely to use price
as an indicator of both service costs and service quality – price is at once an
attraction variable and repellent. Customers’ use price as an indicator of quality
depends on several factors, one of them is the other information available to
them. When service cues to quality are readily accessible, when brand names
provide evidence of company’s reputation, or when level of advertising
communicates the company’s belief in the brand, customers may prefer to use
27
those cues instead of price. In other situations, however, such as when quality is
hard to detect or when quality or price varies at a great deal within a class of
services, consumer may believe that price is the best indicator of quality. Many of
these conditions depict situations that face consumers when purchasing services.
Another factor that increases the dependence on price as a quality indicator is
the risk associated with the service purchase. In high risk situations, many of
which involve credence services such as medical treatment or management
consulting, the customers will look to price as surrogate for quality.
2.1.10 Willingness to Pay
Company and customers has a mutual relationship through an exchange,
which means that a company provides the products or services and customer
offers something in return to obtain the desired products or services, in this case,
their willingness to pay. The measurement of willingness to pay is based on the
principle that the maximum amount of money a customer is willing to pay for a
commodity is an indicator of the value to him/her of that commodity. Therefore,
willingness to pay is the maximum amount of money that may be contributed by
an individual to equalize the utility change. (www.en.wikipedia.org)
In prior study, researchers defined willingness to pay as the maximum
amount of money a customer is willing to spend for a product or service
(Cameron and James 1987; Khrisna 1991 in Homburg, Koschate and Hoyer
2005). Thus, willingness to pay is a measure of the value that a person assigns to
a consumption or usage experience in monetary units (Homburg, Koschate and
Hoyer 2005).
Customer value is a measure of how much a customer is willing to pay for a
product or service (Winer, 2000. 297). Economists call this concept the
reservation price, which is the most someone is willing to pay for a product (or the
28
price at which the product is eliminated from the customer’s budget). Every
customer, whether consumer or business, has a psychological concept of such a
price. People receive price information and then assess whether it is good or bad.
They compare the price being charged with the perceived value or benefits they
would derive from purchasing it.
2.2 Conceptual Framework
Figure 2.4
Conceptual Framework
The explanation of the conceptual framework in figure 2.4 is that a
company must provide products or services that have competitive advantages to
survive in industry. Therefore, in order to achieve company’s objectives, a
company needs to offer a combination of attributes that potentially meet
customer’s expectations and eventually generate customer satisfaction.
29
One of the benefits in having a high level of customer satisfaction is that
satisfied customers are likely to purchase a product or service in a high price. In
some cases, customer may value higher for a product or service if they perceive
a better performed offerings.
With the statement mentioned above, it is assumed that an increase in
customer’s level of satisfaction may also increase their willingness to pay. In
performing this research, the author uses a regression model to find out and
analyze the relationship between customer satisfaction and their willingness to
pay, which is the main idea of this study.
2.3 Premise and Hypothesis
2.3.1 Premises
Premise 1
…that a satisfied client is willing to pay more for the product (Huber, Frank.
Andreas Herrmann and Martin Wricke. 2001)
Premise 2
This indicates a statistically significant and positive relationship between
Customer Satisfaction and Willingness to Pay …that satisfied customers are
willing to pay more for the product or service. (Homburg, Christian. Nicole
Koschate and Wayne D. Hoyer. 2005)
Premise 3
”If that customer perceives the product as a necessity, then that customer
becomes much less sensitive to price increases for that product” (Ferrel and
Hartline, 2008, 237).
30
2.3.2 Hypotheses
Hypothesis 1
The relationship of Customer Satisfaction and Willingness to Pay is statistically
significant.
Hypothesis 2
The relationship of Customer Satisfaction and Willingness to Pay can be
explained in linear regression model.
Hypothesis 2alt
The relationship of Customer Satisfaction and Willingness to Pay appears to
have a non-linear regression model.
Hypothesis 3
The strength of the relationship between Customer Satisfaction and Willingness
to Pay is positive and strong
31
CHAPTER III
RESEARCH METHODOLOGY
3.1 The Overview of Mobile Telecommunication Industry in Indonesia
Mobile telecommunication has become familiar among Indonesian society
because this industry has started the activities since 24 years ago. In several
European developed countries, cellular technology has been applied for the
needs of communication since 70’s decade, even so, Indonesia started to utilize
the technology in years afterwards.
The first cellular technology that applied in Indonesia was Mobile
Telephone (NMT) technology in 1984, however, the number of people using
mobile phone was still slightly. In 1985-1992, the size of a mobile phone was
large with approximate weights about 430 gram. It was priced above Rp.10
millions, which made it become a very expensive means of communication in the
era. At the time, there were only two known cellular technology, NMT-470, which
operated by PT Rajasa Hazanah Perkasa, and Advance Mobile Phone Service
(AMPS) employed by four providers, which were PT Elektrindo Nusantara, PT
Centralindo, PT Panca Sakti, and Telekomindo.
In the late 1993, PT Telkom performed their first project in applying a digital
cellular technology, which is called Global System for Mobile Communication
(GSM). This project was started in Batam and Bintan Island. In 1994, PT Satelit
Palapa Indonesia (Satelindo) began their operations as the first GSM based
provider in Indonesia and commencing its business in Jakarta region. Since GSM
using a Subscriber Identity Module (SIM) card, it allows subscribers to change
32
their mobile phone with the same number. Moreover, this technology provides
better voice quality with a wider coverage.
The Telkom’s project in Batam and Bintan Island was succeeded and they
continued to the other province in Sumatera, which eventually took them to the
establishment of Telkomsel on May 26, 1995 as a national GSM based provider
together with Satelindo. Telkomsel with their main product, kartuHalo, succeeded
in Medan, Surabaya, Bandung, and Denpasar. Afterwards, they entered the
Jakarta’s market. In order to support the development of the industry,
government eliminated admission charge on mobile phones, which made its price
become lower with minimum Rp.1 million per unit. Telkomsel has also made a
breakthrough by providing nationwide network coverage include Ambon (Maluku)
as the 27th province of Indonesia on December 29, 1996. In the late 1996, PT
Excelcomindo Pratama (Excelcom) initiated their first operations in Jakarta and
became the third GSM based telecommunication provider in Indonesia.
Government issued a new regional license to the 10 new Personal Handy
Phone (PHS) and GSM 1800 based technology providers in 1997. Unfortunately,
the project was abandoned since the economic environment of Indonesia
affected by monetary crisis. Nevertheless, at the same time, Telkomsel launched
the first pre-paid GSM in Indonesia, Simpati, as an alternative product of
kartuHalo. As a reaction to the competition, Excelcom launched a pre-paid GSM
service, Pro-XL, which offers subscribers with a superior roaming service. Then,
Satelindo followed Excelcom and Telkomsel by launching Mentari. With the talk
rate advantage where the rate counted for each second, Satelindo gained more
than 100,000 subscribers in a short time. Until the end of 1999, there were at
least 2.5 millions of subscribers nationwide, it was mostly the subscribers of pre-
paid GSM service from Simpati, Mentari, and Pro-XL.
33
The market of pre-paid GSM grew higher than the market of post-paid GSM
service. The reason is that a pre-paid GSM allows subscribers to improve the
control of their expenditure, since subscribers pay in advance -in a certain
amount- for the service and recharge the credits anytime when needed.
Furthermore, this pre-paid GSM service could eliminate provider’s risk of
subscriber’s arrears. On the contrary, with a post-paid GSM settlement,
subscribers had difficulties in controlling the use of the service. Since they are
given an unlimited communication access, their bill amount would unconsciously
mountainous. On the other hand, providers would suffer a big loss in earnings
because they had difficulties to trace the address of subscribers who are
intentionally being in arrears. Generally, a post-paid GSM service is appropriate
for the financially settled markets.
Telecommunication industry, especially cellular telecommunication, has
become one of the industries with a tremendous growth for the last decade in
Indonesia. The number of its market rises significantly every year. Now, more
than a hundred millions of subscribers enjoy the mobile communication service.
As well, the number of providers in this industry increased analogously with the
market growth. At least there are eight mobile telecommunication providers
operate their business in Indonesia, which are PT Telkomsel, PT Indosat, PT
Excelcomindo Pratama, PT Natrindo Telepon Seluler (NTS), PT Hutchison
Charoen Pokphand Telecom (HCPT), PT Mobile-8 Telecom, PT Sampoerna TI,
and PT Smart Telecom.
Since there are many cellular telecommunication providers attempt to win
the market, the competition of this industry becomes tougher. Cellular
telecommunication industry watchers concerned about the competition climate of
this industry that has turn in to an imperfect competition, the price war.
34
Furthermore, some of practitioners said that there is no other way for the
newcomers and small business providers than offering lower tariffs in order to
attract customers as many as they can. Nevertheless, by giving low tariffs, the
communication traffic becomes higher, whereas the quality of network and
provider’s infrastructure has not been sufficient yet. Consequently, they could not
deliver a proper quality performance. In addition, the company needs a greater
amount of investment funds to build their infrastructures. However, if they attract
the market with a high operational cost, it would hamper the investment.
The competition in cellular telecommunication industry emphasized to a
price war since the emergence of Fixed Wireless Access (FWA) providers, which
employ a Code Division Multiple Access (CDMA) technology. Although using a
different technology, this brings an impact to the cellular telecommunication
industry thoroughly because FWA providers offer lower tariffs than GSM based
providers. Eventually, the price war is inevitable, and thus makes the GSM
providers acclimatize the competition by offering lower tariffs in order to retain
their market share. The first provider who offers a CDMA technology was
TelkomFlexi in December 2002 as a trademark from PT Telekomunikasi
Indonesia. PT Bakrie Telecom launched Esia afterwards in November 2003,
which then followed by Fren from PT Mobile-8 Telecom in December 2003. Then
in May 2004, PT Indosat launched StarOne.
35
Table 3.1
List of Cellular Providers with the Number of Subscribers
No. Providers Number of Subscribers
1. PT Telkomsel (June 30, 2008) 50.548.000 2. PT Indosat (March 31, 2008) 25.750.628 3. PT Excelcomindo Pratama (June 30, 2008) 22.423.262 4. PT NTS (July 12, 2008) 591.990 5. PT HCPT (June 30, 2008) 3.209.196 6. PT Mobile‐8 Telecom (July 16, 2008) 3.772.079 7. PT Sampoerna TI (February 29, 2008) 405.287 8. PT Smart Telecom (July 16, 2008) 504.330
Total 106.701.141 Source: www.postel.go.id
Table 3.2
List of FWA Providers with the Number of Subscribers
No. Providers Number of Subscribers
1. PT Indosat (March 31, 2008) 677.163 2. PT Telkom (July 16, 2008) 6.690.198 3. PT Bakrie Telecom (March 31, 2008) 4.456.663
Total 11.129.688 Source: www.postel.go.id
The pioneer in tariff innovation of pre-paid GSM was XL. In the middle of
2007, they only charged Rp.1/second for intra-network connection tariff, which
occurs after subscribers talk for two minutes with regular tariff. This promotion
was attacked by Indosat that promoted Rp.0/second tariff campaign. Even so, it
does not mean that the tariff was free of charge, but every time Mentari
subscribers spent Rp.5000 of credits for talk service, Indosat gave an extra talk
service credits with the same amount. XL was infuriated by Indosat’s offering.
Then, XL bombarded the mass media by providing the table of comparison
between their tariff and Indosat’s tariff. The point of this effort was they tried to
communicate that their tariff offerings were lower-priced than Indosat.
Price war competition between the two providers triggered Telkomsel as
the market leader in this industry, to join the competition. Telkomsel offered
36
Rp.0.5/second tariff after the first minute talk to the subscribers of Simpati PeDe
for an intra-network connection. The involvement of Telkomsel in the price war
made the competition became worse. XL offered a Rp.0.1/second tariff to strike
back Telkomsel’s promotional effort. Still, Indosat responded XL’s promotion by
offering lower tariff with Rp.0.01/second. Furthermore, XL replied with
Rp.0.000001/ second, which was then hit by Indosat with
Rp.0.0000000...1/second, or in other words, free of charge.
Newcomers and small business providers also joined in the price war
competition in this industry. HCPT offered a Rp.1/minute tariff for intra-network
connection. Analogous to HCPT, Mobile-8 offered Rp.38/minute for intra-network
connection and Rp.700/minute for interconnection calls. Finally, all pre-paid GSM
providers adjust their tariff offerings to survive in the business and enliven this
price war competition.
Source: www.photobucket.com
Figure 3.1
Price War Competition
37
3.1.1 Mobile Telecommunication Technologies in Indonesia
In the beginning of the mobile telecommunication development in
Indonesia, providers utilized NMT with 450MHz frequency. NMT had a wide
coverage, so it was able to reach the remote areas. However, the handsets of
NMT were large, thus it was not comfortable to use it in mobile use. Then, the
AMPS technology with a higher frequency, 800MHz, emerged. Even though the
AMPS coverage was not as wide as NMT, this technology became more popular
because the size of AMPS handsets was smaller than NMT.
After NMT and AMPS, GSM with the frequency of 900MHz introduced to
the industry. GSM uses a digital standard, and in short time, it eliminated the
AMPS technology, which was an analog system. Finally, many of AMPS
subscribers switched to GSM at the time and made the market of GSM grew
faster. The ubiquity of the GSM standard has been an advantage to both
consumers (who benefit from the ability to roam and switch carriers without
switching phones) and to network operators (who can choose equipment from
any of the many vendors implementing GSM). GSM also pioneered a low-cost (to
the network carrier) alternative to voice calls, the Short Message Service (SMS,
also called "text messaging"), which is now supported on other mobile standards
as well. Afterwards, CDMA technology is applied in this industry. Differ from the
previous technology switch, the existence of GSM is not disturbed by the
emergence of CDMA
CDMA employs spread-spectrum technology and a special coding scheme
(where each transmitter is assigned a code) to allow multiple users to be
multiplexed over the same physical channel. By contrast, time division multiple
access (TDMA) divides access by time, while frequency-division multiple access
(FDMA) divides it by frequency. CDMA is a form of "spread-spectrum" signaling,
38
since the modulated coded signal has a much higher data bandwidth than the
data being communicated.
An analogy to the problem of multiple access is a room (channel) in which
people wish to communicate with each other. To avoid confusion, people could
take turns to speaking (time division), speak at different pitches (frequency
division), or speak in different languages (code division). CDMA is analogous to
the last example where people speaking the same language can understand
each other, but not other people. Similarly, in radio CDMA, each group of users is
given a shared code. Many codes occupy the same channel, but only the users
associated with a particular code can understand each other.
The latest technologies in mobile telecommunication industry are 3G and
3.5G technology. 3G is the third generation of telecommunication hardware
standards and general technology for mobile networking. 3G networks enable
network providers to offer to users a wider range of more advanced services
while achieving greater network capacity through improved spectral efficiency.
Services include wide-area wireless voice telephone, video calls, and broadband
wireless data, all in a mobile environment.
3.5G or known as Super 3G is the development of 3G technology,
especially on the improvement of higher data transfer speed than 3G (>2Mbps),
which is able to provide multimedia communication such as internet access and
video sharing. This technology purges the previous 3G limitations. For example,
video call in 3.5G is perfected by eliminating the delay of voice and video capture
in mobile phone screen, which often occurs in 3G service. Eventually, video calls
in 3.5G technology become more interactive. The 3.5G services are provided in
Indonesia by PT Telkomsel, PT Indosat, and Excelcomindo.
39
3.1.2 GSM Providers in Indonesia
3.1.2.1 PT Telkomsel
Telkomsel is the leading operator of cellular telecommunications services in
Indonesia by market share. By the end of September 2008, Telkomsel had 60.5
million customers which based on industry statistics represented an estimated
market share of approximately 46%.
Telkomsel provides cellular services in Indonesia, through its own
nationwide dual-band GSM 900-1800 MHz, 3G network, and internationally,
through 323 international roaming partners in 170 countries (end of September
2008). In September 2006, Telkomsel became the first operator in Indonesia to
launch 3G services.
The company provides its subscribers with the choice between two prepaid
cards-simPATI and Kartu As, or the post-paid kartuHALO service, as well as a
variety of value-added services and programs. Telkomsel's operations in
Indonesia have grown substantially since the commercial launch of its post-paid
services on 26 May 1995. In November 1997, Telkomsel became the first cellular
telecommunications operator in Asia to introduce rechargeable GSM pre-paid
services.
Telkomsel's gross revenues have grown from Rp 3.59 trillion in 2000 to Rp
44.38 trillion in 2007. Over the same period, the total number of Telkomsel's
cellular subscribers increased from approximately 1.7 million as at 31 December
2000 to 47.9 million as at 31 December 2007.
Telkomsel has the largest network coverage of any of the cellular operators
in Indonesia, providing network coverage to approximately 95% of Indonesia's
population and is the only operator in Indonesia that covers all of the country's
40
provinces and regencies, and all counties ("kecamatan") in Sumatra, Java, and
Bali/Nusra. The company offers GSM Dual Band (900 & 1800), GPRS, Wi-Fi,
EDGE, and 3G Technology.
3.1.2.2 PT Indosat
PT Indosat Tbk was established in 1967 as a foreign investment company
to provide international telecommunications services in Indonesia, commencing
its operations in 1969 with the inauguration of the Jatiluhur earth station. In1980,
the Government of Indonesia acquired all of the shares of Indosat, which then
became a State-Owned Enterprise (SOE). In 1994, Indosat listed its shares on
the Jakarta Stock Exchange, the Surabaya Stock Exchange and the New York
Stock Exchange, achieving the distinction of being the first SOE to be listed
overseas.
From 1969 until 1990, Indosat provided switched and non-switched
international telecommunications services, including international direct dialing
telephony, international data network communications, international leased lines
and international television transmission services. Entering the 21st century and in
keeping with the global trends, the Government of Indonesia decided to
deregulate the national telecommunications sector, opening it up to free market
competition. From 2001, all cross-ownerships between Indosat and the domestic
telecommunications provider, Telkom, have been eliminated, whereas the
exclusivity rights of the two telecommunications service providers will be
terminated in several stages.
Indosat pursued a main course of development of its cellular business
starting in the mid 90's. In 2001, the company established PT Indosat Multi Media
Mobile (IM3), followed by acquiring full control of PT Satelit Palapa Indonesia,
thus making Indosat Group the second largest cellular operator in Indonesia. At
41
the end of 2002, the Government of Indonesia undertook a 41.94% divestment of
its shares in Indosat to Singapore Technologies Telemedia Pte. Ltd. through the
holding company of Indonesia Communications Limited. With this divestment,
Indosat is once again a foreign investment company, offering full fledged,
integrated network and services in information and communication solutions.
In November 2003, following the signing of the Merger Deed to merge
Satelindo, IM3 and Bimagraha into Indosat, Indosat emerges as a cellular
focused Full Network Service Provider (FNSP). By consolidating its cellular, fixed
telecommunications and MIDI services into a single organization, Indosat is well-
positioned to be the telecommunication service provider with the comprehensive
range of products offering in Indonesia. This was followed by a comprehensive
transformation program, launched in 2004, encompassing in human resources,
technology, platform and corporate culture and values. The transformation has
started to demonstrate encouraging results as the company posted record
revenues that surpassed Rp 10 trillion threshold and increased in margin its 10th
year as a publicly listed company.
Indosat is the second largest mobile operator with 16.704.639 subscriber
base by the end 2006. Indosat launched its 3.5G for the Jakarta and Surabaya
regions in November 29, 2006. Indosat 3.5G in the intermediate generation of the
3G technology, which enables subscribers to enjoy better quality voice, video or
high speed data/internet access of up to 3.6 Mbps or around 9 times faster than
standard 3G service. All Indosat node B has utilized the HSDPA (High Speed
Downlink Packet Access) technology. Indosat is the first 3G operator, which fully
adopt the HSDPA technology base in Indonesia.
In December 15, 2006, Indosat has accepted 2 channels no. 589 and 630
on its 800 MHz frequency band to operate Local Wireless Fixed
42
Telecommunication Network in Jabotabek area. Following the approval of these 2
channels, Indosat will continue to expense local wireless fixed telecommunication
services in Jabotabek area and continue to develop cellular services throughout
Indonesia.
Year 2007 was one of Indosat’s best years ever in terms of operational
results, network expansion and enhancement, product and service innovation,
and customer service delivery. Indosat cellular customer has achieved 24.5
million subscribers and served with 10.760 numbers of BTS in all over the nation.
Indosat also committed to applying principles of good corporate governance
towards the highest standard. Indosat will continue to develop and promote
growth for the company in 2008. With a strong brand in the market and improved
network coverage, Indosat is confident to maintain their growth momentum.
In June 2008, Qatar Telecom (Qtel) bought all Indosat shares through the
holding company of Indonesia Communications Limited from Singapore
Technologies Telemedia Pte. Ltd. and became the majority shareholders of
Indosat. Indosat has become the largest contribution in term of number of
subscribers to Qatar Telecom and one of the tools to achieve Qtel’s vision to
become the Top 20 operators in the world by 2020.
3.1.2.3 PT Excelcomindo Pratama
PT Excelcomindo Pratama Tbk. (“XL” or the “Company”) was founded on 6
October 1989, under the name PT Grahametropolitan Lestari. Its main business
was in trading and general services.
Six years later, the company took an important step by setting up a
cooperation with Rajawali Group – a shareholder of PT Grahametropolitan
Lestari - and three foreign investors (NYNEX, AIF and Mitsui). Its name was
43
changed to PT Excelcomindo Pratama, with the provision of basic telephony
services as its core business.
XL commenced commercial operations in 1996, primarily covering Jakarta,
Bandung and Surabaya areas. This had made XL the first private company in
Indonesia that provides cellular mobile telephony services.
September 2005 was a milestone for the company. Upsizing on all fronts,
XL became a public company listed on the Jakarta Stock Exchange [now known
as the Indonesia Stock Exchange (IDX)]. Currently, the majority of XL’s shares
are held by TM International Berhad through Indocel Holding Sdn. Bhd. (83.8%)
and Emirates Telecommunications Corporation (Etisalat) through Etisalat
International Indonesia Ltd. (16.0%).
XL has now taken the lead in the industry as the cellular
telecommunications provider with extensive coverage throughout Indonesia. It
provides services for retail customers and offers business solutions for corporate
customers, including voice, data and other value-added mobile
telecommunications services. XL operates its network with GSM 900/DCS 1800
and IMT-2000/3G technologies.
XL also holds a Closed Regular Network License, Internet Service Provider
(ISP) License, Voice over Internet Protocol (VoIP) License and Internet
Interconnection Services License (NAP)
44
Table 3.3
Milestone of PT Excelcomindo Pratama
1996 Obtained GSM 900 operating license and commercially launched its GSM services with focus on Jakarta, Bandung and Surabaya.
1997 Established an integrated microcell network in Jakarta’s Golden Triangle area.
1998 Launched proXL, its prepaid cellular service brand.
1999 Entered Sumatera and Batam markets.
2001 Received a DCS 1800 spectrum allocation and finalized its fiber optic backbone.
Launched M-banking and M-fun services.
2002 Expanded its network coverage to Kalimantan and Sulawesi.
Launched leased line and IP (Internet Protocol) services.
2004 Revitalized the XL logo and individually marketed its prepaid and postpaid brands: jempol (prepaid), bebas (prepaid) and Xplor (postpaid).
2006 Became a subsidiary of the TM Group and listed on the Bursa Efek Indonesia (previously Bursa Efek Jakarta) under ticker code EXCL.
2007
Introduced its Rp1/minute tariff.
ETISALAT became a shareholder. ETISALAT is the second largest telecommunications company in the Middle East.
Started to consolidate brands under XL prepaid and XL postpaid.
2008
TM Group completed its demerger of TM International Berhad (TMI), whereby Indocel Holding Sdn. Bhd, a subsidiary of TMI, acquired all XL shares owned by Khazanah Nasional Berhad, increasing Indocel Holding Sdn. Bhd.’s stake in XL to 83.8%.
3.1.2.4 PT Natrindo Telepon Seluler (NTS)
PT Natrindo Telepon Seluler, as the holder of registered trademark of
AXIS, is a national GSM and 3G cellular service provider in Indonesia, offering
innovative and affordable wireless communications services within its service
areas. The company began their operations in Java and Sumatra, and rapidly
45
expanding its 2G and 3G networks to major market and population centers
throughout the archipelago.
The AXIS brand and logo is a symbol of progressiveness and change.
Their goal is for subscribers to enjoy the full benefit of mobile communications
services, which will enrich the way they work and play.
AXIS is supported by two prominent operators in Asia: Saudi Telecom
Company, the national telecommunications service provider in the Kingdom of
Saudi Arabia; and Maxis Communications Berhad, the largest mobile services
provider in Malaysia. These two major investors are committed to the full
development of the Indonesian telecommunications sector.
At AXIS they believe that it is not just "what we do" that is important, but
also "how we do it." The company always aim to carry out our activities
responsibly and have fun doing so. Wherever they are, they feel an obligation to
do business with integrity, as expressed in company’s Code of Conduct and
corporate values.
AXIS is proud to be a responsible corporate citizen. The corporate social
responsibility (CSR) activities embrace all stakeholders, involving local
communities and societies. The company is committed to play the role to
enhance the lives of those the company is involved with, and to support the
Indonesian government's telecommunications objectives.
AXIS currently employs over 400 professionals nationwide, led by a team of
experienced professionals. The company aspires to be an exciting and dynamic
organization. It provides a unique work environment that enables young
professionals to develop themselves within a corporate culture that promotes
passion, inspiration, accountability, speed, and motivation.
46
3.1.2.5 Hutchison Charoen Pokphand Telecom (HCPT)
3 service was launched commercially in Indonesia on 30 March 2007 with
the company name is Hutchison Charoen Pokphand Telecommunications
(HCPT). Only after 9 months of operations, 3 acquired about 2.2 million GSM
customers.
As of April 2009, 3 Indonesia had about 4.5 million customers on its GSM
network. 3 offers both pre-paid and post-paid (contract) services. Currently, the
post-paid service is available in Jakarta, Bandung, and Surabaya area.
3 Indonesia slogan is "Jaringan GSM-mu (Your GSM Network)", formerly
"Jaringan Selularmu (Your Cellular Network)". Sometimes, 3 use "Mau? (Want
it?)" and "Hanya di 3 (Only on 3)" slogan in their ads.
3 currently has full GSM coverage in Java, Sumatera, Bali, Lombok, and
Riau Islands. And as of April 2009, Kalimantan is covered in South Kalimantan
and Sulawesi is covered in South Sulawesi. The 3 UMTS/HSDPA service is
currently available in Jakarta and Puncak area, and in some parts of Java only.
3 Indonesia just launched new unlimited text and MMS service at a certain
fee with Facebook on 8 April 2009, so registered 3 customers can update status,
write on wall, or upload new pictures freely without any more charges. Beside
with Facebook, 3 also cooperate with Yahoo to give unlimited chat at a certain
fee by SMS and downloadable mobile program using Yahoo Messenger service.
Both of this is the first of its kind in Indonesia.
47
3.1.3 Market Share of Pre-Paid GSM Providers
Based on the data obtained from the press release of Department of
Information and Telecommunication No. 84/DJPT.1/KOMINFO/7/2008
(www.postel.go.id) in the middle of 2008, the number of pre-paid GSM
subscribers in Indonesia is 102.523.076. The figure shown below is the market
share of GSM providers.
Figure 3.2
Market Share of Pre-paid GSM Providers
3.2 Site and Period of Research
Site of this research is in universities and colleges around Bogor area
where the students as participants. The research is performed between May and
June 2009.
3.3 Research Methods
This research is using a verification method, which is based on the
theoretical knowledge, understanding ability, and findings in the research
48
performed. Verification method utilized in this research is to ascertain the
association between variables, in this case, the relationship between customer
satisfaction and willingness to pay.
3.3.1 Variables Operational
Table 3.4
Variables Operational
Customer Satisfaction and Willingness to Pay
Variables Indicators Scale
Customer Satisfaction
Quality of Network • Ratio
Quality of Call Center • Ratio
Other Services • Ratio
Willingness to Pay Intra-Network Connection Tariff
• Ratio
3.3.2 Types and Source of Data
In this paper, the author strives to obtain information related to the object of
the research. The data provided in this research are both primary and secondary
information.
1. Primary data, which is collected directly from the participants through
a questionnaire.
2. Secondary data, where the information is obtained from literature,
textbooks, and from the official statistics institution.
49
Table 3.5 Quantitative Data
Type of Data Unit Source
Questionnaire External
Number of Students External (DIKTI)
Table 3.6 Qualitative Data
Type of Data Unit Source
History of Industry External
List of Providers External
3.3.3 Data Collecting Method
In order to obtain the complete data from the object of this research, the
author uses several reviewing method, which is as follows.
1. Library Research
Data collecting using this method is obtained by reviewing textbooks,
journals, and other literatures related to the research problems as a
strong platform between theories and practical.
2. Field Research
Field research is used to obtain data by performing a direct research
or observation to the object of this research. In this field research, the
author obtains the data needed by spreading questionnaires directly
to the participants. The questionnaire uses both of open-ended and
close-ended methods.
50
3.3.4 Analysis Method
Data analysis of this research follows a quantitative approach, which is the
technique of data analysis performed with a measurement to answer the
research problems and suggested hypothetical test.
In order to obtain the data needed in performing the measurement and to
answer the research problems, the author uses a questionnaire with the
instruments as mentioned in the indicators of the variables operational (table 3.4).
The questionnaire utilizes 11 points Likert Scale to score respondent’s answers,
which range from “Strongly Agree” to “Strongly Disagree” and from “Strongly
Satisfied” to “Strongly Dissatisfied”.
3.3.4.1 Validity Test
The validity test utilized to find out whether a research instrument has the
ability to measure what it is designed to measure. Validity refers to the extent to
which the empirical measure adequately reflects the real meaning of the concept
under consideration.
In the social sciences there appear to be two approaches to establishing
the validity of research instrument: logic and statistical evidence. Establishing
validity through logic implies justification of each question in the relation to the
objectives of the study, whereas the statistical procedure provides hard evidence
by way of calculating the coefficient of correlations between the questions and
the outcomes variables.
Since the logical approach needs a backing of experts in the justification,
thus, in order to ascertain the validity of the questionnaire, the author used the
equation below and tested the result from thirty samples.
51
∑ ∑ .∑
. ∑ ∑ . . ∑ ∑
Where:
∑ = Total score of ith question
∑ = Total score of all questions from jth participant
∑ = Total score of multiplication x and y
3.3.4.2 Reliability Test
The concept of reliability in relation to a research instrument has a meaning
that the research tool is consistent and stable, and hence, predictable and
accurate. The greater the degree of consistency and stability in instrument, the
greater is its reliability. The method that commonly used for measuring the
reliability of an instrument is the split-half technique.
The split-half technique is designed to correlate half of the items with the
other half and is appropriate for instruments that are designed to measure
attitudes towards an issue or phenomenon. This technique calculates the
reliability using the product moment correlation between scores obtained from the
two halves.
∑ ∑ .∑
.∑ ∑ . . ∑ ∑
Where:
∑ = Total score of first half
∑ = Total score of second half
∑ = Total score of multiplication x and y
52
Because of the product moment correlation is calculated on the basis of
only half the instrument, to assess reliability for the whole it needs to be
corrected. This is known as stepped-up reliability. The stepped-up reliability for
the whole instrument is calculated by a formula called the Spearman-Brown
formula. 21
Where:
= Correlation value between first and second half
= Internal reliability value of the whole items
3.3.4.3 Regression Analysis
In order to ascertain the relationship between customer satisfaction (CS)
and willingness to pay (WTP), the author utilizes a regression model. Regression
analysis is concerned with the study of the dependence of one variable, the
dependent variable, on one or more other variables, the explanatory variables,
with a view to estimating and/or predicting the (population) mean or average
value of the former in terms of the know or fixed (in repeated sampling) values of
the latter.
The general form of linear regression equation is as follows.
Where:
read Y prime, is the predicted value of the Y variable for a selected X value.
is the Y-intercept. It is the estimated value of Y when X = 0.
is the slope of the line, or the average change in for each change of one
unit (increase or decrease) in the independent variable
is any value of the independent variable that is selected.
53
It should be noted that the linear regression equation for the sample is just
an estimate of the relationship between variables. Thus, the value of and in
the regression equation are usually referred to as the estimated regression
coefficients, or simply the regression coefficients. The formula of and are:
Slope of the regression line
∑ ∑ ∑∑ ∑
Y-Intercept
∑ ∑
Where:
∑ is the sum of the values of the independent variable
∑ is the sum of the values of dependent variable
is the number of items in the sample
∑ is the sum of the products of the two variables
∑ is the sum of squares of the independent variable
3.3.4.4 Coefficient of Correlation
The coefficient of correlation describes the strength of the linear
relationship between two sets of variables. Designated , it is often referred to as
Pearson’s and as the Pearson’s product-moment correlation coefficient.
The coefficient of correlation can be computed from a computational
formula based on the actual values of and . The formula is:
∑ ∑ .∑
. ∑ ∑ . . ∑ ∑
54
Where:
is the number of paired observations.
∑ is the X variable summed.
∑ is the Y variable summed.
∑ is the X variable squared and the squares summed.
(∑ is the X variable summed and the sum squared.
(∑ is the Y variable squared and the squares summed.
∑ is the Y variable summed and the sum squared.
∑ is the sum of the products of X and Y.
The figure 3.3 summarizes the strength and direction of the coefficient of
correlation.
Source: Lind, Marshal and Wathen. 2003, 385
Figure 3.3
Strength and Direction of the Coefficient of Correlation
Perfect negative
correlation
Perfect positive
correlation No
correlation
Strong negative
correlation
Moderate negative
correlation
Weak negative
correlation
Weak positive
correlation
Moderate positive
correlation
Strong positive
correlation
-1.00 1.00 0.50 -0.50 0 Negative
correlation Positive
correlation
55
CHAPTER IV
RESULT AND DISCUSSION
The research of this study performed between May – June 2009 with
students from universities and colleges in Bogor area as the participants. The
author spent more than 200 of questionnaires for the research, however, in order
to obtain the significant result, the author made prerequisites for the answers
given by the participants and only choosing 100 of the most relevant results.
In the questionnaire, participants evaluated written scenarios that were set
in a cellular provider services context. To induce different level of customer
satisfaction, the author established expectations about the cellular provider
services and then manipulated the actual experience with the service. The object
was described as a GSM provider that offers a pre-paid cellular
telecommunication service. Willingness to pay is measured with an open-ended
question, where respondents asked to state the maximum amount of credits that
they would be willing to spend for an intra-network connection tariff per minute in
every given scenarios.
The manipulation of the actual experience was analogous to a conjoint
design with three key attributes of the cellular provider service: quality of network,
quality of call center, and other value-added services. Each attribute was varied
at two levels, resulting in eight different scenarios as in table 4.2.
Since the questionnaire contains a simulation of cellular providers offering,
the author held the research in class and gave a proper explanation about the
aim of the research in order to attain a better understanding from the participants.
Moreover, the table of customer satisfaction manipulation was attached to the
56
questionnaire as guidance for the participants to give a better reflects of every
scenario.
Table 4.1
Customer Satisfaction Manipulation
Attributes Dimensions Favorable Unfavorable
Quality of Network
Intra-network connection, interconnection, mobile usage
The voice quality of both intra-network and interconnection is very clear. It is remain clear in mobile use.
The voice quality is poor for both intra-network and interconnection. It is getting worse in mobile use.
Quality of Call Center
Responsiveness, friendliness, accessibility
Response well in giving solutions, the staff are friendly and courteous, and it is easy to reach
The response is bad, and not giving a sufficient solution. The staff are not well-mannered and it is hard to reach
Other Value-Added Services
Features, the ease of use, Internet support
Provide an attractive features, the application is easy to perform, and a great Internet support
The contents are not attractive, the application is not user-friendly, and a poor Internet support
Table 4.2
Scenarios of Provider’s Offerings
Scenario Attributes
Quality of Network Quality of Call Center Other Services
1 - - - 2 - - + 3 - + - 4 + - - 5 + + - 6 + - + 7 - + + 8 + + +
Where:
+ = favorable
- = unfavorable
57
4.1 Number of Samples
According to the data obtained in DIKTI (www.evaluasi.or.id), the number of
university student in Bogor area are 29,918. Thus, the author utilizes Slovin
Sampling equation to determine the number of samples needed in performing the
research with a 0.1 error sampling.
1
Where:
= Number of samples
= Number of population
= Error sampling
299181 29,918. 0.1
99.66
Samples
4.2 Validity Test
The questionnaire of this research uses the same questions for every
scenario, therefore, the author only test for the validity of the first scenario.
Table 4.3
Validity Test of First Scenario
No 1 1 4 4 1 16
2 5 17 85 25 289
3 3 12 36 9 144
4 1 4 4 1 16
5 1 4 4 1 16
6 2 8 16 4 64
58
Table 4.3 (Continued)
7 2 9 18 4 81
8 2 9 18 4 81
9 1 4 4 1 16
10 3 13 39 9 169
11 1 7 7 1 49
12 1 6 6 1 36
13 1 4 4 1 16
14 1 4 4 1 16
15 1 4 4 1 16
16 1 4 4 1 16
17 1 4 4 1 16
18 3 11 33 9 121
19 5 17 85 25 289
20 1 6 6 1 36
21 2 8 16 4 64
22 1 8 8 1 64
23 3 15 45 9 225
24 1 4 4 1 16
25 2 12 24 4 144
26 1 4 4 1 16
27 1 4 4 1 16
28 1 4 4 1 16
29 1 6 6 1 36
30 5 20 100 25 400
Total (∑) 55 236 600 149 2500
0.950486908
= 30 ∑ = 600
∑ = 55 ∑ = 149
∑ = 236 ∑ = 2500
59
∑ ∑ .∑
. ∑ ∑ . . ∑ ∑
30 600 55 23630. 600 55 . 30. 2500 236
.
From the above calculation of first question in scenario one validity test, it
found that the value of statistics is 0.950. To simplify the conclusion, the value
of from the calculation compared with the critical value of Pearson Product-
Moment Correlation Coefficient. The validity test uses 30 samples and a 0.1 level
of significance. From the value comparison, it is clearly seen that the value of
statistics = 0.950 > table = 0.306, and thus clarify that the first question in
scenario one is valid. Table 4.2 shows the results of validity test for every
question in scenario one.
Table 4.4
Validity Test of All Questions in Scenario One
No statistics table Validity
1 0.950 0.306 Valid
2 0.933 0.306 Valid
3 0.903 0.306 Valid
4 0.772 0.306 Valid
The statistics value of the whole questions in scenario one are all above
the table value. In other words, the result indicates that all of the questions in
scenario one are valid or suitable to be utilized in obtaining the data needed in
this research.
60
4.3 Reliability Test
Table 4.5
Reliability Test of First Scenario
No 1 2 2 4 4 4
2 10 7 70 100 49
3 6 6 36 36 36
4 2 2 4 4 4
5 2 2 4 4 4
6 4 4 16 16 16
7 4 5 20 16 25
8 4 5 20 16 25
9 2 2 4 4 4
10 6 7 42 36 49
11 3 4 12 9 16
12 3 3 9 9 9
13 2 2 4 4 4
14 2 2 4 4 4
15 2 2 4 4 4
16 2 2 4 4 4
17 2 2 4 4 4
18 6 5 30 36 25
19 9 8 72 81 64
20 3 3 9 9 9
21 4 4 16 16 16
22 5 3 15 25 9
23 9 6 54 81 36
24 2 2 4 4 4
25 4 8 32 16 64
26 2 2 4 4 4
27 2 2 4 4 4
28 2 2 4 4 4
29 2 4 8 4 16
30 10 10 100 100 100
61
Table 4.5 (Continued)
Total (∑) 118 118 613 658 616
0.867590249
= 30 ∑ = 613
∑ = 118 ∑ = 658
∑ = 118 ∑ = 616
∑ ∑ .∑
.∑ ∑ . . ∑ ∑
30 616 118 11830. 613 118 . 30. 658 118
.
The stepped-up reliability
21
2 0.8681 0.868
.
From the above calculation of reliability test for scenario one, it is found that
the value of statistics is 0.929, and it is higher than the table value = 0.306
( statistics = 0.929 > table =0.306). Thus, the instrument for this research is
assumed reliable for the data collection.
62
4.4 Respondents Profile
The participants for this research are students from several universities and
colleges in Bogor area. Under mentioned below are profiles from a hundred
respondents.
Table 4.6
Respondents Profile: Range of Age
Range of Age Percentage (%)
16-19 Years 15
20-24 Years 70
25-29 Years 8
> 30 Years 7
In table 4.5, it shows that the biggest number of respondents came from the
students in the age between 20-24 years old, with a 70% of contribution.
Respondents in range 16-19 years old with 15%, 25-29 years old with 8%, and
7% came from respondents above 30 years old.
Table 4.7
Respondents Profile: Gender
Gender Percentage (%)
Male 43
Female 57
As seen in table 4.6, the percentage of female respondents is 57%,
whereas male respondents have a lower number with 43% contribution for the
research.
63
Table 4.8
Respondents Profile: City of Origin
City of Origin Percentage (%)
BEKASI 3
BOGOR 59
DEPOK 3
JAKARTA 6
TANGERANG 3
Outside Jabodetabek area 26
Table 4.7 shows that 59% of the respondents are came from Bogor.
Respondents from Bekasi, Depok, and Tangerang have the same number with
3% for each. Six percents of respondents came from Jakarta, and the remaining
are from outside Jabodetabek area with 26%.
Table 4.9
Respondents Profile: University / College
University / College Percentage (%)
STEI TAZKIA 12
STIE BINANIAGA 10
STIE KESATUAN 33
UNIVERSITAS PAKUAN 17
UNIVERSITAS DJUANDA 5
INSTITUT PERTANIAN BOGOR 23
As mentioned before, the respondents of the research are students from
various universities and colleges in Bogor area. From table 4.8, the biggest
number of respondents is from STIE Kesatuan by 33% of contribution. Institut
Pertanian Bogor by 23%, Universitas Pakuan by 17%, STEI Tazkia by 12%, STIE
Binaniaga by 10%, and the smallest portion of contribution came from Universitas
Djuanda with 5%.
64
Table 4.10
Respondents Profile: Employment Status
Employment Status Percentage (%)
Employed 27
Unemployed 73
Table 4.9 shows that the number of students that already employed is 27%
of the total respondents and 73% are still unemployed.
Table 4.11
Respondents Profile: In-Use Brands of Cellular Products
Brand Percentage (%)
THREE 8
IM3 34
SIMPATI 18
XL 9
FLEXI 5
AS 9
MENTARI 6
ESIA 8
SMART 1
AXIS 1
From table 4.10, it is clearly seen that IM3 has the biggest market in this
research with 34% of share. The second is Simpati with 18%, then XL and AS
with 9% for each, Three and Esia has the same share of 8% for each, Mentari
has 6%, Flexi has 5% of share, and Smart and Axis has the same share of 1%
for each.
65
Table 4.12
Respondents Profile: Range of Expenditure
Range of Expenditure Percentage (%)
< Rp.25.000 9
Rp.25.000 - Rp.50.000 37
Rp.50.000 - Rp.75.000 21
Rp.75.000 - Rp.100.000 18
> Rp.100.000 15
The respondents’ cellular telecommunication credits expenditure per month
is mostly in range Rp.25.000 – Rp.50.000 by 37%. Then followed by range
Rp.50.000 – Rp.75.000 by 21%, range Rp.75.000 – Rp.100.000 by 18%, above
Rp.100.000 by 15%, and below Rp.25.000 with 9%.
4. 5 Regression Analysis: Customer Satisfaction and Willingness to Pay
The main idea of this research is to ascertain the relationship between
customer satisfaction and willingness to pay in pre-paid GSM university student
market. Therefore, the author utilizes the regression model to measure its
relationship.
∑ ∑ ∑∑ ∑
∑ ∑
Where:
Willingness to Pay (WTP)
is the WTP-intercept
is the slope of the line
Customer Satisfaction (CS)
66
Table 4.12 provides the means of every data in scenarios obtained from the
research. The data is used to examine the relationship between customer
satisfaction and willingness to pay.
Table 4.13
Means of Customer Satisfaction and Willingness to Pay Value
Scenario Attributes
Customer Satisfaction Willingness to PayN CC OS
1 - - - 1,90 133,00 2 - + - 2,84 181,11 3 - - + 3,02 191,60 4 - + + 4,65 282,65 5 + - - 4,97 289,60 6 + + - 6,51 373,15 7 + - + 6,86 410,85 8 + + + 9,66 578,85
Where:
N = Quality of Network
CC = Quality of Call Center
OS = Other Services
In order to simplify the calculation, table 4.13 provides the summary of data
to be utilized in regression equation.
Table 4.14
Linear Regression
X Y X2 Y2 XY 1.90 133.00 3.60 17,689.00 252.37 2.84 181.11 8.05 32,799.02 513.89 3.02 191.60 9.11 36,710.94 578.16 4.65 282.65 21.62 79,891.02 1,314.32 4.97 289.60 24.65 83,868.16 1,437.86 6.51 373.15 42.41 139,240.92 2,430.14 6.86 410.85 47.09 168,797.72 2,819.46 9.66 578.85 93.22 335,067.32 5,588.80
40.40 2440.81 249.76 894,064.11 14,934.99
67
= 8 ∑ = 14934.99
∑ = 40.40 ∑ = 249.76
∑ = 2440.81 ∑ = 894064.11
The equation to determine the relationship between customer satisfaction
and willingness to pay is as follows:
Slope of the Line:
∑ ∑ ∑∑ ∑
8 14934.99 40.40 2440.818 249.76 40.4
20877.46366.09
.
Intercept:
∑ ∑
2440.818 57.028
40.48
305.10 287.97
.
The Regression Equation:
.
68
Thus, the regression equation is 17.1 57 . Which means that
when the value of customer satisfaction is 1, then the customers’ willingness to
pay will increase as much as 74.1. This equation explains that when the value of
variable customer satisfaction changes, then it will change the variable of
Willingness to pay. For example, if the value of customer satisfaction is 10, the
equation will be 17.1 57 10 then 587.1.
To ensure the above regression calculation, the author provides the
regression calculation result from Minitab statistical software.
Figure 4.1
Regression Calculation from Minitab
Furthermore, the author performs a hypothesis test by calculating the
Standard Error of Estimate . and Estimated Standard Deviation of
Regression Coefficient as follows.
Regression Analysis: Relationship between Customer Satisfaction and Willingness to Pay The regression equation is WTP = 17.1 + 57.0 CS Predictor Coef SE Coef T P Constant 17.129 7.898 2.17 0.073 CS 57.028 1.414 40.34 0.000 S = 9.56205 R-Sq = 99.6% R-Sq(adj) = 99.6% Analysis of Variance Source DF SS MS F P Regression 1 148824 148824 1627.68 0.000 Residual Error 6 549 91 Total 7 149372
69
Standard Error of Estimate:
.∑ ∑ ∑
2
.894064.11 17.1 2440.81 57 14934.99
8 2
. .
Estimated Standard Deviation of Regression Coefficient:
∑ ∑ /
9.562249.76 40 /8
9.562√249.76 203.99
9.5626.765
.
Hypothesis test:
0 the relationship is not exist
0 the relationship is exist significantly
Rejection Rule:
Using test statistics: Reject if / or if /
Where / is based on distribution with 2 degrees of freedom.
Level of significance 0.1 / 0.05
8 2 6
70
From the table, it finds that the value is . 1.943
To obtain the sufficient evidence from the value of table, author performs a
statistical hypothesis test as follows:
Test Statistics:
571.413
.
The result shows that the value of statistics (40.345) > table (1.943).
This means is rejected and clarifies that the relationship between customer
satisfaction and willingness to pay exists with a 0.1 level of significance. Thus,
the statistical evidence is sufficient to conclude that there is a significant
relationship between customer satisfaction and willingness to pay.
Figure 4.2
Hypothesis Test of Regression Analysis
Figure 4.2 shows that the statistics falls inside the area where is
rejected. Therefore, it explains the null hypothesis that states there is no
relationship between customer satisfaction and willingness to pay is rejected, and
71
the alternate hypothesis that states there is a relationship between customer
satisfaction and willingness to pay is accepted.
Figure 4.3
Relationship between Customer Satisfaction and Willingness to Pay
4.5.1 Residual Analysis
Residual analysis is the primary tool for determining whether the assumed
regression model is appropriate. The linear regression of customer satisfaction
and willingness to pay was assumed in the equation below.
This model indicates that the author assumes willingness to pay to be linear
function of the customer satisfaction plus an error term . Assumptions about the
error term are as follows.
1. E = 0
2. The variance of denotes by , is the same for all values of
3. The values of are independent
4. The error term has a normal probability distribution.
72
Much of the residual analysis is based on the examination of graphical
plots. Thus, the author provides the following residual plots of the research, in
order to determine whether the assumptions for are appropriate.
1. A plot of the residuals versus values of customer satisfaction
2. A plot of residuals versus the predicted values of willingness to pay
3. A standardized residual plot
4.5.1.1 Plot of the Residual versus Values of Customer Satisfaction
A residual plot versus the independent value of (Customer Satisfaction) is
a graph in which the values of the independent variable are represented by the
horizontal axis and the corresponding residual values are represented by vertical
axis. From figure 4.4, it shows that the residuals appear in a good pattern since
the plots do not indicate greater variability about the regression line for larger
values of customer satisfaction. Thus, the author feels confident to conclude that
the simple linear regression of customer satisfaction and willingness to pay is
valid.
Figure 4.4
Plot of the Residual versus Values of Customer Satisfaction
73
4.5.1.2 Plot of the Residual versus Values of Willingness to Pay
Another residual plot represents the predicted value of the dependent
variable Willingness to pay on the horizontal axis and the residual values on the
vertical axis. A point is plotted for each residual. For simple linear regression,
both of the residual plot versus and the residual plot versus provide the same
pattern. Residual plot versus dependent variable of willingness to pay in figure
4.5 shows the same pattern as the pattern of residual plot versus the
independent variable of customer satisfaction. Thus, the result also indicates that
the assumed regression model is appropriate.
Figure 4.5
Plot of the Residual versus Predicted Values of Willingness to pay
4.5.1.3 Plot of the Standardized Residual versus Values of Customer
Satisfaction
The standardized residual plot can provide insight about the assumption
that the error term has a normal distribution. If this assumption is satisfied, the
distribution of the standardized residuals should appear to come from a standard
normal probability distribution. Thus, the plots are supposed to have
74
approximately 95% of the standardized residuals between -2 and 2. In figure 4.6,
it shows that all standardized residuals are between -2 and 2. Therefore, based
on the standardized residuals, the figure confirms that the error term has a
normal distribution.
Figure 4.6
Plot of the Standardized Residual versus Values of Customer Satisfaction
4.6 Correlation Analysis: Customer Satisfaction and Willingness to Pay
The second analysis of this study is to examine the strength of the
association between two variables, in this case the customer satisfaction and
willingness to pay. Therefore, author utilizes the correlation analysis to measure
the strength of relationship between customer satisfaction and willingness to pay.
The usual first step is to plot the data in a scatter diagram.
75
Figure 4.7
Scatterplot of Willingness to Pay and Customer Satisfaction
Using the same data in table 4.13, the correlation equation is as follows.
∑ ∑ .∑
. ∑ ∑ . . ∑ ∑
Where:
= 8 ∑ = 14934.99
∑ = 40.40 ∑ = 249.76
∑ = 2440.81 ∑ = 894064.11
8 14934.99 40.4 2440.818 249.76 40.4 . 8 894064.11 2440.81
20877.4620915.90
.
From the calculation regarding the relationship between customer
satisfaction and willingness to pay, the author finds that the coefficient of
correlation is 0.998. This means that the relationship between customer
76
satisfaction and willingness to pay is positive and strong. However, this result
does not have precise meaning. A measure that has a more easily interpreted
meaning is the coefficient of determination. It is computed by squaring the
coefficient of correlation.
0.998 x 100%
. %
The result states that 99.6% of the variation in willingness to pay is
explained, or accounted for, by the variation in the level of customer satisfaction.
In order to ascertain the calculation, the author compares the result with Minitab
and finds a same coefficient of correlation value.
Figure 4.8
Correlation Calculation from Minitab
To improve the analysis, the author performs a hypothesis test to find out
the significance of the correlation coefficient. The null hypothesis and the
alternate hypothesis are:
ρ 0 The correlation in population is zero
ρ 0 The correlation in the population is different from zero
test for the coefficient of correlation is as follows.
√ 2√1
with 2 degree of freedom
Correlations between Customer Satisfaction and Willingness to Pay Pearson correlation of CS and WTP = 0.998
P-Value = 0.000
77
From the table, the critical value of with 0.1 level of significance and
8 2 6 is 1.943. The decision rule states that if statistics falls in the
area between 1.943 and -1.943, the null hypothesis is not rejected.
0.998√8 2√1 0.998
2.4420.077
.
The result shows that the value of statistics (38.671) > table (1.943).
This means is rejected and clarifies that there is a correlation between
customer satisfaction and willingness to pay with a 0.1 level of significance. Thus,
the statistical evidence is sufficient to conclude that there is a correlation between
customer satisfaction and willingness to pay in the population. Figure 4.9 shows
that the statistics falls inside the area where is rejected.
Figure 4.9
Hypothesis Test of Coefficient of Correlation
78
CHAPTER V
CONCLUSION AND SUGGESTION
5.1 Conclusion
1. The regression calculation shows that the value of 57.028 is
positive and significantly different from zero. The result indicates that
the relationship between customer satisfaction and willingness to pay
in pre-paid GSM university student market is statistically significant (
statistics = 40.345 > table = 1.943) and confirms the hypothesis one
that states the relationship between customer satisfaction and
willingness to pay is significant.
2. From the residual analysis, the results explained that the linear
regression model is appropriate for the relationship between
customer satisfaction and willingness to pay, since the assumptions
for the residual analysis of linear regression is fulfilled by the
regression equation. Therefore, the findings support hypothesis two
that assumes the relationship is linear, whereas the alternate
hypothesis two is rejected. The linear function of the relationship
explained that every change in customers’ level of satisfaction would
affect customers’ willingness to pay.
3. The strength of relationship between customer satisfaction and
willingness to pay shows a strong and positive association, with the
value of 99.6%. This means that 99.6% of the variation in
willingness to pay is explained, or accounted for, by the variation in
the level of customer satisfaction. The hypothetical test of the
correlation is also significant with statistics 38.671 > table 1.943,
79
which also confirms hypothesis three that states the relationship is
positive and strong. The findings support the notion that customer
satisfaction has a positive impact on company’s profitability, since
customers are willing to pay more for products or services when it
reaches the desired level of satisfaction.
5.2 Suggestion
1. The author would like to suggest providers to maximize customers’
satisfaction by offering non-tariffs attributes, such as quality of
network, quality of customer service, and other value-added services
in order to increase customers’ willingness to pay and to improve their
profitability.
2. Providers must adjust appropriate tariff offerings by analyze
customers’ satisfaction about their services at present, and when they
found that their tariff offerings exceed customers’ willingness to pay at
a particular level of satisfaction, then they must lower the tariffs, or
else, improve their services to attain a greater level of customers’
satisfaction.
3. The relationship between customer satisfaction and willingness to pay
is strong and positive, thus, providers must totally consider the
customer satisfaction in their corporate strategies, because customer
satisfaction has become a very important issue in providers’
profitability.
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APPENDIX
No Scenario 1 Scenario 2 Scenario 3 Scenario 4 CS WTP CS WTP CS WTP CS WTP
1 1.00 50.00 1.00 50.00 1.00 50.00 6.00 300.00
2 1.50 - 5.00 500.00 2.75 500.00 8.00 800.00
3 1.00 150.00 2.00 150.00 2.00 150.00 2.00 150.00
4 1.50 150.00 2.00 150.00 1.75 150.00 2.00 200.00
5 1.00 200.00 1.00 210.00 1.25 225.00 2.00 250.00
6 1.00 - 2.50 150.00 1.00 150.00 2.75 500.00
7 1.00 150.00 1.00 150.00 1.00 150.00 1.00 150.00
8 1.00 100.00 4.00 100.00 2.25 200.00 4.00 200.00
9 1.00 - 1.00 100.00 1.00 50.00 2.00 200.00
10 1.50 100.00 2.25 150.00 2.25 150.00 4.25 200.00
11 2.00 150.00 3.00 300.00 5.00 300.00 5.00 300.00
12 6.00 50.00 5.00 50.00 4.50 50.00 6.50 150.00
13 1.75 - 2.50 25.00 3.75 40.00 5.50 75.00
14 5.00 100.00 5.00 100.00 5.00 100.00 5.00 100.00
15 1.00 20.00 1.00 20.00 1.00 20.00 9.00 100.00
16 2.00 800.00 6.75 900.00 6.75 900.00 6.75 900.00
17 1.00 50.00 1.00 100.00 3.50 100.00 6.00 100.00
18 1.25 50.00 3.25 75.00 4.75 100.00 5.00 110.00
19 1.25 50.00 4.00 150.00 2.75 150.00 6.25 150.00
20 1.00 100.00 2.00 150.00 3.00 200.00 4.00 450.00
21 1.00 100.00 6.00 125.00 6.25 150.00 7.75 250.00
22 1.00 300.00 1.75 300.00 3.75 500.00 5.00 500.00
23 6.25 300.00 5.50 400.00 7.50 400.00 8.75 800.00
24 1.00 50.00 1.00 50.00 1.00 50.00 7.75 500.00
25 1.75 500.00 2.75 600.00 2.25 600.00 5.00 600.00
26 1.25 150.00 3.00 300.00 4.00 350.00 5.00 300.00
27 1.00 100.00 1.00 100.00 1.00 100.00 1.00 100.00
28 1.25 50.00 2.25 100.00 1.50 50.00 3.00 150.00
29 2.75 100.00 5.00 150.00 1.25 100.00 3.75 150.00
30 5.00 200.00 5.50 250.00 5.50 200.00 6.00 300.00
31 6.50 200.00 6.75 300.00 4.75 300.00 7.25 500.00
32 1.25 150.00 2.00 200.00 1.75 200.00 4.25 350.00
33 1.00 350.00 1.75 450.00 2.75 350.00 7.00 450.00
34 1.00 500.00 2.75 500.00 2.00 400.00 2.75 400.00
35 1.50 200.00 2.25 200.00 1.00 200.00 1.50 300.00
36 1.25 150.00 3.75 200.00 2.75 200.00 7.75 350.00
37 6.00 50.00 3.25 75.00 4.00 75.00 6.50 75.00
38 1.00 150.00 3.00 200.00 1.00 150.00 4.00 250.00
39 5.75 25.00 5.75 100.00 6.25 50.00 4.25 125.00
40 2.50 300.00 2.25 500.00 2.50 500.00 3.00 500.00
41 1.50 500.00 1.25 500.00 1.25 500.00 1.25 500.00
42 2.00 75.00 2.75 85.00 2.25 95.00 3.00 100.00
43 1.00 100.00 2.00 150.00 2.25 200.00 4.75 500.00
44 3.00 50.00 5.75 100.00 5.25 60.00 6.75 400.00
45 1.00 50.00 4.00 130.00 3.00 100.00 6.50 200.00
46 1.00 100.00 3.25 150.00 1.25 100.00 5.25 300.00
47 1.00 50.00 2.00 50.00 1.00 50.00 2.25 100.00
48 1.75 50.00 3.75 75.00 3.00 75.00 7.00 100.00
49 3.00 50.00 3.50 100.00 3.25 100.00 5.25 150.00
50 1.00 500.00 3.00 500.00 3.00 500.00 7.00 1,000.00
51 1.00 50.00 2.25 100.00 1.00 50.00 3.25 250.00
52 1.25 50.00 2.50 150.00 2.25 100.00 3.25 250.00
53 4.50 - 7.75 500.00 5.75 500.00 7.50 750.00
54 3.00 50.00 4.00 200.00 5.00 200.00 7.00 500.00
55 6.00 500.00 6.00 700.00 6.00 500.00 6.50 500.00
56 1.50 50.00 3.00 100.00 4.00 100.00 4.75 100.00
57 1.00 100.00 4.00 100.00 4.75 100.00 7.25 100.00
58 1.50 90.00 3.75 100.00 3.00 100.00 6.50 100.00
59 1.00 200.00 2.75 300.00 2.75 300.00 7.25 700.00
60 1.00 150.00 1.00 150.00 1.00 100.00 5.00 150.00
61 1.00 100.00 1.00 100.00 1.00 100.00 5.25 125.00
62 1.00 10.00 1.00 10.00 1.00 10.00 6.00 100.00
63 4.50 100.00 5.50 100.00 2.25 100.00 3.75 100.00
64 7.00 50.00 7.00 50.00 7.00 50.00 7.00 50.00
65 1.00 50.00 2.75 100.00 1.75 150.00 2.50 300.00
66 1.00 50.00 3.75 100.00 2.25 100.00 4.50 100.00
67 4.50 150.00 4.50 150.00 4.50 150.00 4.50 150.00
68 2.00 100.00 3.75 150.00 2.75 100.00 5.50 250.00
69 1.75 100.00 3.75 100.00 3.50 100.00 4.50 150.00
70 1.00 50.00 2.75 150.00 1.75 50.00 5.25 250.00
71 6.00 250.00 6.00 250.00 5.25 300.00 6.25 300.00
72 1.50 50.00 3.25 150.00 3.50 100.00 6.50 250.00
73 1.00 500.00 1.75 500.00 3.00 500.00 5.00 500.00
74 1.00 10.00 1.00 50.00 2.25 50.00 5.00 100.00
75 1.00 50.00 3.00 100.00 2.00 50.00 6.00 200.00
76 1.00 50.00 3.50 100.00 2.00 75.00 5.25 200.00
77 1.00 - 4.00 500.00 1.75 500.00 5.50 500.00
78 1.00 20.00 2.00 30.00 2.00 30.00 3.00 100.00
79 1.00 10.00 6.00 15.00 5.00 10.00 8.00 50.00
80 1.25 50.00 2.00 75.00 3.25 100.00 8.00 80.00
81 1.00 500.00 3.50 800.00 2.50 500.00 5.50 1,000.00
82 1.00 100.00 2.00 150.00 3.00 150.00 3.00 150.00
83 1.00 50.00 1.00 75.00 3.00 80.00 6.00 85.00
84 3.25 100.00 3.75 100.00 4.50 100.00 4.50 100.00
85 1.00 100.00 1.00 100.00 1.00 100.00 3.25 1,000.00
86 2.00 50.00 2.50 75.00 2.50 75.00 4.00 75.00
87 1.75 40.00 2.75 45.00 3.50 75.00 4.50 100.00
88 1.00 100.00 1.00 100.00 1.00 100.00 5.75 500.00
89 1.00 200.00 1.75 215.00 1.25 215.00 3.75 250.00
90 1.00 - 2.00 0.10 2.75 0.50 7.25 100.00
91 1.00 150.00 1.00 150.00 1.00 150.00 3.75 600.00
92 1.25 100.00 2.75 300.00 1.00 100.00 6.75 400.00
93 1.00 200.00 1.00 210.00 2.00 210.00 3.00 220.00
94 2.00 250.00 3.00 250.00 3.00 250.00 7.00 300.00
95 1.75 200.00 4.00 200.00 3.25 150.00 5.50 250.00
96 1.75 150.00 2.50 200.00 3.00 200.00 2.75 250.00
97 1.50 100.00 2.25 110.00 2.50 110.00 3.00 130.00
98 1.00 200.00 1.25 200.00 1.00 200.00 2.75 200.00
99 1.00 - 2.00 150.00 2.00 200.00 3.25 250.00
100 1.25 - 1.75 30.00 2.25 30.00 2.50 60.00
No Scenario 5 Scenario 6 Scenario 7 Scenario 8 CS WTP CS WTP CS WTP CS WTP
1 7.25 300.00 8.00 350.00 2.00 100.00 11.00 750.00
2 8.00 1,000.00 9.00 800.00 7.00 500.00 10.00 1,000.00
3 6.00 300.00 6.00 300.00 5.00 300.00 11.00 1,000.00
4 3.00 250.00 4.75 250.00 3.00 250.00 10.00 300.00
5 3.25 500.00 3.50 550.00 1.75 350.00 10.00 1,200.00
6 5.25 500.00 9.00 1,000.00 3.50 500.00 11.00 1,500.00
7 1.00 150.00 1.00 150.00 1.00 150.00 7.00 1,000.00
8 5.75 200.00 5.25 300.00 5.25 300.00 9.00 400.00
9 8.00 800.00 4.00 500.00 1.00 300.00 11.00 1,200.00
10 6.75 200.00 7.00 200.00 7.50 250.00 8.25 300.00
11 6.00 500.00 7.00 500.00 5.00 500.00 8.00 1,000.00
12 6.75 400.00 5.75 500.00 5.50 300.00 9.00 700.00
13 8.25 150.00 9.00 200.00 6.25 125.00 9.25 350.00
14 5.00 100.00 5.00 100.00 5.00 100.00 5.00 100.00
15 10.00 100.00 10.00 100.00 5.00 30.00 11.00 150.00
16 8.00 1,100.00 8.50 1,200.00 8.00 1,100.00 11.00 1,500.00
17 8.00 100.00 8.00 100.00 7.00 100.00 11.00 100.00
18 6.00 150.00 6.50 180.00 3.75 120.00 8.75 200.00
19 9.00 250.00 9.75 250.00 6.00 200.00 10.75 300.00
20 5.00 600.00 6.00 700.00 7.00 425.00 8.00 800.00
21 7.50 1,000.00 8.25 1,000.00 6.25 900.00 11.00 1,200.00
22 7.00 800.00 6.00 850.00 2.50 350.00 11.00 900.00
23 9.00 900.00 9.25 950.00 5.50 400.00 11.00 1,000.00
24 7.75 650.00 7.00 650.00 5.00 50.00 9.00 800.00
25 7.00 700.00 4.50 650.00 2.00 500.00 9.00 1,000.00
26 6.00 350.00 6.00 350.00 3.00 300.00 11.00 800.00
27 4.00 300.00 4.00 300.00 3.00 200.00 11.00 600.00
28 6.00 250.00 6.50 300.00 1.50 100.00 10.50 500.00
29 7.00 300.00 6.25 350.00 2.50 150.00 9.00 500.00
30 7.25 300.00 6.00 300.00 5.75 200.00 11.00 400.00
31 7.50 650.00 8.25 700.00 4.75 200.00 9.25 900.00
32 6.25 350.00 6.00 400.00 5.00 350.00 10.00 500.00
33 7.75 550.00 7.75 550.00 7.50 650.00 9.50 1,000.00
34 2.75 550.00 3.75 500.00 2.25 400.00 10.00 800.00
35 4.50 450.00 4.50 450.00 4.75 400.00 8.75 700.00
36 8.75 500.00 8.50 900.00 6.00 750.00 11.00 1,000.00
37 7.75 100.00 6.50 100.00 6.00 85.00 11.00 250.00
38 6.00 300.00 7.00 300.00 5.00 150.00 9.00 500.00
39 6.00 175.00 5.25 300.00 5.00 200.00 7.25 400.00
40 4.00 550.00 4.00 550.00 3.50 550.00 8.25 600.00
41 6.00 600.00 6.00 600.00 6.00 600.00 7.00 800.00
42 6.75 150.00 6.75 150.00 6.00 170.00 9.00 500.00
43 6.00 700.00 6.00 700.00 3.25 500.00 9.00 800.00
44 5.25 500.00 8.00 600.00 6.00 300.00 7.50 800.00
45 6.75 250.00 7.75 300.00 4.00 150.00 10.25 400.00
46 6.50 450.00 8.25 500.00 4.00 250.00 10.00 700.00
47 3.00 100.00 3.25 100.00 3.50 100.00 5.00 150.00
48 7.75 150.00 9.00 200.00 3.00 75.00 9.75 500.00
49 6.00 300.00 8.00 350.00 4.75 100.00 10.00 600.00
50 8.00 1,000.00 8.00 1,000.00 7.00 1,000.00 9.00 1,000.00
51 6.25 350.00 6.75 500.00 3.00 200.00 11.00 650.00
52 3.50 30.00 4.50 400.00 2.25 200.00 10.00 500.00
53 9.25 750.00 10.25 1,000.00 10.25 750.00 10.25 1,000.00
54 7.00 500.00 7.00 500.00 6.00 200.00 9.00 800.00
55 7.00 500.00 7.00 500.00 6.50 600.00 8.50 1,000.00
56 5.25 100.00 6.50 100.00 5.75 150.00 8.25 200.00
57 8.25 100.00 8.75 100.00 6.00 100.00 10.00 100.00
58 7.50 110.00 9.00 110.00 7.75 110.00 10.00 150.00
59 9.00 1,200.00 8.50 1,000.00 3.50 300.00 10.75 1,500.00
60 6.00 300.00 6.00 400.00 4.00 200.00 9.00 500.00
61 7.75 150.00 9.00 200.00 6.25 300.00 11.00 500.00
62 10.00 125.00 9.00 150.00 5.00 175.00 11.00 200.00
63 6.00 125.00 3.25 100.00 2.00 100.00 9.00 150.00
64 7.00 50.00 7.00 50.00 7.00 50.00 7.00 50.00
65 5.50 500.00 4.75 700.00 4.25 600.00 10.00 1,000.00
66 6.50 100.00 8.00 100.00 4.25 100.00 11.00 100.00
67 4.75 200.00 5.50 200.00 4.75 200.00 8.50 500.00
68 7.00 350.00 8.50 450.00 3.50 150.00 10.50 500.00
69 6.25 200.00 6.00 150.00 4.75 150.00 10.00 200.00
70 6.00 350.00 8.00 450.00 5.00 250.00 9.25 500.00
71 6.00 300.00 6.00 300.00 6.00 300.00 6.00 300.00
72 6.75 350.00 6.25 450.00 6.00 150.00 8.25 550.00
73 6.00 500.00 9.00 500.00 4.50 500.00 10.00 500.00
74 7.00 100.00 7.25 100.00 5.00 50.00 11.00 200.00
75 6.75 250.00 8.75 300.00 4.25 100.00 10.00 400.00
76 6.00 200.00 7.75 400.00 4.50 150.00 11.00 600.00
77 6.00 500.00 8.25 500.00 4.50 500.00 10.00 500.00
78 7.00 200.00 7.00 250.00 5.75 150.00 8.25 300.00
79 9.00 75.00 9.00 75.00 9.00 75.00 11.00 100.00
80 8.00 100.00 9.00 100.00 5.00 80.00 11.00 150.00
81 8.00 1,100.00 8.25 1,500.00 5.00 1,000.00 11.00 1,500.00
82 5.00 250.00 5.00 250.00 5.00 250.00 7.00 490.00
83 7.25 90.00 8.00 90.00 2.00 85.00 11.00 95.00
84 5.75 100.00 5.75 100.00 4.50 100.00 9.25 100.00
85 6.50 1,500.00 6.50 1,500.00 1.00 100.00 11.00 1,500.00
86 9.00 75.00 7.75 75.00 5.25 50.00 10.00 100.00
87 5.75 125.00 7.00 200.00 4.50 150.00 8.00 300.00
88 5.50 500.00 6.75 700.00 6.75 700.00 11.00 1,000.00
89 5.00 245.00 8.25 250.00 5.75 250.00 11.00 300.00
90 8.00 100.00 6.00 50.00 4.00 50.00 11.00 150.00
91 5.25 600.00 7.25 600.00 3.75 600.00 11.00 1,200.00
92 6.75 450.00 8.25 450.00 4.00 200.00 11.00 450.00
93 6.00 240.00 5.00 220.00 2.00 210.00 11.00 250.00
94 7.00 300.00 8.00 300.00 3.25 200.00 9.00 300.00
95 6.75 300.00 7.50 325.00 3.50 200.00 9.00 350.00
96 7.00 300.00 6.75 300.00 5.25 300.00 11.00 500.00
97 6.00 150.00 4.25 170.00 4.00 180.00 9.00 200.00
98 5.50 250.00 5.25 240.00 1.00 200.00 11.00 300.00
99 8.25 300.00 7.25 300.00 6.00 300.00 10.00 400.00
100 4.75 100.00 6.75 150.00 2.50 70.00 8.75 250.00
