CHAPTER I

INTRODUCTION

This chapter explains about research background, research problem, research

limitation, research objective, research usefulness, and literature review. Research

background explains what the reason of the researcher to conduct this thesis. The research

problem is research questions which are based on theoretical thoughts to obtain problem

solving through research data. The research limitation explains about the limitation of this

research such as the field of research, the amount of samples, etc. The research objective is

things that would be achieved through the research process. The research usefulness

explains about benefits for the science, telecommunication business and researcher that also

can be used as reference for other research.

1.1. Problem Background

The wireless telecommunication business in Indonesia has shown a good

improvement since its beginning in 1990 era. Only in a few years, cellular service providers,

which are the supporting companies of wireless telecommunication business, grow so fast in

the last 15 years. The wireless telecommunication service was once used for business

purposes, but now, it becomes the most popular communication tools for people. People

now cannot be separated from their cellular phones. It is more likely as a primary needs than

a luxury thing nowadays.

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People usually search the easiest way to communicate each other by using cellular

phones with a good service provider that provides wide network coverage, advanced

technology, and of course with a good price. That is why the service providers in Indonesia

are struggling hard to make their companies as the number 1 service providers in Indonesia.

The competition among the service providers in Indonesia becomes tighter and their

technology is progressively improving.

Besides traditional voice communication services, service providers offer more

advanced technology that makes the users more convenient. Not only for calls, cellular

phones now can also send and receive messages, access mobile internet (by using WAP,

GPRS, EDGE, UMTS, and HDSPA), make video calls, and download additional features.

In Manado, now the development of cellular service providers is not too far behind

the development in Java Island, especially in the capital city, Jakarta. There are about 7

providers in Manado. Four of them are GSM service providers and the rest are CDMA

service providers. The GSM providers are Telkomsel, Indosat, XL, and Three, while the

CDMA providers are TelkomFlexi, Fren, and Esia. Telkomsel’s products are Kartu Halo as

the post-paid SIM card, and Simpati, and Kartu As as the pre-paid SIM card. Indosat’s

products are Matrix as the post-paid SIM card, and Mentari and IM3 as the pre-paid SIM

card. XL’s products are XL post-paid and XL pre-paid. The CDMA products are all pre-

paids.

In this competition era, consumers have many choices of products, so, if a company

wants to win the market, it has to build a good relationship to its customers and engage the

customers so that they will not go to other products. The company also has to be able to

2

communicate to its customers. A good marketing communication will make the relationship

between the company and the customers tighter

Marketing communication has been improved by companies in order to get

customers as much as they can. In the early days, marketing communication was separated

and applied one by one. Companies in the early days only rely on one or two

communication tools. This situation makes the promotion was not effective and companies

cannot maximize the profit.

Because of that condition, companies now apply a new concept of marketing

communication, which is the combination of all communication tools. This new concept is

called Integrated Marketing Communication (IMC). By applying this new concept,

companies hope that the communication way will be more effective and more engage the

consumers. Hence, they will maximize profit.

Based on the IMC tools that are Mass Communications and Personal

Communications, the researcher only focuses on Mass Communication tools, which are

Advertising, Sales Promotions, Events, and Public Relations in conducting this research.

1.2. Problem Statement

Based on the situation from the background above, the problem statement is:

Do the Mass Communication modes influence the consumer decision in choosing

telecommunication providers?

Which Mass Communication mode that has the most significant influence to the

consumer decision?

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1.3. Research Limitation

There are so many people are using cellular phone now. Because of the limitation of

time and it is impossible to explore all of the users, so researcher only focus on the cellular

phone users of any mobile phone providers (both GSM and CDMA) in Manado. The

independent variables used are also limited only to the Mass Communication modes, which

are advertising, sales promotions, events, and public relations, while the dependent variable

is the consumers’ decision.

1.4. Research Objective

1. To find out if the Mass Communication modes influence the consumer decision in

choosing telecommunication providers.

2. To find out which Mass Communication mode that has the most significant influence to

the consumer decision.

1.5. Research Usefulness

This research provides several benefits as follows:

1. The Science

To give contribution in scientific work about the influence of the tools of Integrated

Marketing Communication, especially Mass Communication, which are Advertising,

Sales Promotions, Events, and Public Relations to the consumers decision in choosing

telecommunication providers.

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2. Telecommunication Business

To provide information and recommendation about the most effective marketing

communication to telecommunication business that can be used to attract more

consumers.

3. The Researcher

To improve the researcher’s knowledge about Integrated Marketing Communication,

especially Mass Communication modes and also to sharpens the analyzing skill of the

researcher.

1.6. Literature Review

This sub-chapter contains the comparison of this research with the previous

researches.

Table 1.1. Literature Review

Title Author Year

Variables Tools of Analysis

Notes

THE IMPACT OF VISUAL

MERCHANDISING ON THE

CONSUMER DECISION

PROCESS FOR INTIMATE APPAREL

Derry Law, Joanne Yip

Visual Merchandising

(X) and Consumer

Decision (Y)

Axial-Coding Stage

In contemporary

intimate apparel

retailing, the fashion and

trend element becomes

another key reason for

consumers to purchase new

5

Title Author Year

Variables Tools of Analysis

Notes

THE IMPACT OF CONSUMER PACKAGE

COMMUNICATION ON CONSUMER

DECISION MAKING PROCESS

Vitalija Butkeviciene

, Jugita Stravinskien,

Ausra Rutelione

2008 Consumer Package

Communication (X) and Consumer Decision Making

Process (Y)

Empirical Research

intimate apparel and in

order to be distinctive in the market

place. Intimate apparel has paid a close attention to intensify its

retail identity by unique

Visual Merchandising

strategy to arouse

purchase.

This research evaluates the influence of

package components

and features in stages of consumer decision making

process and missing

functions of package

communication excluded in

the model

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Title Author Year

Variables Tool of Analysis

Notes

HABITUAL BUYING PIRATED

SOFTWARE BY CHINESE

CONSUMERS

Fang Wang, Hongxia Zhang, Hengjia

Zang, and Ming

Ouyang

2005 Consumer Buying Habit

Descriptive

The researcher established a

research model by extending a model used by Ang et al. in

studying Singaporeans’ buying pirated

CD.. The findings

were four personal and social factors found to be important in influencing

Chinese consumers’

attitude toward software piracy,

including value

consciousness, normality

susceptibility, novelty

seeking, and collectivism.

In the first journal, the writers, Derry Law and Joanne Yip, were analyzing about the

impact of visual merchandising to the consumers decision making. Based on the research,

there were four reasons of looking for new intimate apparel, these are: physical condition,

print media, peer influence, and self concept. The researcher took this journal as a reference

because in this journal, it is implicitly said that among different kinds of promotional

channel, printed media shared the highest influence in arousing the need to buy something,

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in this case, lingerie. The writer said that the unity of printed advertising and large posters in

window display and store reinforces their memory of the new products and also, the

repetition of the same advertising image further arouse customers’ intention to check out the

promoted products. The finding of this journal really helps the researcher to conduct this

thesis because the researcher is also going to examine the analysis the influence of mass

communication modes, including advertising, to consumers’ decision. However, the

researcher will not reduplicate the whole journal because there are some differences

between what the writers was done and what will the researcher do in conducting this thesis.

The differences are: first, the tool of analysis that was used was axial coding-stage, while the

researcher is going to use multiple linear regressions in this thesis; the second one is the

independent variable that was visual merchandising, while the researcher is going to use

mass communication modes. Although there are some differences, there is also a similarity

of the journal and this thesis, in which, this thesis is going to examine what the consumer

decision is influenced by.

From the second journal, “The Impact of Consumer Package Communication on

Consumer Decision Making Process” by Vitalija Butkeviciene, Jugita Stravinskien, and

Ausra Rutelione, one of the findings stated that the traditional communication is now

inefficient. Companies prefer to use the modern communication that is more integrated. In

the traditional way, companies applied the communicating tools separately and it was

inefficient. Companies only focused in one communication tool, whereas there are many

other marketing tools. Based on this finding, the researcher becomes more convenience to

continue this thesis because there is a support from previous research about what the

researcher wants to examine in this thesis. But still, the researcher thinks that the journal

8

needs to be improved. That is why the researcher conducts this thesis, hopes that this thesis

will give some addition findings in marketing communication field.

Another research in China on 2005 about “Habitual Buying Pirated Software by

Chinese Consumer” was conducted by Fang Wang, Hongxia Zhang, Hengjia Zang, and

Ming Ouyang. The researcher established a research model by extending a model used by

Ang et al. in studying Singaporeans’ buying pirated CD. A survey was conducted.

Hypotheses were tested through stepwise regressions. An exploratory factor analysis was

carried out to analyze Chinese consumers’ attitude toward software piracy. The findings

were four personal and social factors found to be important in influencing Chinese

consumers’ attitude toward software piracy, including value consciousness, normality

susceptibility, novelty seeking, and collectivism. Five attitude measures, which were

important in influencing consumer purchase intention, were identified as reliability of

pirated software, recognized social benefits of piracy, functionality of pirated software, risks

of buying, and perceived legality of buying. An exploratory study identified three attitude

attributes.

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CHAPTER II

THEORETICAL FRAMEWORK

In the chapter of “Theoretical Framework”, researcher presents several theories

related to the subject of research. This chapter is purposely included to present the theories

that will strengthen base the research. This chapter also provides the research hypothesis and

conceptual framework that expected to guide the concept of this research.

2.1. Theories

2.1.1. Marketing

In general, most people think that marketing is always about selling and advertising.

In fact, those things are only a little part of marketing itself. To support this idea, there are

some definitions of marketing based on some books and other sources.

Kotler and Armstrong (2006, p.5) defined marketing as “A social and managerial

process by which individuals and groups obtain what they need and want through creating

and exchanging value with other. In a narrower business context, marketing involves

building profitable, value-laden exchange relationship with customers. Marketing as the

process by which companies create value for customers and build strong relationships in

order to capture value from customers in return.”

Kotler (2005, p.5) defined marketing as “The task of creating, promoting, and

delivering goods and services to consumers and businesses. Marketers are skilled in

stimulating demand for company’s products, but this is too limited a view of the tasks

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marketers performs. Just as production and logistics professionals are responsible for supply

management, marketers are responsible for demand management. Marketing people are

involved in 10 marketing types of entities: goods, services, experience, events, persons,

places, properties, organizations, and ideas.

Burns and Bush (2006, p.4) defined marketing as “An organization function, not a

group of persons or separate entity within the firm. It is also a set of processes and or a

single tactic such as creating an end-aisle display. The processes are creating,

communication, and deliver value to customers. Marketing is not trying to sell customer

something; rather, it is providing customers with something the value. The objective of

marketing is to create and manage customer relationships for the benefit of the organization

and its stakeholders.”

American Marketing Association defined Marketing as “An organizational function

and a set of processes for creating, communicating, and delivering value to customers and

for managing customers’ relationship in ways that benefit the organization and its

stakeholders.”

Marketing includes the activities of all those engaged in the transfer of goods from

producer to consumer not only those who buy and sell directly, wholesale and retail, but

also those who develop, warehouse, transport, insure, finance, or promote the product, or

otherwise have a hand in the process of transfer.

2.1.2. Marketing Communication

Kotler and Keller (2006, p.496) defined Marketing Communications as “The

means by which firms attempt to inform, persuade, and remind consumers-directly or

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indirectly-about the products and brands that they sell. In a sense, marketing

communications represent the voice of the brand and are a means by which it can establish a

dialogue and build relationships with consumers.” They also said that Marketing

Communications perform many functions for consumers. Consumers can be told or shown

how and why a product is used, by what kind of person, and where and when; consumers

can learn about who makes the product and what the company and brand stand for; and

consumers can be given an incentive or reward for trial or usage. Marketing

Communications allow companies to link their brands to other people, places, events,

brands, experiences, feelings, and things. Marketing Communications can contribute to

brand equity by establishing the brand in memory and crafting a brand image.

Furthermore, Kotler and Keller in the book Marketing Management (2006, p.496)

also explained the six major modes of communication, which are:

1. Advertising

Advertising is any paid form of nonpersonal presentation and promotion of ideas, goods,

or services by an identified sponsor.

2. Sales Promotion

Sales Promotion is a variety of short-term incentives to encourage trial of purchase of a

product or service.

3. Events and Experiences

Events and Experiences are the company-sponsored activities and programs designed to

create daily or special brand-related interactions.

4. Public Relations and Publicity

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Public Relations and Publicity are a variety of programs designed to promote or protect a

company’s image or its individual products.

5. Direct Marketing

Direct Marketing is the use of mail, telephone, fax, e-mail, or Internet to communicate

directly with or solicit response or dialogue from specific customers and prospects.

6. Personal Selling

Personal Selling is a face-to-facet interaction with one r more prospective purchasers for

the purpose of making presentations, answering questions, and procuring orders.

2.1.3. Consumer Behavior

Schiffman and Kanuk (2007:3) defined consumer behavior as “the behavior that

consumers display in searching for, purchasing, using, evaluating, and disposing of products

and services that they expect will satisfy their needs. Consumer behavior focuses on how

individuals make decisions to spend their available resources (time, money, and effort) on

consumption-related items. That includes what they buy, why they buy it, when they buy it,

where they buy it, how often they buy it, how often they use it, how they evaluate that after

the purchase, the impact of such evaluations on future purchase, and how they dispose of it.”

The American Marketing Association (2005:5) defined 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. In other words, consumer behavior

involves the thoughts and feelings people experience and the actions they perform in

consumption process. It also includes all the things in the environment that influence these

thoughts, feelings, and actions. These include comments from other consumers,

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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. Consumer behavior is dynamic because the thinking,

feelings, and action of individual consumers, targeted consumer groups, and society at large

are constantly changing. Consumer behavior involves interactions among people’s thinking,

feelings, and actions, and the environment. Consumer behavior involves exchanges between

human beings, in other words people give up something of value to others and receive

something in return”.

2.1.4. Consumer Buying Behavior

Possibly the most challenging concept in marketing deals with understanding of

why buyers do what they do (or do not do).  But such knowledge is critical for marketers

since having a strong understanding of buyer behavior will help shed light on what is

important to the customer and also suggest the important influences on customer decision-

making.  Using this information, marketers can create marketing programs that they believe

will be of interest to customers.  As you might guess, factors affecting how customers make

decisions are extremely complex.  Buyer behavior is deeply rooted in psychology with

dashes of sociology thrown in just to make things more interesting.  Since every person in

the world is different, it is impossible to have simple rules that explain how buying

decisions are made.  But, those who have spent many years analyzing customer activity

have presented us with useful “guidelines” in how someone decides whether or not to make

a purchase.

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Customers make purchases in order to satisfy needs.  Some of these needs are

basic and must be filled by everyone on the planet (e.g., food, shelter) while others are not

required for basic survival and vary depending on the person.  It probably makes more sense

to classify needs that are not a necessity as wants or desires.  In fact, in many countries

where the standard of living is very high, a large portion of the population’s income is spent

on wants and desires rather than on basic needs

2.1.5. Buying Decision Process

This section describes the influential factors, which is affecting consumer buying

decision. The process of buying decision starts as soon as the consumer choosing and

buying product or service. If the customer feels dissatisfied, he or she will not do anything

and if feel satisfied, he/she will do decision about what they are desire to have. In buying

decision process, there are also some factors that influence decision. Buying decision is an

important study, which is related with marketing, because marketing is one of the very

essential studies in economics.

The importance of marketing theory enables every business organization to search

the real needs of customer and increase the interest of products and services in order to

stimulate sales. It requires knowledge of consumer behavior with the purpose to know the

characteristics of the people in the market to meet their needs, and make them satisfy.

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2.1.5.1. Stages of the Buying Decision Process

Kotler and Armstrong (2006:148) stated that consumer passes through five stages:

Figure 2.1. Stages of Buying Decision Process

Need Recognition

1. Need Recognition

The buying process starts with need recognition-the buyer recognizes a problem

or need. The need can be triggered by internal stimuli when one of the person’s normal

needs-hunger, thirst, sex-rises to a level high enough to become a drive. The need can also

be triggered by external stimuli. For example, an advertisement or a discussion with a friend

might get you thinking about buying a new car.

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Information Search

Evaluation of Alternatives

Purchase Decision

Postpurchase Behavior

2. Information Search

An interested consumer may or may not search for more information. If the

consumer’s drive is strong and satisfying product is near at hand, the consumer is likely to

buy it then. If not, the consumer may store the need in memory or undertake an information

search related to the need. For example, once a person decided need a new computer, at the

least, she will probably pay more attention to computer ads, computer owned by friends, and

computer conversations. Or she may actively look for reading material, phone friends, and

gather information in other ways. The amount of searching will depend on the strength of

her drive, the amount of information start with, the ease of obtaining more information, the

value she place on additional information and the satisfaction she gets from searching.

Consumer information source come from several sources:

a. Personal sources (family, friends, neighbors, acquaintances),

b. Commercial sources (advertising, sales people, dealers, packaging,

displays),

c. Public sources (mass media, consumer-rating organizations),

d. Experiential sources (handling, examining, using the product).

3. Evaluation of Alternatives

Alternative evaluation is how the consumer processes information to arrive at

brand choices. Unfortunately, consumers do not use a simple and single evaluation process

in all buying situations. Instead, several evaluation processes are at work. How consumers

go about evaluating purchase alternatives depends on the individual consumer and the

specific buying situation. Sometimes consumers make buying decisions on their own;

sometimes they turn to friends, consumer guides, or salespeople for buying advice.

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4. Purchase Decision

In the evaluation stage, the consumer ranks brands and forms purchase intentions.

Generally, the consumer’s purchase decision will be to buy the most preferred brand, but

two factors can come between the purchase intention and the purchase decision. The first

factor is the attitudes of others. If someone important to a person thinks that he should buy

the lowest-priced car, then the chances of his buying a more expensive car are reduced. The

second factor is unexpected situational factors. The consumer may form a purchase intention

based on factors such as expected income, expected price, and expected product benefits.

However, unexpected events may change the purchase intention. For example, the economy

might take a turn for the worse, a close competitor might drop its price, or a friend might

report being disappointed in one preferred car.

5. Post-purchase Behavior

After purchasing the product, the consumer will be satisfied or dissatisfied and

will engage in post-purchase behavior of interest to the marketer. What determines whether

the buyer is satisfied or dissatisfied with a purchase? The answer lies in the relationship

between the consumer’s expectations and the product’s perceived performance. If the

product falls short of expectations, the consumer is disappointed; if it meets expectations,

the consumer is satisfied; if it exceeds expectations, the consumer is delighted.

2.2. Previous Research

Beside some theories from the books, the researcher also obtained information

from previous researches that might support this thesis. The theories to build this thesis are

18

from the book, but, there is any possibility that a new theory might be revealed from the

previous researches.

In 2002, Loretta N. Satterwaite and John J. Haydu from University of Florida US,

conducted research in Florida about “Consumers Buying Habits of Environmental

Horticulture Products”. The researcher stated that the purpose of the study was to ascertain

the buying habits of consumers in Florida regarding environmental horticulture products.

To obtain the needed information, a garden center exit survey was conducted in 2002 under

the auspices of the Florida Nurseryman and Growers Association. The research results

were the category of convenience/location as the major reason for shopping at a particular

store. Other categories included price, quality, service, information, and other. Most

respondents were shopping for non-plant (hardgood) items, but when shopping for plants,

flowering plants for the outdoors ranked first.

The second journal is “The Impact of Consumer Package Communication on

Consumer Decision Making Process” by Vitalija Butkeviciene, Jugita Stravinskien, and

Ausra Rutelione. One of the findings stated that the traditional communication is now

inefficient. Companies prefer to use the modern communication that is more integrated. In

the traditional way, companies applied the communicating tools separately and it was

inefficient. Companies only focused in one communication tool, whereas there are many

other marketing tools. Based on this finding, the researcher becomes more convenience to

continue this thesis because there is a support from previous research about what the

researcher wants to examine in this thesis. But still, the researcher thinks that the journal

needs to be improved. That is why the researcher conducts this thesis, hopes that this thesis

will give some addition findings in marketing communication field.

19

Another research in China on 2005 about “Habitual Buying Pirated Software by

Chinese Consumer” was conducted by Fang Wang, Hongxia Zhang, Hengjia Zang, and

Ming Ouyang. The researcher established a research model by extending a model used by

Ang et al. in studying Singaporeans’ buying pirated CD. A survey was conducted.

Hypotheses were tested through stepwise regressions. An exploratory factor analysis was

carried out to analyze Chinese consumers’ attitude toward software piracy. The findings

were four personal and social factors found to be important in influencing Chinese

consumers’ attitude toward software piracy, including value consciousness, normality

susceptibility, novelty seeking, and collectivism. Five attitude measures, which were

important in influencing consumer purchase intention, were identified as reliability of

pirated software, recognized social benefits of piracy, functionality of pirated software,

risks of buying, and perceived legality of buying. An exploratory study identified three

attitude attributes.

2.3. Research Hypothesis

Research hypothesis in this research is:

1. Mass Communication modes influence the consumer decision in choosing mobile phone

providers in Manado simultaneously.

2. Mass Communication modes influence the consumer decision in choosing mobile phone

providers partially.

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2.4. Conceptual Framework

This research starts from the Mass Communication modes, which are advertising, sales

promotion, events, and public relation. This research is aimed to find out the influence of those

marketing communication modes to consumer’s decision partially or simultaneously.

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Advertising

Sales Promotions

Events

Public Relations

Consumer Decision

CHAPTER III

RESEARCH METHOD

This chapter explains about describe type and sources of data, this research

will be conducted with two sources of data: Primary data will obtain by direct questionnaire

that will distribute to employees and secondary data will gathered from some related books,

articles in magazines or news paper, internet, and all necessary sources from library.

Describe the population and sampling method, each research variable definition along with

the measurement, describes data analysis method used in the research process.

3.1 Data Sources and Data Collection Method

All the data in this research are from primary data and secondary data. The

primary data in this research derived from questionnaires that directly distributed and

collected by the researcher. While secondary data are information that has been collected for

some other purpose, the sources of secondary data can be external or internal sources

The research data will be collected through two main data collection method:

1. Primary Data

- Questionnaire

The data collected through questionnaires will be distributed to the respondents and

they have to read and fill the questionnaire directly.

- Face-to-face Interview

Face-to-face interview will be done to the restaurant management.

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2. Secondary Data

- Library research

The research will be by books or any literature that contains information about the

research and theories

- Internet browsing

Internet browsing regarding the research and theories of the research will ne used

3.2 Population and Sample

3.2.1. Population

Population refers to the entire group of people, events, or things of interest that

the researcher wishes to investigate (Sekaran, 2003:265). The population of this research is

the cellular phone users in Manado.

3.2.2 Sample

A sample is a subset of the population. It comprises some members selected from

it. In the other words, some, but not all, elements of the population would form the sample.

A sample is thus a subgroup of subset of the population (Sekaran, 2003:266). The sample of

this research is limited to 100 cellular phone users in Manado.

3.2.2.1 Sample Criteria

The respondents came from the users cellular phone service that provided by

cellular providers. All respondents use mobile phone, whether GSM or CDMA, or both

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GSM and CDMA. For age, gender, occupation, and income, researcher use random sample

to the cellular provider users in Manado.

3.3 Definition of Variables

3.3.1 Variable X

X1 = Advertising

X1 is the advertising (TV commercials, posters, flyers, billboard, etc) that companies use to

attract the consumer.

X2 = Sales Promotions

X2 is the Sales Promotions that companies use to attract consumers.

X3 = Events

X3 is Events that companies use to attract consumers.

X4 = Public Relations

X4 is Public Relations that companies use to attract consumers.

3.3.2 Variable Y

Y = Consumer Decision

It means that the decision is undertaken by consumer in regard to a potential market

transaction of a product or services.

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3.4. Variables Measurement

It is important for this research to use the scaling method, because by

implementing the scaling method it will ease the analysis of data. In the scaling method the

collected data will be converted into meaningful information therefore will be easier to

understanding the result. For this research, the researcher will use the Likert scale method

for decision making.

Malhotra (2002:284) defines the Likert Scale as “An Interval scale that

specifically uses the five response categories ranging from ‘strongly disagree’ to ‘strongly

agree’ which requires the respondents to indicate a degree of agreement or disagreement

with a series of statements related to the stimulus.” The Likert scale has been chosen to

consider that the data from decision making is based on the respondent’s experience and

attitude on Experiential Marketing and Customer Loyalty. By using the Likert Scale,

respondents will not have problems in understanding and filling out the questionnaire, and it

is easy for the researcher to measure, interpreting and analyze the data.

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In this kind of scale, variables will be measured on five points of scale (1, 2, 3, 4,

and 5) as shown below:

Table 3.1. Grading point of Decision Making

Statement Score

Strongly agree 5

Agree 4

Uncertain 3

Disagree 2

Strongly disagree 1

Source: Data Processed 2009

3.5. Data Analysis Method

3.5.1. Multiple Linear Regression Analysis

Linear regression is used to model the value of a dependent scale variable based

on its linear relationship to one or more predictors (SPSS help tutorial). The linear

regression model assumes that there is a linear, or "straight line," relationship between the

dependent variable and each predictor. Multiple linear regressions involves more than one

predictor variable (Xk).

Cooper and Schindler (2001, p.767) stated that multiple regression analysis is a

technique to observed value of more than one X to estimate or predict corresponding Y

value. Multiple regressions is a descriptive tool used to (1) develop a self-weighting

estimating equation by which to predict values for a dependent variable from the values of

independent variables, (2) control confounding variables to better evaluate the contribution

of other variables, or (3) test and explain a causal theory.

26

The formula of multiple regression models in this research is shown

below:

Where: Y = Consumers’ Decision of Choosing Telecommunication

Providers

a = The constant, when all the independent variable equal to

0

b1,b2,b3,b4 = The regression coefficient of each variable

x1,x2,x3,x4 = Mass Communication tools (Advertising, Sales

Promotions, Events, and Public Relations)

3.5.2 Steps of Multiple Regressions Analysis

There are also some steps of Multiple Regressions analysis. They are outline as follow

(Hair et al 1998):

1. Objective of Multiple Regressions

Select the objective, prediction, and explanation and then dependent and independent

variable.

2. Research Design of a Multiple Regression

Determine the sample size to ensure statistical power of the significance testing and the

generalizability of the result.

3. Assumption in Multiple Regression Analysis

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Y = a + b1x1 + b2x2 + b3x3 + + b4x4

Find out assumption of linearity, constant variance of the error terms, independence of

the error terms, and normality of term distribution.

4. Estimating the Regression Model and Assessing Overall Model Fit

In this stage, must accomplish three basic tasks: select a method for specifying the

regression model to be estimate, asses the statistical significance of the overall model in

predicting the dependent variable, and determine whether any of the observations exert

an undue influence on the result.

5. Interpreting the Regression Variety

Evaluate the prediction equation with the regression coefficient and then evaluate the

relative importance of the independent variables with the beta coefficients.

6. Validation of the Result

The final step is ensuring that it represents the general population and is appropriate for

the situation in which it will be use.

3.5.3 Testing of Classical Assumptions

According to Sulaiman (2004:87), a multiple linear regression model should meet

some basic assumptions as seen below:

3.5.3.1 Multicollinearily

Multicollinearity shows the intercorrelatioon of independent variables. R2’s near

1 violate the assumption of no perfect collinearity, while high R2 increases the standard

error of beta coefficient and makes assessment of the unique role of each independent

28

difficult or impossible. To asses multicollinearity, researchers can use tolerance or VIF,

which build in the regressing of each independent on all the others. Even when

multicollinarity is present, note that estimates of the importance of other variables in the

equation (variable which are not collinear with others) are not affected.

Tolerance is 1 – R2 for the regression of those independent variables on all the

other independents, ignoring the dependent. There will be as many tolerance coefficients as

there are independent. The higher the intercorrelation of the independents, the more the

tolerance will approach to zero. As a rule of thumb, if tolerance is less than .20, a problem

with multicollinearity is indicated.

Variance-inflation factor or VIF which is simply the reciprocal of tolerance.

Therefore, when VIF is high show multicollinearity and instability of the b and beta

coefficient. These two variables are provided in the SPSS output.

3.5.3.2 Heteroscedasticity

Newbolt, et.al (2003:508) explained that ‘Models in which the errors do not all

have the same variance are said to exhibit heteroscedasticity”. When this phenomenon is

present, the least square is not the most efficient procedure for estimating the coefficients of

the regression model. Moreover, the usual procedure for deriving confidence interval and

test of hypothesis for these coefficients are no longer valid. There are some tests for

detecting heteroscedasticity:

29

1. Sulaiman (2004:88) says that “Scatter plot is the residuals against an independent

variable. A model can be concluded not apparent of heteroscedasticity if the scatter plot

does not form any pattern.

2. Spearman correlation, highly recommended for a small samples model, is usually less

than 30 samples. A model is said to be infected by heteroscedasticity if the spearman

coefficient or correlation has significant value (Sig.<0.05) toward the residual.

3.5.3.3 Normality

In multiple linear regression models, the residual is assumed to be normally

distributed. A residual is the difference between the observed and model-predicted values of

the dependent variable. The residual for a given product is the observed value of the error

term for that product. A histogram or P-P plot of the residuals can help researchers to check

the assumption of normality of the error term. The requirements are as follows:

1. The shape of the histogram should approximately follow the shape of the normal

curve

2. The P-P plotted residuals should follow the 45-degree line.

3.5.3.4 Autocorrelation

Autocorrelation is the correlation between some observed data that is organized

based on time series or data in a certain time or is cross-sectional. It is attempt to test is there

any correlation between errors in t period and t-1 period in a linear regression model.

Autocorrelation appears because if there continues observation in a time series, this problem

30

emerges of the residual from one observation tp another. Autocorrelation could be identified

by computing the critical value of Durbin-Watson Statistic (d-test).

3.5.4. Testing the Goodness of Fit

3.5.4.1 Multiple Coefficient Correlation (R)

Correlation can be measured by means of the correlation coefficient, usually

represented by letter R. It indicates the relationship between all independent variables (X)

with dependent variable (Y). The coefficient is

- Zero if there is no relationship between two variables;

- 1.0 if there is a perfect positive correlation between variables (they increase

together);

- -1.0 if there is perfect negative correlation between variables (one increases

and the others decreases);

- Between 0 and 1.0 if there is some positive correlation;

- Between 0 and –1.0 if there is some negative correlation.

According to Ticehurst (2000), the closer the coefficient is to 1.0, the greater the

correlation. Multiple coefficient correlation for two predictors’ equation is formulated as:

1X1Y + 2X2Y + 3X3Y + ……….. + nXnY

RY =

Y2

31

3.5.4.2 Coefficient of Determination (R2)

Coefficient of determination (R2) is the amount of common variance in X and Y,

two variables in associations. In predicting the values of Y without any knowledge of X, the

best estimate would be Y (Cooper and Schindler, 2001). It measures how far the ability of a

model in explaining variation of dependent variable. The value of coefficient of

determination is between 0 and 1.

After R is found, the R2 can be determined. The result of R2 is the contribution

percentage of influencing factors to the dependent variable (Sumodiningrat, 1999). SPSS

(Statistical Package for Social Science) software version 13.0 will be used in this research.

3.5.5 Coefficient of Determination

According to Newbolt, et.al (2003:385), “this R2 provides a descriptive measure

of the proportion or percent of the total variability that is explained by the regression model.

Besides that, it is often interpreted as the percent of variability in Y that is explained by the

regression equation”. In addition Newbolt, et.al (2003:430) says that. “The Coefficient of

determination (R2) routinely is used as a descriptive statistic to describe the strength of the

linear relationship between the independent variables and the dependent variables”.

3.5.6 Hypothesis Testing

In order to test the hypothesis, a statistical analysis such as F test and Ttest need to be

calculated. The Ftest and Ttest will be useful in a situation when the researchers need to find

32

out the relationship between dependent and independent variables. When Ftest and Ttest are

given and compared to the Ftable and Ttable, the hypothesis could be examined.

3.5.6.1 Ftest

An Ftest as any statistical test in which the test statistical has an F-distribution if the

null hypothesis is true. The Ftest is used to determine the whole effect of all independent

variables to a dependent variable. This test done by comparing the Fvalue with Ftable . If Fvalue is

greater than Ftable . Ho is rejected and H1 is accepted the value off is done by formula:

Then calculate F as

F =( RSS 1−RSS 2

p2−p 1 )( RSS 2

n−p 2 )

Where,

RSSi = residual sum of squares of model i

(p2 –p1, n – p2) = degrees of freedom

The null hypothesis, that none of the additional p2 – p1 parameters differs from

zero, is rejected if the calculated F is greater than the F given by the critical value of F for

some desired rejection probability (e.g. 0.05).

3.5.6.2 Ttest

A Ttest is any statistical hypothesis test in which the test statistical has a t

distribution if the null hypothesis is true. The Ttest is used to determine the effect of each

33

independent variable to dependent variable individually, considering the other variables

remain constant.

This test is done by comparing the tvalue with ttable. The level of significance is

5% (α = 0.05). If tvalue is greater than t table H0 is rejected and H1 is accepted. The value of t

is done by formula:

t = b j – β j

Sbj

Where,

bj = jth variable coefficient

βj = jth parameter

Sbj = jth standard deviation

34

CHAPTER IV

RESULT AND DISCUSSION

4.1 Result

4.1.1. Characteristics of Respondent

The respondents of this research were cellular phone users, whether GSM or

CDMA, and not specified to any certain telecommunication providers. The respondents are

classified into gender, occupation, income, and gender.

4.1.1.1. Gender

Figure 4.1 Classification of Respondents based on Gender

Male47%

Female53%

Source: data processed 2010

35

The characteristic of respondents based on age is shown in figure 4.1. It shows

that 53% of the respondents are female and the rest 47% are male.

4.1.1.2. Occupation

Figure 4.2. Classification of Respondents Based on Occupation

56%

16%

16%

4% 8%

Student/College StudentTeacher/LecturerEmployeeEntrepreneurOther

Source: data processed 2010

The characteristic of respondents based on occupation is shown in figure 4.2. the

respondents are divided into 5 kinds of occupation. The highest percentage of the

respondents comes from students/college students, which is 56%. The second highest comes

from teachers/lecturers and employees, 16% both. The third highest comes from other

occupations that are not classified, such as housewife and unemployment, which is 8%. And

the least comes from entrepreneur, which is 4%.

36

4.1.1.3. Age

Figure 4.3. Classification of Respondents Based on Age

36%

40%

4%

17%3%

15 - 20 years old21 - 25 years old26 - 30 years old31 - 35 years old≥ 36 years old

Source: data processed 2010

From the chart above, we can see that the most respondents are between 21 – 25

years old, which is 40%, then, followed by the respondents who are between 15 – 20 years

old. Respondents who are between 31 – 35 years old are 17%, followed by respondents who

are between 26 – 30 years old (4%), and respondents above 36 years old (3%).

37

4.1.1.4. Income

Figure 4.4. Classification of Respondents Based on Income per Month

48%

24%

20%8%

Rp. 0 - Rp. 1.000.000Rp. 1.000.001 - Rp. 2.000.000Rp. 2.000.001 - Rp. 3.000.000 ≥ Rp. 3.000.001

Source: data processed 2010

The characteristic of respondents based on income per month is clearly shown in

figure 4.4. The respondents are divided into four classes. It shows that the highest

percentage 48% derived from income below Rp. 1.000.000; followed by income Rp.

1.000.001 – Rp. 2.000.000, which is 24%; Income Rp. 2.000.001 – Rp. 3.000.000 with 20%,

and the lowest percentage of respondents comes from income ≥ Rp. 3.000.000 which is only

8%.

38

4.1.2 Data Analysis

In order to analyze the influence of mass communication modes on consumers’

decision of telecommunication providers, the writer was using the multiple linear regression

analysis. To apply the regression procedure, Consumer Decision as the dependent variable is

selected and the independent variable are the elements of Mass Communication Modes,

which are advertising, sales promotion, events, and public relation. Multiple linear

regression model is used to determine the effect of several independent variables on a

dependent variable. The model of this research is:

Y = b0 + b1x1 + b2x2 + b3x3 + b4x4+ e

Where,

Y = Consumer Decision

x1 = Advertising

x2 = Sales Promotion

x3 = Events

x4 = Public Relation

b0, b1, b2, b3, b4 = Regression coefficient of each variable

e = Random error

39

This analysis was calculated by using the SPSS (Statistical Package for Social

Science) software. With the computerized calculation, it can ensure the accuracy of the

analysis.

4.1.3 Result of Classical Assumption

4.1.3.1 Multicollinearity

Table 4.1 Multicollinearity Test

Coefficients(a)

Model Collinearity Statistics

Tolerance VIF1 (Constant) Advertising .670 1.492 Sales_Promotion .522 1.915 Events .545 1.834 Public_Relations .353 2.833

a Dependent Variable: Consumer_Decision

Source: data processed 2010

The model concluded to be free from multicollinearity if the tolerance value is

more than 0.2 and VIF value is less than 10. Table 4.1. shows that the tolerance value for

Advertising is 0.670, Sales Promotion is 0.522, Events is 0.545, and Public Relation is 0.353.

It also shows that the VIF value for Advertising is 1.492, Sales Promotion is 1.915, Events is

1.834, and Public Relation is 2.833. Since all tolerance value is more than 0.2 and VIF value

is less than 10, then the model is concluded that it is free from multicollinearity.

40

4.1.3.2 Heteroscedasticity

In figure 4.5 were shown the result of heteroscedasticity test.

Figure 4.5 Heteroscedasticity Test Output

Source: Data processed, 2009

Figure 4.5 is Scatterplot graphic that is used to test the heteroscedasticity. It shows

that the pattern of the dots is spreading and does not create a clear pattern, and the dots are

spreading above and below 0 (zero) in the Y axis. Thus, this proves that the model is free

41

from heteroscedasticity, so the model can be used to predict the Consumers’ Decision based

on the independent variables Advertising, Sales Promotion, Events, and Public Relation.

4.1.3.3 Normality

To identify the normality test, figure 4.6 will shows the graphic results for the

normality test.

Figure 4.6 Normality Test Output

1.00.80.60.40.20.0

Observed Cum Prob

1.0

0.8

0.6

0.4

0.2

0.0

Expecte

d C

um

Pro

b

Normal P-P Plot of Regression Standardized Residual

Dependent Variable: Consumer_Decision

Source: data processed 2010

42

Figure 4.6 shows that the data that is represented by dots are spreading near the

diagonal line and spreading follows the direction of the diagonal line. This proves that the

model has passed the Normality Test.

4.1.3.4 Autocorrelation

Table 4.2 shows the result of the Autocorrelation Test.

Table 4.2 Autocorrelation Test Output

Model Summary(b)

Model Durbin-Watson

1 2.012

a Predictors: (Constant), Public_Relations, Advertising, Events, Sales_Promotionb Dependent Variable: Consumer_Decision

Source: data processed 2010

Table 4.2 shows that the critical value is 2.012, which means the model is free

from autocorrelation. For more explanation see table 4.3.

Table 4.3 Critical Values of the Durbin-Watson Test Statistic

43

Source: Data Processed, 2010

This research used a = 0.05 to identify the autocorrealation which could be

examined in table 4.4. From Table 4.4 shows that the critical value of Durbin-Watson are

2.012 which in the area No Autocorrelation, concludes that the model is free from

autocorrelation.

4.1.4. Coefficient of Determination

Table 4.4 Coefficient of Determination

Model Summary(b)

Model R

R Square

Adjusted R Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square Change

F Change df1 df2

Sig. F Change

1 .939(a) .882 .877 .23461 .882 178.098 4 95 .000 2.012

a Predictors: (Constant), Public_Relations, Advertising, Events, Sales_Promotionb Dependent Variable: Consumer_Decision

The coefficient of determination is identified by R2 = 0.882 which is a correlation

coefficient quadrate (0.939)2 = 0.882. R square is usually called coefficient of determination

which is 0.882 or 88.4% which means Consumers’ Decision (Y) is able to be explained by

Advetising, Sales Promotion, Events, and Public Relation, and the rest 11.8% are caused by

other factors.

4.1.5. Result of Multiple Linear Regression Analysis

44

The interpretation of Multiple Linear Regression Analysis will be shows at table 4.5.

Table 4.5 The Multiple Linear Regression Analysis Output

Coefficients(a)

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

95% Confidence Interval for B Correlations

Collinearity Statistics

BStd.

Error BetaLower Bound

Upper Bound

Zero-order Partial Part

Tolerance VIF

1 (Constant) -.037 .194 -.192 .848 -.422 .347

Advertising .159 .052 .131 3.039 .003 .055 .263 .562 .298 .107 .670 1.492Sales_Promotion

.378 .040 .458 9.413 .000 .298 .458 .839 .695 .331 .522 1.915

Events .244 .047 .248 5.207 .000 .151 .337 .742 .471 .183 .545 1.834Public_Relations

.232 .048 .288 4.855 .000 .137 .327 .835 .446 .171 .353 2.833

a Dependent Variable: Consumer_Decision

Source: data processed 2010

The multiple linear regression models is used to determine the effect of several

independent variables on a dependent variable. The calculation was done by using the SPSS

14.0. software. The computerized calculation ensures the accuracy of the analysis. The

analysis output is described in table 4.5. From the result in table 4.5., the model is defined

as:

Y = -0.037 + 0.159 X1 + 0.378 X2 + 0.244 X3 + 0.232 X4

Where:

45

Y = Consumers’ Decision

X1 = Advertising

X2 = Sales Promotion

X3 = Events

X4 = Public Relation

Constant (α) -0.037 means that if all of the independent variables equal to zero, then the

Consumers’ Decision will decrease as much as 0.037 points.

If the others are constant or equal to zero, an increase of one point in Advertising (X 1)

will result in an average increase of at least 0.159 in Consumers’ Decision (Y).

If the others are constant or equal to zero, an increase of one point in Sales Promotion

(X2) will result in an average increase of at least 0.378 in Consumers’ Decision (Y).

If the others are constant or equal to zero, an increase of one point in Events (X 3) will

result in an average increase of at least 0.244 in Consumers’ Decision (Y).

If the others are constant or equal to zero, an increase of one point in Public Relation (X4)

will result in an average increase of at least 0.232 in Customer Loyalty (Y).

4.1.6. Hypothesis Testing

This research shows the influence of Mass Communication Modes (Advertising,

Sales Promotion, Events, and Public Relation) on Consumers’ Decision as the dependent

variable partially and simultaneously. The F-test was used to determine the simultaneous

46

effect, while the T-test was used to determine the partial effect of each independent variable

on the dependent variable.

4.1.6.1 F-Test

The simultaneously F-test was conducted to identify whether the independent

variables which consist of Advertising (X1), Sales Promotion (X2), Events (X3), and Public

Relation (X4) have any relationship with Consumers’ Decision (Y) simultaneously. Table

4.6 describes the F-test result.

Table 4.6 Simultaneously Test (F-Test) Output

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression 39.211 4 9.803 178.098 .000(a)

Residual 5.229 95 .055Total 44.440 99

a Predictors: (Constant), Public_Relations, Advertising, Events, Sales_Promotionb Dependent Variable: Consumer_Decision

Source: data processed 2010

H0: β1=β2=β3=β4=0 (Advertising (X1), Sales Promotion (X2), Events (X3), and Public Relation

(X4) have no influences on Consumers’ Decision (Y) simultaneously).

Ha: β1=β2=β3=β4≠0 (Advertising (X1), Sales Promotion (X2), Events (X3), and Public Relation

(X4) have any influences on Consumers’ Decision (Y) simultaneously).

If:

Fvalue > Ftable Reject H0

47

Fvalue < Ftable Accept H0

By using the level of significance of 0.05 (α = 0.05) and degree of freedom (df) =

5; found:

178.098 > 2.31

Since the Fvalue is greater than Ftable, H0 rejected and Ha is accepted, which means

Advertising (X1), Sales Promotion (X2), Events (X3), and Public Relation (X4) have any

influences on Consumers’ Decision (Y) simultaneously.

4.1.6.2 T-Test

The partial test (t-test) was conducted to identify the relation between the

independent variables and dependent variable partially or individually. In conducting the T-

Test will be used table 4.7.

Table 4.7 Partial Test (T-Test)

Coefficients(a)

Model Unstandardized

CoefficientsStandardized Coefficients t Sig.

B Std. Error Beta 1 (Constant) -.037 .194 -.192 .848 Advertising .159 .052 .131 3.039 .003 Sales_Promotion .378 .040 .458 9.413 .000 Events .244 .047 .248 5.207 .000 Public_Relations .232 .048 .288 4.855 .000

a Dependent Variable: Consumer_Decision

Source: data processed 2010

48

From table 4.7 found the tvalue for each independent variable, which for

Advertising (X1) tvalue = 3.039 and ttable = 1,984 which tvalue > ttable = 3.039 > 1,980. Therefore,

H0 is rejected and Ha is accepted, which means Advertising is significantly influence

Consumers’ Decision. The analysis shows that generally the amount of Advertising will

improve or even decrease Consumers’ Decision.

For Sales Promotion (X2) the tvalue = 9.413 with the same α, ttable = 1,984 which tvalue

> ttable = 9.413 > 1,984. Therefore, Ho is rejected and Ha is accepted which means Sales

Promotion is significantly influence Consumers’ Decision. The result showed that in general

the amount of Sales Promotion would improve or decrease individual Consumers’ Decision.

For Events (X3) the tvalue = 5.207 with the same α, ttable = 1.984 which tvalue > ttable =

5.207 > 1.984. Therefore, Ho is rejected and Ha is accepted which means Events

significantly influence Consumers’ Decision. The result showed that in general the amount

of Events would improve or decrease individual Consumers’ Decision.

For Public Relation (X4) the tvalue = 4.855 with the same α, ttable = 1,984 which tvalue

> ttable = 4.855 > 1,984. Therefore, Ho is rejected and Ha is accepted which means Public

Relation significantly influence Consumers’ Decision. The result showed that in general the

amount of Public Relation would improve or decrease individual Consumers’ Decision.

Based on the hypothesis testing by F-test and t-test, the result has proven that

there is linear relationship between variables partially and simultaneously.

49

4.2 Discussion

From the analysis that has been conducted by using the Multiple Linear

Regression Analysis it found that:

Y = -0.037 + 0.159 X1 + 0.378 X2 + 0.244 X3 + 0.232 X4

The result shows that Mass Communication Modes (Advertising, Sales

Promotion, Events, and Public Relation) have significant influence toward Consumers’

Decision. This result is understandable because all of those are the important things in

marketing. The result shows that three out of four variables (Sales Promotion, Events, and

Public Relation) are very significant influencing the Consumers’ Decision. They are shown

by the levels of significance that are 0.000 each.

Based on the hypothesis testing by F-test and T-test, the result has proven that

there is linear relationship or have influence between variables partially and simultaneously.

The result of this research shows that among four mass communication modes,

advertising is not too significant compared to the other four modes. It is because that the

way of communication between producers and consumers are changing. In the advertising,

consumers are not involved. But, in sales promotion, event, and public relation, consumers

are directly get the advantages.

Advertising is a communication tool to introduce a product to consumers. This is

the most common tool for companies to introduce their products to consumers because it is

50

simple. Forms of advertising are printed media, such as billboard, newspapers or magazine

ads, flyers, brochures, etc, and electronic media, such as TV / radio commercials, spams,

pop-up advertisements, etc. By advertisements, consumers only get the information without

knowing further. Consumers can only read or listen to the message of the information. In

order to make consumers interested to watch or read the information, marketers have to

attract consumers by making the advertisement enjoyable to watch or read and also

memorable. For example, in every advertisement, every telecommunication providers use

certain colors to make consumers easy to remember. Telkomsel with red, Indosat with

yellow, Esia with green, Fren with blue, etc. This mode influences consumers to decide

what they want based on the information of the advertisements.

Sales promotion is a way of companies to encourage consumers to purchase their

products. The common form of sales promotion is bonus. Telecommunications providers are

often give discounts for their products. For example, Telkomsel gives free credit in every

credit recharges at least Rp. 20,000 on its latest product, simpatimax. TelkomFlexi gives

tariff discount for every phone call during 12 a.m. - 6 a.m. become Rp. 300. Indosat gives

the cheapest tariff for internet connection. XL gives free text messaging everyday. These

promotions make consumers more attracted to use certain product because the promotions

give many benefits to the consumers.

Event is program that is held or sponsored by a company to increase the

awareness to the consumers. Through events, companies communicate with consumers

directly. A company makes an event, consumers attend that event, and then the sales

promotion boys or girls explain the advantage of the product directly to the consumers. In

the event, consumers can interact with the representatives of the company about the product.

51

The most common example of event is exhibition. Telecommunication providers use this

way to communicate directly to the consumers. We usually see this in public places like

malls and supermarkets. Events also have non-profit purposes. CSR (Company Social

Responsibility) is a form of event that is not purposed for making profits. This is a form of

events that the company must do as a payback for society. For example, TelkomFlexi made

band festival for high school in order to find some potential band from high school so that

their talents will not be hidden.

Public relation involves a variety of programs designed to promote company’s

image. Public relation is the front liner of a company in the market. They are responsible of

a company’s image. Public relation officers have to mix to the consumers to know what

consumers want and then bring it back to the company. Public relation officers are also

responsible to build the image of the company.

52

CHAPTER V

CONCLUSIONS AND RECOMMENDATIONS

In this chapter, there are some conclusions of the research and recommendations

that can be useful.

5.1 Conclusion

The conclusions drawn from this research are as follows:

1. The result based on data processing using Multiple Regression Equation Model,

shows that all independent variables have positive and strong relationship with

Consumers’ Decision as the dependent variable.

2. It can be seen that Sales Promotion is the most influencing factors with the coefficient

0.378, means that every additional of 1 unit in Sales Promotion adds as much as 0.378

points to Consumers’ Decision. It is because the consumers are more attracted by the

bonuses and discounts that given by the providers. They tend to choose the providers

that give interesting offers in discounts or bonuses.

3. The second most influencing factor is Events with the coefficient 0.244, means that

every additional of 1 unit in Events adds as much as 0.244 points to Consumers’

53

Decision. It can be explained that people’s tendency to buy the product is high when

there is an event in public places like malls and supermarkets.

4. The third most influencing factor is Public Relation with the coefficient 0.232, means

that every additional of 1 unit in Public Relation adds as much as 0.232 points to

Consumers’ Decision. Public relation in a company is very important to build

communication between the company and the customers. As we know that cellular

phone is still a complicated thing that sometimes cannot be fixed by the users even

for small problem. So, the users tend to call the public relation of the providers to ask

some help if they have problem with their service providers.

5. The least influencing factor is Advertising with the coefficient 0.159, means that

every additional of 1 unit in Advertising adds as much as 0.159 points to Consumers’

Decision. Advertising is the most common tool that company use to introduce their

products. But, advertising is only one way communication, which is only from

company to the consumers, while sometimes consumers need explanation directly

from the representatives of the company that advertising cannot do.

54

5.2 Recommendations

Based on the conclusions above, herewith are the recommendations to telecommunication

providers.

1. The marketing communication now has shifted to the more modern way, which is

integrated marketing communication. This method is more effective to attract

consumers than the traditional way of marketing communication. So, for companies,

especially growing companies, should use this new way of marketing communication

in order to attract more consumers and of course, get profit as much as they can.

2. Telecommunication providers should consider the mass communication modes in

order to attract consumers because the modes, which are advertising, sales promotion,

events, and public relation have strong relationship to the consumers decision (proved

by the significant level that are all 0.000). It means that the mass communication

modes (advertising, sales promotion, events, and public relation) have strong

contribution in attracting consumers to buy the products.

3. According to the result, Sales Promotion has the highest influence on consumer’s

decision among the other factors, the telecommunication providers have to maintain

the discounts and bonuses given without reduce the quality of the service. However,

providers have to consider the other factors also in order to attract consumers and get

consumers as many as they can.

55

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http://www.empower.com/pages/services_demo.htm

http://www.answers.com/marketing?cat=biz-fin

http://en.wikipedia.org/wiki/Marketing_mix

http://www.answers.com/multiple%20regression

www.emeraldinsight.com http://www.researchand markets.com/reportinfo.asp?report_id=58402&te&cat_id

en.wikipedia.org/simplelinearregression

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A P P E N D I C E S

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APPENDIX 1

Regression Output

Descriptive Statistics

Mean Std. Deviation NConsumer_Decision 3.9100 .66999 100Advertising 3.8900 .55059 100Sales_Promotion 3.9867 .81225 100Events 3.8800 .68251 100Public_Relations 3.7733 .82997 100

Correlations

Consumer_D

ecisionAdvertisin

gSales_Promo

tion EventsPublic_Relati

onsPearson Correlation

Consumer_Decision 1.000 .562 .839 .742 .835Advertising .562 1.000 .373 .383 .574

Sales_Promotion .839 .373 1.000 .556 .675

Events .742 .383 .556 1.000 .657

Public_Relations .835 .574 .675 .657 1.000

Sig. (1-tailed) Consumer_Decision . .000 .000 .000 .000

Advertising .000 . .000 .000 .000

Sales_Promotion .000 .000 . .000 .000

Events .000 .000 .000 . .000

Public_Relations .000 .000 .000 .000 .

N Consumer_Decision 100 100 100 100 100

Advertising 100 100 100 100 100Sales_Promotion 100 100 100 100 100

Events 100 100 100 100 100

Public_Relations 100 100 100 100 100

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Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 Public_Relations, Advertising, Events, Sales_Promotion(a)

. Enter

a All requested variables entered.b Dependent Variable: Consumer_Decision

Model Summary(b)

Model R

R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square Chang

eF

Change df1 df2Sig. F

Change1

.939(a) .882 .877 .23461 .882178.09

84 95 .000 2.012

a Predictors: (Constant), Public_Relations, Advertising, Events, Sales_Promotionb Dependent Variable: Consumer_Decision

ANOVA(b)

Model Sum of

Squares df Mean Square F Sig.1 Regression 39.211 4 9.803 178.098 .000(a)

Residual 5.229 95 .055Total 44.440 99

a Predictors: (Constant), Public_Relations, Advertising, Events, Sales_Promotionb Dependent Variable: Consumer_Decision

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Coefficient Correlations(a)

Model Public_Relation

s Advertising EventsSales_Promoti

on1 Correlations Public_Relations 1.000 -.423 -.410 -.458

Advertising -.423 1.000 -.014 .025Events -.410 -.014 1.000 -.203Sales_Promotion -.458 .025 -.203 1.000

Covariances Public_Relations .002 -.001 -.001 -.001

Advertising -.001 .003 -3.54E-005 5.35E-005Events -.001 -3.54E-005 .002 .000Sales_Promotion -.001 5.35E-005 .000 .002

a Dependent Variable: Consumer_Decision

Collinearity Diagnostics(a)

Model Dimension EigenvalueCondition

Index

Variance Proportions

(Constant) AdvertisingSales_Promot

ion EventsPublic_Relati

ons1 1 4.936 1.000 .00 .00 .00 .00 .00

2 .028 13.359 .21 .07 .15 .00 .143 .016 17.718 .07 .09 .67 .01 .314 .014 18.647 .00 .17 .09 .81 .055 .007 26.905 .72 .66 .09 .18 .50

a Dependent Variable: Consumer_Decision

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value 2.4526 4.6285 3.9100 .62934 100Residual -.51215 .48991 .00000 .22982 100Std. Predicted Value -2.316 1.142 .000 1.000 100Std. Residual -2.183 2.088 .000 .980 100

a Dependent Variable: Consumer_Decision

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APPENDIX 2

Charts Output

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