CHAPTER I
INTRODUCTION
1.1. Research Background and Motivation
Nowadays, language, especially English, is being recognized as a key to connect
to the world. All over the world, there are more and more language centers occurred and
it is going to be more competitive. Specifically, in Vietnam, as entered into WTO, there
are more foreign enterprises have invested into the market. That’s a challenge for
Vietnamese to speak English and also is a chance for language center. However, to build
up the new company need a long process and the first thing is making a plan with
location decision and make a target segment. Because a company cannot meet the whole
market needs. Every successful business has good strategies and campaigns. It is even
required to survive. It’s hard to a new company can stand steadily in the competitive
environment. With the development of global economy, the business competition is
becoming more and more fiercely. Enterprises should carry out the target segmentation
from which they can benefit most and in which their companies can be the most
competitive.
Market segmentation is important in order for a company’s marketing strategy to
work properly (Weinstein 1994, Gunter & Furnham 1992). It is necessary for companies
to understand the consumer segment that they are focusing on regarding factors as age,
values, purchase behavior, attitudes and so forth, in order to become successful (Gunter
& Furnham 1992). Kotler (2003) categorized market segmentation into four main
variables as the figure below
Market segmentation
Geographic
Demographic
Psychographic
Figure1.1 Market Segmentation (Kotler 2003)
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Behavioral
Fuzzy Multiple Criteria Decision Making (MCDM) was used as a model to
evaluate the most effective location, such a framework provides a natural way of dealing
with problem (Zadeh, 1965). The theory of fuzzy logic, unlike statistics (where
uncertainty is modeled with randomness), represents imprecision by the fact that certain
objects (or certain classes of objects) have poorly or ill-defined boundaries (Prodanovic,
2001). It is supposed that “not all uncertainties easily fit the probabilistic classification”
(Bender & Simonovic, 2000). So, fuzzy logic is not a direct competitor to statistics.
A numerical example is used to test the model in this study. Fuzzy system theory
has been developed steadily and has significance for decision making in engineering,
economics and social system. For an English learning center in start-up time, a lot of
things need to make decision such as strategy or plan. Fuzzy MCDM is the suitable
model to apply. This study used qualitative criteria, such as substantiality, accessibility or
actionability and quantitative criteria as measurability and cost. Fuzzy model helped
solving decision making problems with more than one criterion. The “α–cuts” and
arithmetic operations of fuzzy number were used to evaluate the membership functions.
The final evaluation values from the fuzzy MCDM model are still fuzzy numbers. So, the
defuzzication method is applied to rank all the final fuzzy evaluation value of decision
makings and it showed the feasibility of the proposed method.
1.2. Research Description
It is important for the business to develop the potential needs and adjust the
strategy in time. By doing segment of demand of market, companies can equip the best to
handle the market. It is about the concentration of the company to their target to get the
highest effectiveness. Theoretically, it is “market segmentation” and each company
should have their target. Selecting English center location is a part of this process. In
segmenting market, it is similar to demographic variable. It might be country, state, city,
neighborhood or population size, population density and climate. The company can
decide to do business in one or more geographic location. Companies localize their
products and marketing strategy to fit the needs of each location. This research based on
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some criteria that found out from researchers as Kotler (2003), Wedel and Kamamura
(2000), Biggadike (1981) and Morrit (2007). These criteria showed as below:
Accessibility
Qualitative
Criteria
Stability
Actionability
Substantiality
Competitiveness
Profitability
Benefit
Number of
employees
Quantitative
Criteria
Growth Rates
Cost
Cost
Length of time
to set up
Figure 1.2 Qualitative Criteria and Quantitative Criteria
The ranking method of fuzzy numbers was first introduced by Jain (1976).
Ranking method is an important procedure in fuzzy decision making problems, which is
a defuzzication process to transform fuzzy numbers to crisp values for effective decision
making. Some recent works can be found in Rao and Shankar (2013), Rezvani (2013),
Sharma (2015).
Among the ranking approaches, the maximizing set and minimizing ser method
proposed by Chen (1985) is a commonly used approach that is highly cited an has wide
applications. It is not too complex and difficult to implement the connection between the
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ranking procedure and the final fuzzy value evaluations. A numerical example justifies
the merits of the proposed ranking method to decision making procedure.
The research structure will be (1) problem definition, (2) research design, (3)
giving a data base on numerical examples and researches, (4) analysis, (5) explain the
data and (6) conclude results.
It is important for the business to develop the potential needs and adjust the
strategy in time. By doing segment of demand of market, companies can equip the best to
handle the market.
1.3. Research Objectives

Adapting fuzzy MCDM as a model to execute this study, the first objective is to
extend the effect of this model, especially in location evaluation and selection.

To establish a fuzzy multiple criteria decision making model that is suitable to
evaluate and select the right location to build up a productive English center.

By conducting a numerical example, it might show the feasibility of the
proposed method.
1.4. Research Framework

This study is divided into six chapters with introduction, literature review, fuzzy
set theory, model establishment, numerical example and conclusions.
 The chapter one included background and motivation, description as well
limitations of the research and objectives.
 Chapter two is about the literature review about market segmentation, market
segment criteria, the process of doing segmenting and theory of fuzzy multiple
criteria decision making (MCDM) approach.
 Chapter three shows some basics on fuzzy set theory.
 The process of model establishment is presented in Chapter four.
 And then, the numerical example is applied to explain the feasibility of the
proposed model.
 Finally, Chapter six is the conclusions and discussions
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Chapter I
Introduction
Chapter II
Literature Review
Chapter III
Fuzzy Set Theory
Chapter IV
Model Establishment
Chapter V
Numerical Example
Chapter VI
Conclusions
Figure 1.3 Framework
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