The factors affecting on apartment purchase decision on customers in ho chi minh city

The main purpose of the study is to investigate the effecting of key factors on housing purchase decision of customers in Ho Chi Minh City with focus on condominiums in new urban areas,

RESEARCH PROJECT

(BMBR5103)

THE FATORS AFFECTING ON

APARTMENT PURCHASE DECISION OF CUSTOMERS IN HO CHI MINH CITY

Page 2

Advisor’s assessment

Advisor’s signature

ACKNOWLEDGEMENTS

I would like to express my most sincere gratitude to Assoc Prof Phan Nguyen I

am deeply indebted for his guidance, patience, valuable comments and suggestions which greatly helped me in the completion of this dissertation

I also would like to thank you all my colleagues and friends of HUTECH class for their valuable contributions to give comments and suggestion to revise the questionnaire survey

Warmly thanks to my classmates, friends and all anonymous participants, and especially my family for their supports and inspiring me to complete the MBA course

December 2015

Pham Phu Phong

ABSTRACT

The issue of housing preference has been widely researched in housing literature, because it provides valuable information for the planning and development of housing for various residential groups with different needs In Vietnam, the issue has not received proper attention from scholars and developers though the local housing market is going through a phase of rapid development and transformation The main purpose of the study is to investigate the effecting of key factors on housing purchase decision of customers in Ho Chi Minh City with focus on condominiums in new urban areas, due to strong demand of the residential group for the specific type of housing

The thesis employed a stated-preference approach with application of direct measurement and conjoint analysis methods to answer research question A total of

400 responses were collected by mean of questionnaires delivered to customers The study finds out a strong positive relationship between top two factors, including

“living space”, “distance” and customers’ housing purchase decision The three weaker positive relationship factors are “feature”, “finance” and “environment” to housing decision makers It is also found that there is no difference in decision making of customers according to different demographics consisting of gender, age, marital status, monthly income and education level

Analysis of the empirical data shows that, households are most concerned about developers’ commitments and basic quality of the housing units They appreciate child-friendly qualities of the living environment, as well as child-friendly facilities and services, large space, etc The preferences are then discussed in connection to current conditions of Ho Chi Minh City urban areas in order to give implications for

urban planning policies and new housing projects

Key works: housing, purchase factors, Ho Chi Minh City in Vietnam

CONTENTS

ACKNOWLEDGEMENTS

ABSTRACT

LIST OF TABLE

LIST OF FIGURE

LIST OF ABBREVIATIONS

CHAPTER 1 INTRODUCTION 1

1.1 BACKGROUND 1

1.2 RESEARCH OBJECTIVES 2

1.3 RESEARCH QUESTIONS 2

1.4 OBJECT OF STUDY 3

1.5 SCOPE OF STUDY 3

1.6 METHODOLOGY 4

CHAPTER 2 LITERATURE REVIEW 5

2.1 INTRODUCTION 5

2.2 APARTMENT MARKET IN VIETNAM OVERVIEW 5

2.3 FORECASTS APARTMENTS MARKET IN 2015 - 2016 10

2.4 BEHAVIOUR IN PURCHASE DECISION OF CUSTOMER 12

2.5 THE FACTORS IMPACT ON PURCHASE DECISION APARTMENT OF CUSTOMER 16

CHAPTER 3: RESEARCH METHODOLOGY 20

3.1 RESEARCH DESIGN 20

3.2 SAMPLE SIZE 21

3.3 RESEARCH PROCESS 22

3.4 RESEARCH MODEL 25

3.5 MEASUREMENT SCALE 27

3.5.1 Measurement scale factors affecting apartment buying decision 27

3.6 MAIN SURVEY 30

3.7 DATA ANALYSIS METHOD 31

3.7.1 Reliability measure 31

3.7.2 Validity measure by EFA (Exploratory Factor Analysis) 31

3.7.3 Multiple regression analysis 32

CHAPTER 4: DATA ANALYSIS AND RESULTS 34

4.1 STATISTICAL SAMPLES 34

4.2 ASSESSMENT MEASUREMENT SCALE 37

4.3 MULTIPLE REGRESSION ANALYSIS 47

4.4 HYPOTHESIS TESTING BY MULTIPLE REGRESSION 51

CHAPTER 5: CONCLUSIONS AND IMPLICATIONS 57

5.1 RESEARCH OVERVIEW 57

5.2 RESEARCH FINDINGS 58

5.3 MANAGERIAL IMPLICATION 59

REFERENCES 61

APPENDIX 66

LIST OF TABLE

Table 3.5: Main factors affecting customer’ housing decision

Table 4.1: Characteristics of respondents

Table 4.2: Cronbach’s Alpha test results

Table 4.3: Total testing results scales

Table 4.4: EFA results

Table 4.5: EFA results analysis Factor of scale purchase Decision

Table 4.6: EFA results analysis Factor adjusted

Table 4.7: Correlation among variables

Table 4.8: Indicators for assessment the relevance of model (Model Summary) Table 4.9: Regression Model

Table 4.10: Coefficient Regression Results

Table 4.11: Hypotheses results

LIST OF FIGURE

Figure 2.2: Condominium market in HCMC Q3-2015

Figure 2.4.3: General model of consumer behavior

Figure 2.4.4: Model of consumer behavior (Kotler, 1999)

Figure 3.1: Research design

Figure 3.3: Research process

Figure 3.4: Research model

Figure 4.1: Adjust the research model

Figure 4.4: Official research model

LIST OF ABBREVIATIONS

ANOVA Analysis Of Variance

CFA Confirmatory Factor Analysis

EFA Exploratory Factor Analysis

SPSS Statistical Package for Social Scientists

EFA Exploratory Factor Analysis

GSO Vietnam Government Statistics Office

HCMC Ho Chi Minh City

Mil Million

MLR Multiple Linear Regression

CHAPTER 1 INTRODUCTION

1.1 BACKGROUND

The property market in Vietnam is showing signs of getting warmer and industry insiders do not think there will be another real estate bubble as there was seven years ago The latest housing bubble occurred in Vietnam in the 2007-2008 period, when investors rushed to the realty sector after the stock market went into a crisis The bubble then quickly burst, leaving the market frozen with a huge number of unsold land plots, houses, and apartments (Young news, 2015) Thanks to strong economic growth, and a growing middle class, after almost five years of a housing slump but most important is the new Housing Law and the Law on Real Estate Business These came into effect in July 2015, and allow foreigners and overseas Vietnamese to legally own, sell and transfer real properties (Global property guide, 2015)

As many as 5,150 apartments were put on sale in the first quarter of this year, three times the figure last year, according to a survey by realty consultant CBRE (CBRE Releases Q3/2015 Quarterly Report Highlights for Ho Chi Minh City Market) The number of new apartments in the first quarter rose 40 percent year on year, which consultancy Savills said is the strongest growth since February 2011

Most apartment purchasers in Ho Chi Minh City in the year to date have been real homebuyers, who buy to live there, rather than speculators and secondary investors who purchase to resell, according to industry insiders

Real estate trading floors in the city are receiving more customers than this time last year, and more purchase contracts have also been closed

According to the report of “Vietnam Housing Sector Forecast to 2015” indicates the housing requirement is rising with trend of nuclear families has created immense demand expected to grow around 6% during 2012-2015

The condominiums in new urban areas are preferred by many young people because the types of condominiums offer various advantages over traditional housing types such as: lower price, good infrastructure with various facilities and services which are suitable for the needs The demand of young people for condominiums has been increasing massively in recent few years

One of the most significant economic decisions of everybody is buying a house oneself The need of dwelling is practical and more increasingly when the population is growing and choosing big cities for permanent residency

However, according to the Deputy Minister of Construction Nguyen Tran Nam (2015), he emphasized that “people’s housing demand is very large and solvency is high, but the real estate market lacked of information”

This thesis focuses on factors which influence on people's purchase decision toward apartments/condominiums in Ho Chi Minh City

Based on this situation, I would like to point out some problems to correspond to questions stated as follow:

- What are main factors influencing on apartment purchase decision of customers in HCMC?

- How is impact of these factors on apartment purchase decision of customers evaluated in HCM context?

Understanding relationship between main factors affecting customer house purchase decision is an important role for both real estate developers and enterprises to satisfy customers’ demand and to have available strategies in the real estate field

Target respondents for this thesis should be people who are living and working in HCMC

1.6 METHODOLOGY

The real estate is a broad topic requires further deeply research with consuming significant time and efforts This thesis is relatively provided merely firsthand information to assess real demand and determinants impact on residential apartment buying decision

Research methodology is an important part of the whole process of research to determine how the research should be undertaken

In order to achieve the objective, both primary data and secondary data are collected

to use in the thesis:

The primary data is gained by distributing questionnaire on residential apartment purchasing decision to study key factors influence on The questionnaire consists of

3 parts: socio-demographic; apartment preference pattern; apartment purchasing intention; factors influence on buying decision

The secondary data is collected from a wide variety of reliable sources including academic books, articles, newspapers, magazines, journals, publications, reports of real estate companies, official websites Data related to apartment market in HCM City, definition and theory of apartment preference pattern; apartment purchasing intention; decision making process and previous finding will be utilized in the thesis

 By analyzing results of the primary data and compiling the secondary data

 The research method refers to techniques and procedures

 The research methodology refers to research designs and data collection via questionnaires

The inductive approach should be applied for this research to draw results from data collected and analysis and empirical observation

CHAPTER 2 LITERATURE REVIEW

2.1 INTRODUCTION

This chapter presents overview of previous literatures relating to apartment purchase decision making of customers Also, a conceptual framework is built up and relative hypotheses of research are raised

A variety of studies focuses on housing characteristics such as cost, size and location Others give attention to demographic characteristics such as age, sex and income as determinants of preference Some investigate housing preference in the connection with family life cycle and residential mobility

2.2 APARTMENT MARKET IN VIETNAM OVERVIEW

According to David R Henderson, the concise of encyclopedia of economic (David, 2002), the law of demand is built almost the whole edifice of economics The law of demand states that when the price of a good rises, the amount demanded falls, and when the price falls, the amount demanded rises However, the real estate industry does not always apply this law conclusively The effective housing demand is the amount of housing for which the population is willing and able to pay The effective housing demand for private housing is volatile and has been affected in the past by the market supply and market allocation mechanism There are many factors impact

on demand and decision of buyer of apartments such as: price, financing supports, household income, features of apartment, legal framework, developer, contractor, management etc

Potential buyers have been divided into two subgroups: residents who buy and sell houses for personal use, and speculators and property developers who make money

by selling and buying property (Roehner, 1999)

Residents’ choice to migrate from one city to another depends on the employment,

income and political and social environments (Dieleman et al., 2000) demonstrated

that, population growth and employment growth seem to create differences in the rate of turnover and the differences in price levers Many researchers claim that income is an important determinant of housing demand

The population density in HCMC could be considered highest with the average density in the central at 27,000 persons per km2 when comparing with density cities

in the world, namely Singapore and Hong Kong where high-rise apartment buildings are ubiquitous The density in Hong Kong Island stands at 16,000 persons per km2 (2008) (Census & Hong Kong., 2009), and the density in Singapore is 7100 persons per km2 (2010) (Department of Statistics, 2010) (Jieming Zhu, 2011) Another factor influences on demand of buying apartment is financing support from bank and government Credit constraints in the form of down payment requirements significantly affect housing consumption for many buyers Bank loans are usually required by most households to finance their purchases The credit or financial market typically cannot lend on the basis of the borrower’s expected future income prospects Therefore, current income and current financial assets then become important indicators of a borrower’s means of repaying a loan The availability of housing loans and government subsidies will influence consumers’ choice of whether or not to buy a home (Omar and Ruddock, 2002) The demand for housing also depends on the mortgage rates and the general level of consumer confidence (Tutoru, 2003)

The study of RNCOS (Business Consultancy Services) on Vietnam Housing Sector Forecast to 2015, one of issues relating to housing demand of Vietnamese is affordability The report studies the affordability scenario of Vietnam and found that house price to household income ratio is much higher than the neighboring regions, creating vast gap between house price and affordability

Young people live in big cities such as Ha Noi, Da Nang, and HCMC have great demand of housing based on various experiences of life milestones (adulthood, education and graduation stages, job seeking, and occupation path, leaving parental home, job opportunities, marriage and children) These various experiences somehow influence on demands of housing types, attributes and services associated into

But the price of residential condominium in HCMC is still quite high and people tends to purchase apartments depends on the level of disposable income (Bible & Hsieh, 2001; Brandy & Parsons, 2002) High level of disposable income will increase the ability of spending and especially in purchase of housing is a major goal of most people

Firstly, price is one of important determinants of a household choice and buying decision However, unlike other consumption goods, the housing market is unique because it manifests the characteristics of durability, heterogeneity, and spatial fixity Thus, to model this differentiation effectively, the second approach of the hedonic price model has been introduced The hedonic price model posits that goods are typically sold as a package of inherent attributes (Rosen, 1974) Therefore, the price of one house relative to another will differ with the additional unit of the different attributes inherent in one house relative to another house The relative price of a house is then the summation of all its marginal or implicit prices estimated through the regression analysis The market price of a housing unit’s bundle of inherent attributes, such as: location, structure and neighborhood or environment attributes (Freeman, 1979)

The house price determination is associated with macro (market-related factors) and micro (house-specific factors) How do the researchers link these factors to the price? The first step to this is to establish theoretical background for the pricing theory Thus, the review begins with identifying price determinants The review will then followed by discussion on the utilization of statistical tool as one of the

approaches available to segregate the contribution of each variable hence enabling the quantification of perceived contribution in the overall price

In this thesis, the micro factors (house-specific factors should be focused replace for macro factors (such as: interest rates, inflation rates, taxes are critical explanations for setting price from developers) The micro factors could be derived from buyers

of apartments in evaluating factors such as: structural (physical characteristic), location and life environment attributes (contain of neighborhood) impact on buying decision process

During last economic recession years, there was a phenomenon of bubble real estate industry where the price of apartment segment had pushed up very high and caused customers who have real need could be unaffordable to buy This had been occurring problem of affordability and inequality (Yip, 2008) and major real estate developers, private and public alike to focus on squeezing into higher end market and this had made low income workers out of reach for new flats

The city government increasingly seeks solutions to support middle income and low income group could be affordable to buy apartment (SGGP News, 2013) According to HCMC Real Estate Association said many capable Vietnamese businesses have channeled their capital into the luxury housing sector to satisfy demand of high income groups, while affordable housing apartments for low-income people has fallen short The unbalanced supply of accommodation has now left a large unsold inventory

The HCMC real estate market remains positively stable in this quarter and the upward trend of FDI and M&A is expected to continue for the foreseeable future (CBRE Releases Q3/2015 Quarterly Report Highlights for Ho Chi Minh City

Market)

In Q3 2015, positive market momentum continued, boosting new launch activities and sales performance A total of 10,114 new units were launched from 26 projects,

Research and Consulting, shared that by location, new supply from the South (encompassing districts 4, 7, 8, and Nha Be Commune) accounted for 36% of the total new launched stock, while the recent hot spot in the East (districts 2, 9, Binh Thanh and Thu Duc) accounted for a more modest 29% this quarter Ms Dung further highlighted, “It is interesting to once again see Southern properties taking the lead compared to the East, particularly following the recent news that HCMC plans to develop its first special economic zone (SEZ) in the East of HCMC encompassing districts 7, Nha Be, part of Binh Chanh and Can Gio with a focus on marine economy Vingroup has also announced to partner up with Saigon Port to develop a 32 hectare prime site at the removed Khanh Hoi Port in District 4 in the East zone The market is believed to witness more competition between these two hot zones in the coming time, especially in the context that now Thu Thiem New Urban Area in the East has been started its development with the first condominium blocks called Sarimi being launched in Q3 2015.” The review quarter also witnessed a repackaging of some long-delayed projects where new developers have taken over and revitalised developments by providing more finance or redesigning unit layout, size and mix These projects include City Gate Towers (District 8), Linh Tay Tower (Thu Duc District), and C.T Plaza Nguyen Hong (Go Vap District) Figure 2.2

Three months after new regulations came into effect some initial interest from foreign buyers has been recorded Mr Marc Townsend, Managing Director of CBRE Vietnam, commented, “There has not been a notable increase in sales to foreigners to date as many potential buyers are awaiting more guidance and progress in implementation Being an agent initiatively targeting at this group of buyers, we have observed that professionalism, language proficiency and ease of credit card payment are some of the key issues once foreign buyers are involved.”

Figure 2.2: Condominium market in HCMC Q3-2015

2.3 FORECASTS APARTMENTS MARKET IN 2015 - 2016

According to Savills research (Briefing apartment sector, 2015), from Q4/2015 to

2017, approximately 57,500 new units from 92 existing and future projects are expected to enter the market Approximately 33% of the total future supply is expected to be completed in 2015 and 2016

VNREA forecast in 2016, the real estate market continues to grow thanks to favorable macroeconomic factors, the lure of mergers and M & A in the field is capable of exploding in the period 2016 to 2017 by the Vietnam visit Family deeper

on the path of regional integration and globalization

Specifically, Vietnam is a country that will benefit most, thanks to flexible conditions than the Member States Economic Partnership Agreement Trans-Pacific (TPP) other Therefore, in the next 4-5 years, a number of economic sectors in Vietnam will benefit and strong growth, including real estate

At the same time, the ASEAN Economic Community (AEC) will be formally established in late 2015, the real estate market in Southeast Asia will become the focus in the sights of international investors

With policies on housing and real estate business has been enforced, that Vietnam has VNREA well prepared to catch the wave of international investment

Based on the business performance of realty firms this year, experts believed that Vietnam real estate market will become better in 2016

Thanks to increasing demand and new regulations of the 2014 Housing Law and the

2014 Law on Real Estate Business, leading experts said the market would be more buoyed next year

A recent report of Hung Thinh Real Estate Exchange JSC (Hung Thinh Land) revealed that the firm has sold around 4,500 apartments since the beginning of

2015, nearly reaching the sales target of 5,000 units for the whole year

Nguyen Nam Hien - General Director of Hung Thinh Land said the firm has more customers who have searched for medium-end apartments with good prices For

2016, Hung Thinh Land plans to expand operation, with the aim of distributing more products developed by its parent company Hung Thinh Corp

Besides, Dat Xanh Group plans to launch 4,000-6,000 apartments onto the market per year, apart from villas and urban land lots by 2020

This year, many major Ho Chi Minh City-based real estate trading floors expect to sell 1,000 - 3,000 apartments and land lots These ambitious targets would be maintained for 2016

Chairman of the Ho Chi Minh Real Estate Association (HoREA) Le Hoang Chau forecasted that property market recovery would continue in 2016

Prices at various housing projects in HCMC have been 5-15% higher this year, Chau added However, he also stressed that there is no sign of a real estate bubble in the coming time

At a recent conference on the 2016 real estate market trends, Prof Dang Hung Vo - former Deputy Minister of Natural Resources and Environment said there have been more positive signs for the domestic market, such as increased disbursements of loans for housing projects, more successful transactions and falling inventories According Prof Dang Hung Vo, analyzed that when a real estate bubble occurred in previous years, property prices skyrocketed at least 1% per day For the next years, however, thanks to the new legal documents and higher market transparency, the domestic market will not experience such price rallies

2.4 BEHAVIOUR IN PURCHASE DECISION OF CUSTOMER

Study of consumer behavior is very important because intentionally or unintentionally we are consumer With the philosophy of marketing production trend to marketing trend of consumer behavior has been important In marketing some question create that as a marketer we should pay attention to them and provide

a reasonable answer for them One of the following questions is: What is the purpose of consumer behavior? Considering that a marketer seeking to identify the needs and demands of our customers and do the appropriate action to meet those needs and desires, should understand Consumer behavior as well In this study, the researcher wants to explain his view according to previous studies briefly in consumer behavior

2.4.1 Definition of Consumer Behavior

Consumer behavior in marketing is a new issue So that the first books published does not reach before 1968 in this field Most universities do not make any effort before 1970, but it has grown significantly in recent years, So that a special team of investigators was formed in 1970 about consumer behavior and in 1990 the group

had 1500 members from 30 countries

Definition: Consumer behavior include mental activity, emotional and physical that people use during selection, purchase, use and dispose of products and services that satisfy their needs and desires (Kotler, 1999)

2.4.2 Key concepts of consumer behavior

1) Consumer behavior is motivational: The main question that arises in this context

is that "why consumer behaviors occur?” Answer to this question is included in the definition of consumer behavior Consumer behavior is to meet the needs and demands of him Behavior is a tool to achieve objectives and target consumer derives from his needs and desires (Wilke, 2000)

2) Consumer behavior include many activities: All consumers have differences in terms of thoughts, feelings, and decisions and etc With each other, marketers must pay attention to the activities of consumers, some consumers activities are: See this advertisement, purchase decision, the decision about how to pay (cash, credit) and etc

3) Consumer behavior is a process: Consumer behavior, including the selection, purchase and consumption of goods and services that include elimination of three steps before buying activities, purchasing activities, activities after purchase (Rostami, 2001)

4) Consumer behavior at different times has different complexity: Buy different product by different people has different implications Buy some goods, involves all three process step of the consumer Behavior, while buying some goods (goods that are consumed regularly) is very simple and does not require multiple steps Customers try to make buying process simple through trusting others, loyalty to the brand and etc

5) Consumer behavior includes different roles: Consumers in different time can play

each of the three roles affective, buyers and consumer When we buy something for our self we can play that 3 role (Golchinfar, 2006) Sometime by using others opinion buy something for some one that in this case we can play an individual role 6) Consumer behavior is influenced by external factors: Consumer behavior is influenced by many external factors such as culture, subculture, social classes etc These effects can be short, medium or long term

7) Consumer behavior is different in different people: Because people have different desires and needs, so their behavior is different And the difference consumer behavior make predict consumer behavior more difficult, to resolve this problem can categories the market (Abbasi & Torkamani, 2010)

2.4.3 Consumer buying decision process

Consumers can purchase different products And this difference because that different buying decisions buying process consists of several steps in Figure 1 (taken from the site abercrombie.com) presented Consumers to purchase some goods don’t need to pass during all stages of the buying decision However, some purchases are so important that the consumer is forced to do all these steps carefully and meticulously (Gilani Nia, 2010) These steps include:

1) Identify the problem: The first stage of the decision-making process is that people can feel the difference between current and desired situation, so trying to resolve these differences

2) Data collection: For solving this problem collect information This information can be internal (experiences) and external (family, exhibits, etc.)

3) Assessment Options: After gathering information, the consumer is ready to make

a decision At this point, he should be able to evaluate different options and choose products that meet the demands of him

Consumer at this stage, according to the information already obtained, Select a product that feels satisfy his need and buys it

5) After purchase behavior: Consumer compare purchased products with ideas, products, competitors, perceptions and expectations of the product and two satisfaction and dissatisfaction, which may appear different reasons

Figure 2.4.3: General model of consumer behavior

In the past, sellers, due to lack of competition and lower a variety of products directly sell the product But today, by increasing companies, increasing competition and increasing revenues from other people, other sellers will not be

able to communicate directly with sellers Marketers and sellers are forced to study consumer behavior research Now the question comes, who the buyers? When do they Purchase? And etc But the important question is how consumers respond to marketing stimuli? The company is rated from consumer responses to be aware marketing stimuli, so companies in relationship between marketing stimuli and consumer response, have been done many studies Starting point for this research is shown in Figure 2 As the figure shows, the marketing stimuli associated with other stimulants into the black box of the consumer and this will cause a reaction in the black box Now, marketers want to know what is going on in the black box Black Box itself is composed of two parts First part personal characteristics of buyer on how to understand and respond to stimuli affect and the second part is the buyer's decision-making process that effects on his behavior

Figure 2.4.4: Model of consumer behavior (Kotler, 1999)

2.5 THE FACTORS IMPACT ON PURCHASE DECISION APARTMENT

OF CUSTOMER

Haurin (2002) demonstrated that, owning one house will be improve the family environment, including the child's life, improves cognition and reduces behavioral

problems However, the current apartment market have to many residential projects, each project had features and factors with different convenience to be able to choose the one apartment matching demand and investment value, customer interest following factors to choose decided to buy apartments

2.5.3 Factors “Living space”:

Based on past studies, only a few exterior attributes are believed to influence consumers’ housing purchase choices These attributes can be roughly divided into two types: exterior design and exterior space Exterior design includes the appearance of the house, type of finish, quality of finish, the presence of a garden, the function of the garden, the type and the quality of roof, external walls and external floors

Exterior space refers to size of garden and size and the type of public area (such as swimming pool, recreation room, public kitchen, game room) (Bhatti & Church, 2004; Greene & Ortuzar, 2002; Opoku & Abdul-Muhmin, 2010; Pasha & Butt,

1996, 1996)

Dale-Johnson and Phillips (1984) identify lot size, number of bedrooms, number of bathrooms, square footage of living space, year built, number of fireplaces and the internal condition as intrinsic housing attributes

These may include “the actual area of living space, an address, accessibility to employment, a set of neighbors, a neighborhood environment, a diverse collection

of services including schools, clinics and retails, and sense of belonging to the community of residence” (Kain and Quigley, 1970)

Living space consists of “size of living room”, “size of kitchen”, “quantity of bathrooms” and “quantity of bedrooms” (Opoku & Abdul-Muhmin, 2010) In addition, it is accepted that there is relationship between the “space customer” and

customers’ purchase making process (Graaskamp, 1981)

2.5.4 Factors “Environment”:

Besides house characteristics, many residents are also concerned with other extrinsic Factors which affect their houses Thus, many researchers attach importance to identifying these factors The attributes of the environment around

the residential house are mentioned most frequently in recent studies The housing environment includes a very wide range of attributes, such as neighbor-hood characteristics, time in neighbor-hood (Arimah, 1997; Cheshire & Sheppard, 1995; Fierro et al., 2009; asha & Butt, 1996) environmental pollution, danger focus, air pollution, open space, greenery, security, cultural characteristics of the environment, street lighting, noise, pollution, rain water drainage, footpaths, width

of roads and pavements, orientation, layout of the street and geographic aspect (Ekeland, Heckman, & Nesheim, 2004; Rojas & Greene, 1995)

2.5.5 Factors “Finance”:

The financial is also taken into consideration by property investors As mentioned

by Reed and Mills (2006), several key areas regarding the financials are identified These include mortgage interest rates, household income, house price, and ability to obtain financing As an investor, the financials might be the utmost important factor among all factors This is because the financials are often involved with money in which investors would want to gain from their investment In the case of homeowners, the financials accounts almost 30 percent of the decision for them when purchasing a house (Reed & Mills, 2006)

Karsten (2007) mentioned that, affordability is a major factor in terms of making purchasing decisions of a residential property Therefore, the financial factors would play a significant role in making investment decisions

CHAPTER 3: RESEARCH METHODOLOGY

as a questionnaire and will be sent to respondents Meanwhile, an interview is used

to collect the opinions from investors relating to residential investment The results from both methods will be collect and analysis

It is also mentioned by Saunders et al., (2009) that, there are three research approaches which are used in a market research: inductive, deductive and combination The inductive approach starts with the observations and theories are formulated towards the end of the research and as a result of observations (Goddard and Melville, 2004) Contrary, a deductive approach is concerned as “reasoning from the general to particular” (Pelissier, 2008) This thesis is develop base on an inductive approach, which means the results of thesis are drawn from the theories, the collect and analysis data as well as from empirical observations The process approaching data and information in this thesis is described in the Figure 3.1 below

Figure 3.1: Research design

The empirical study is built on both primary and secondary data Primary data is collected using a quantitative method (questionnaire) and a qualitative method (interview) While the quantitative method provides the general observation, the qualitative method indicates the in-deep knowledge and opinions of the respondents Secondary data is drawn from articles, reports, and statistics from official sources such as government, agencies and prestige organizations

3.2 SAMPLE SIZE

The reliable and validity of variables were tested by using Cronbach’s Alpha and EFA after that the multiple regression was applied to test model and hypotheses First of all, the sample size was required to have enough quantity for the analysis The minimum sample size was 100 and not less than five times of items (Hair et al., 2010), thus:

- n > 100 and n = 5k (where k is the number of items)

- In this study, the number of items are 29 items

- Thus, the minimum sample size was 5x29 = 145 samples

- In addition, based on five independent factors of the conceptual model, the multiple regression analysis required sample size at least (Tabachnick & Fidell, 2007):

- 50 + (8m) = 50 + (8x5) = 90 samples

- Where m: is the number of independent factors of the model

- Consequently, the minimum sample size should be 145 Based on the actual collection data, the quantity of available respondents from the questionnaire survey estimated 400, so that samples met the requirements above

3.3 RESEARCH PROCESS

Design the research progress through two phases:

- The first phase is to build scale and theoretical models to analyze the factors affecting the apartment market for customers’ purchase decision

- The second phase is a testing of the scale and model studies for specific cases study in Ho Chi Minh City, Vietnam

First phases: the ideas for construction scale, theoretical models for analyzing

factors affecting the apartment market for customers’ purchase decision The first phase has two steps

- Step 1: Build the scale From the preliminary analysis, establish the concept

of variables studying affecting factors of the real estate market Using a qualitative analysis at first to build a preliminary quantitative study After

interview, indicate the main factors that affect the apartment market for

customers’ purchase decision in case study of Ho Chi Minh City That is

built for the basis of theoretical concept purpose

- Step 2: Development of theory and modeling studies From preliminary

studies, completely research concept as a basis for the design study model,

construction of hypotheses

Second phase: Check the scale and model studies Continue 2 steps above,

- Step 3: determine the object, scope and scale testing hypotheses are

registered for apartment market for customers’ purchase decision in Ho Chi

Minh City After defining the object and scope of the study will be

conducted drafting interview content and interviews

- Step 4: testing the scale factor using the tool reliability (Cronbach’s alpha)

and factor analysis to explore (Exploratory Factor Analysis: EFA) to assess

the appropriateness of the model Verification scale model studies will be

adjusted to fit the data

After the results of factor analysis will be conducted to explore the quantitative

analysis of the factors affecting the supply for property for people with average

incomes

The main research implementation by quantitative methods for data collection

technique was direct interview through a questionnaire Data collected is processed

by SPSS 16.0

Assessment research factors impact to purchase decision of customer in choice

apartments in Ho Chi Minh city All steps were illustrated by following Figure 3.3

EXPLORATORY FACTOR ANALYSIS

(EFA)

MULTIPLE REGRESSION ANALYSIS

- ASSESSMENT MEASUREMENT SCALE

- ITEMS REMOVE INAPPROPRIATE

- CHECKING FACTORS

- CHECKING VARIANCE

- CHECKING APPROPRIATE MODEL

- ASSESSMENT IMPORTANT OF FACTORS

THEORETICAL

FRAMEWORK

Figure 3.3: Research process

“quality of building”, “equipment inside”, “legality” (Ariyawansa, 2007)

- H1: The factor “feature”, there is a positive impact on customers’

apartment purchase decision in Ho Chi Minh city

- H2: The factor “distance”, there is a positive impact on customers’

apartment purchase decision in Ho Chi Minh city

Living space:

“Private living space” is one of most important factors affecting to “consumer housing decision” Living space consists of “size of living room”, “size of kitchen”,

“quantity of bathrooms” and “quantity of bedrooms” (Opoku & Abdul-Muhmin,

2010, p.219) In addition, it is accepted that there is relationship between the “space customer” and customers’ purchase making process (Graaskamp, 1981)

- H3: The factor “living space”, there is a positive impact on customers’

apartment purchase decision in Ho Chi Minh city

Environment:

“Environment” including: “neighborhood”, “pollution”, “view”, “fire alarm system, exits”, “security” (Tan Teck Hong, 2012) In addition, factor “traffic” the researcher added (Connie Susilawati, 2001)

- H4: The factor “environment”, there is a positive impact on customers’

apartment purchase decision in Ho Chi Minh city

Finance:

“Financial” is an important factor affecting to decision when customer choice buy apartments (Sengul et al., 2010) The “financial” element of real estate requires access to a relative large amount of “capital” and as well as “borrowing costs” (Xiao

& Tan, 2007) In addition, “financial” status bases on combination of “house price”,

“mortgage loans”, “income” and “payment term” (Opoku & Abdul-Muhmin, 2010; Yongzhou, 2009) Haddad et al (2011) finds out the “economic” factor which is consisted of five variables, such as “income”, “interest rate”, “area”, “conversion” and “taxes” Moreover, Adair et al.(1996, p.24) and Daly et al (2003, p.306) group

“interest rate”, “maximum mortgage”, “maximum monthly payment”, and “length

of time payment” into “financial” factor

- H5: The factor “Finance”, there is a positive impact on customers’

apartment purchase decision in Ho Chi Minh city

Purchase decision

Customer behavior is an important research topic for recent decades “There is also

a clear shift from rational factors to psychological factors and to social decision factors” (Bargh, 2002) Beside there is a link between the “intention to purchase” to

“decision to purchase” of customers, especially the decision related to purchase real estate (Ajzen, 1991; Han & Kim, 2010; Kunshapn & Yiman, 2011)

3.5 MEASUREMENT SCALE

3.5.1 Measurement scale factors affecting apartment buying decision

According to research results of Mateja Kos Kokli’c Irena Vida (2009), about the factors affecting the buying behavior apartment in survey at Amman, Jordan And the factors affecting luxury apartment buying decision of customer individual at

HCMC (Nguyen Quang Thu et al., 2013) In this study, the author have used scale

of Nguyen Quang Thu et al., (2013), including five scales and twenty six variables observe, because this scales has been inspected in Vietnam market through quantitative research The scales are adjusted and supplemented by the results of in-depth interviews

As discussed in chapter 2, Five factors affecting apartment purchase decision including “Feature”, “Distance”, “Living space”, “Environment” , “Finance” are the independent variables and factor “purchase decision” is the dependent variable From discussion above, a summary table of main factors affecting customer’ housing decision making is presented as following Table 3.5

Table 3.5: main factors affecting customer’ housing decision

1

Fea01 Apartment size

Tan Teck Hong, (2012); RG Ariyawansa, (2007)

Fea02 Apartment design Fea03 Construction quality Fea04 Equipment inside Fea05 Apartment’s legal status

2

Dis01 Distance to school

Tan Teck Hong, (2012); RG Ariyawansa, (2007) Dis02 Distance to work

Dis03 Distance to the business

center

Dis04 Distance to market

Dis05 Distance to the health

center

3

Liv01 Living room size

Opoku & Abdul Muhmin (2010); Graaskamp, (1981)

Liv02 Kitchen size Liv03 Bedroom size Liv04 Bathroom size Liv05 Balcony size

Env02 Pollution Env03 View Env04 Fire alarm systems / Exits Env05 General security

5

Fin01 Interest rate

Opoku & Abdul Muhmin (2010);

Adair et al., (1996); Haddad et al.,

(2001)

Fin02 Payment duration Fin03 Mortgage loan Fin04 Income loan

Fin05 Maximum payment

In Table 3.5: The perception of customer factors as feature (code Fea01 – Fea05), distance (code Dis01 – Dis05), living space (code Liv01 – Liv05), environment (code Env01 – Env05), finance (code Fin01 – Fin05) Each factor including five observe variables, the observe variables are measure with scale Likert five levels Separate, decision factor of customer buying apartments (code Dic01 – Dic04), the author offering four observe variables, the observe variables are measure with scale Likert four levels

3.6 MAIN SURVEY

There were 450 hand delivered questionnaires, only 430 respondents gave feedback, but quantity of available respondents was 400

3.7 DATA ANALYSIS METHOD

After data collection, the first step would be data preparation with editing, coding, and data entry to ensure accuracy of data from raw data and to detect errors or omissions to correct Next, data were classified to arrange them into groups or classes of common demographic

Finally, variables would be tested reliable by Cronbach’s alpha, validity by EFA, and hypothesis and model would be tested by multiple regression of SPSS

3.7.1 Reliability measure

In order to check reliability of each of scales with particular sample, as well as consider the internal consistency of the scales, it was necessary to use Cronbach’s Alpha coefficient which should be above 7 (Devellis, 2003)

Also, the corrected item - total correlation values should be at least 3 to ensure each

of items was measuring the same from the scale as a whole (Pallant, 2011)

3.7.2 Validity measure by EFA (Exploratory Factor Analysis)

In order to evaluate the validity and the correlation among variables to identify underlying factors or define number of extracted factors, EFA was applied with the oblique approach using the Promax method However, some requirements of EFA should be satisfied (Pallant, 2011):

- The minimum of sample size should be at least 100 and rate of observations per items of models should be five cases for each of the items, so that meant the minimum required sample size should be at least 5m = 5x34 = 170 cases (where m: quantity of items from the conceptual model) The actual sample size was 400, bigger than 170 so it met the requirement

- The correlations of r of the correlation matrix should show at least 0.3