UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business -------------------- PHAN THANH SI KEY FACTORS AFFECTING HOUSE PURCHASE DECISION OF CUSTOMERS IN VIETNAM ID: 60340102 MASTER OF BUSINESS (Honours) SUPERVISOR: DINH THAI HOANG, Ph. Ho Chi Minh City - Year 2012 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ii ACKNOWLEGEMENTS First of all, I would like to express my deep appreciation to my supervisor, Dr. Dinh Thai Hoang who instructed and helped me enthusiastically during period of the thesis. I also would like to thank you all my colleagues and friends of Hoa Binh Corporation and Sacomreal for their valuable contributions to give comments and suggestion to revise the questionnaire survey.
I am grateful to the supervisory board for providing me with their available advices and patient supports when I need. I will never forget the friendly postgraduate students for helping me during studying and doing thesis. The most special thanks go to my parents, my brothers and sisters who always create the most convenient conditions for me as well as support me all time. LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com iii ABSTRACT The main purpose of the study is to investigate the effecting of key factors on housing purchase decision of customers in Vietnam.
First, a model which is proposed based on analyzing of previous literature. Then the model is tested on a pilot test which is conducted of a small real estate professional group and another group of 15 respondents, and on a larger survey of 263 samples. 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. Key works: real estate, purchase factors, Vietnam LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com iv TABLE OF CONTENTS ACKNOWLEGEMENTS .iii LIST OF TABLES. vii LIST OF FIGURES. RESEARCH PROBLEMS & RESEARCH QUESTIONS.
SCOPE OF THE RESEARCH. 15 LUAN VAN CHAT LUONG download : add luanvanchat@agmail. DATA ANALYSIS METHOD. Validity measure by EFA (Exploratory Factor Analysis).
Multiple regression analysis. DATA ANALYSIS & RESULTS. ASSESSMENT MEASUREMENT SCALE. Exploratory Factor Analysis (EFA).
Assessment of data. Defining number of extracted factors. HYPOTHESES TESTING BY MULTIPLE REGRESSION. Checking assumption of Multiple Regression.
Assessment multicollinearity of independent variables. Normality, linearity, homoscedasticity & outliers. Evaluating the model. Evaluating the independent of variables.
Checking hypotheses of model. Analysis effect of control variables by Multiple Regression. CONCLUSIONS AND IMPLICATIONS. RESEARCH LIMITATIONS & DIRECTIONS FOR FUTURE RESEARCH.
37 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com vi REFERENCES. 38 Appendix 1: The first draft of the questionnaire. 42 Appendix 2: The English questionnaire. 45 Appendix 3: The Vietnamese questionnaire.
49 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com vii LIST OF TABLES Table 3.1: Main factors affecting customers’ housing purchase decision .1: Codebook of questionnaire items .2: Characteristics of respondents .3: Cronbach’s Alpha test results .5: Correlations among variables .6: Coefficient table of MLR .9: Cronbach’s Alpha with full items for each constructs .10: KMO and Bartlett’s test .11: Total variance explained .12: Correlation among variables (Partial only) .14: Factor Correlation Matrix .19: Cofficients of MLR including Sex_Render .20: Cofficients of MLR including Marital_Render .21: Cofficients of MLR including Education_Render .22: Cofficients of MLR including Age_Render.23: Cofficients of MLR including Career_Render .24: Cofficients of MLR including Income_Render. 65 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com viii LIST OF FIGURES Figure 2.2: Regression standardized residual. 63 ABBREVATIONS EFA : Exploratory Factor Analysis GSO : Vietnam Government Statistics Office HCMC : Ho Chi Minh City Mil. : Million MLR : Multiple Linear Regression UEH : University of Economic LUAN VAN CHAT LUONG download : add luanvanchat@agmail.
BACKGROUND As universal population levels continue to rise, the housing shortage in many developing countries has reached critical levels (Morel, 2001, p. Real estate is one of the most important things to citizens, so “the house purchase decision of them can change their life” (Wells, 1993). The house purchase decisions are different from other business decisions due to “the innate, durable and long-term characteristics of real estate”. It is a highly differentiated product with “each specific site unique and fixed in location” (Kinnard, 1968).
In Vietnam, it is known as the third largest population in South East Asia and ranked the 14th largest in the world in terms of total population. Its population estimated of 89 million in 2010 (GSO, 2011). The annual average growth population of Vietnam from 2000 to 2010 was approximately 1.03 million people per year or 1. Particularly, one of the top economic centers of Vietnam is Ho Chi Minh City which has around 7.2 million people as in April 2009, but its actual population is likely to be significantly higher because of unrecorded migration from rural areas.
The real estate market in Vietnam has significantly changed during from the 1990s to now and it might be seen as three times fever and declining prices in the last 20 years. Up to the end of 2012, the large real estate outstanding loans and a big number of inventories created a serious crisis. However, according to the Deputy Minister of Construction Nguyen Tran Nam, he emphasized that “people’s housing demand is very large and solvency is high, but the real estate market lacked of information”. RESEARCH PROBLEMS & RESEARCH QUESTIONS In general, the real estate in Vietnam has got many difficulties in making effort to satisfy customer demands.
According to incomplete statistics of the Ministry of Construction surveyed in 44 provinces up to August 30th, 2012, the country now LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 2 had 16,469 unsold apartments, in which HCMC was 10,108 unsold apartments and total number of inventories of low buildings was 4,116, in which HCMC was 1,131 ones (Anh, 2012). Therefore, the Prime Minister stressed that the solution to rescue real estate market should be included in the Resolution of the Government. The main reasons of the crisis were the real estate market supply did not meet customer demands, the investors lacked of exact information of customer and real estate market conditions. “There are two main fields of customer research are how customers go about making decisions and how decisions should be made.
In addition, “creating true value for customer and customer notion focused approach” is confirmed (Edwards & Fasolo, 2001). It is found that “customer decision making is one of the most important areas of customer behavior and it requires gathering a lot of regarding information” (Bettman et al., 1998 & Simonson et al. There have been many published academic research about customer house purchase with variety of both developed and developing countries. However, “the national and cultural characteristics play a very significant role in house purchase decision, that mean finding which is applied in specific context may not extend to another context” (Opoku & Abdul-Muhmin, 2010).
The real estate in Vietnam has got specific characteristics to which connected customer demands closely. In recent years, researchers, domestic and foreign companies attracted to real estate field in Vietnam with a number of research works. However, there has been not enough research into the way customers making decision to buy real estate as well as which major factors have got relationship with customer decision. Consequently, in the term of real estate purchase decision of customers, the research questions of the thesis are raised as two following questions: LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 3 What are the key factors affecting the house purchase decision of customers in Vietnam? How is impact of these factors on house purchase decision of customers evaluated in Vietnamese 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.
RESEARCH PURPOSE Based on the research questions, the main purpose of this thesis is to identify what factors have impact on house purchase dicision of customers and examine how these factors influence their decision of buying house in Vietnam. SCOPE OF THE RESEARCH The research is conducted in Ho Chi Minh City with the respondents who are the postgraduates and students of UEH with various careers, as well as customers of a small book-coffee. The timeframe of research lasts from the middle of September to the end of October in 2012. RESEARCH STRUCTURES The research is divided into five chapters.
The first chapter introduces about background, research problems, research questions, research purpose, scope of research and research structures. The second chapter covers literature review of the previous research and shows hypotheses, as well as the conceptual framework of the research. The third chapter presents the research process, sampling size, measurement scale, main survey, and data analysis method. The fourth chapter concentrates on preparation data, descriptive data, assessment measurement scale and hypotheses testing.
Finally, the fifth chapter points out research overview, research findings, managerial implications, research limitations and directions for future research. LUAN VAN CHAT LUONG download : add luanvanchat@agmail. LITERATURE REVIEW This chapter presents overview of previous literatures relating to housing purchase decision making of customers. Also, a conceptual framework is built up and relative hypotheses of research are raised.
Feature Firstly, “features” of the building structure itself is an important determinant of a household choice of residence (Quigley, as cited in Haddad, 2011, p. Also, it is confirmed that “feature” has significant effects on customers’ house purchase decision making (Sengul et al. The “feature” of house includes “design”, “house size” and “quality of building” determinants relating to decision making to buy a house of an individual (Adair et al., 1996; Daly et al., 2003; Sengul et al.218; Opoku & Abdul-Muhmin, 2010). There is a positive impact of house features on customers’ house purchase decision.
Living space Secondly, “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. In addition, it is accepted that there is relationship between the “space customer” and customers’ purchase making process (Graaskamp, 1981). There is a positive impact of living space on customers’ house purchase decision.
LUAN VAN CHAT LUONG download : add luanvanchat@agmail. Finance Thirdly, “financial” status is much significant to customer house choice (Hinkle and Combs, 1987, p.375; Kaynak & Stevenson, as cited in Sengul et al. The “financial” element of real estate requires access to a relative large amount of “capital” and as well as “borrowing costs” (Xiao & Tan, 2007, p. In addition, “financial” status bases on combination of “house price”, “mortgage loans”, “income” and “payment term” (Opoku & Abdul-Muhmin, 2010; Yongzhou, 2009, p.
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.24) and Daly et al.306) group “interest rate”, “maximum mortgage”, “maximum monthly payment”, and “length of time payment” into “financial” factor. There is a positive impact of financial status on customers’ house purchase decision.
Distance Fourthly, one of the most important factors affecting individual “decision” making to buy a house is “location” factor (Kaynak & Stevenson, as cited in Sengul et al. The “residential location” has an influence on “people’s housing choice” (Zabel & Kiel, as cited in Opoku & Abdul-Muhmin, 2010, p. Distance to choose house can be affected by “width of adjacent” and “location to school” (Opoku & Abdul-Muhmin, 2010). Moreover, “distance to central business”, “distance to school” and “distance to work” are considered (Adair et al.