Key factors influencing on apartment purchase decision of customers in ho chi minh city

RESEARCH PROJECT (BMBR5103) KEY FACTORS INFLUENCING ON APARTMENT PURCHASE DECISION OF CUSTOMERS IN HO CHI MINH CITY STUDENT ‘S FULL NAME : PHAM THI NGOC VAN STUDENT ID : CGSVN00015047 INTAKE : MBAOUM0313 ADVISOR’S NAME & TITLE : A. Prof. PHAN DINH NGUYEN September 2014 Page ADVISOR’S ASSESSMENT Advisor’s signature i ACKNOWLEDGEMENTS First of all, I would like to express my sincere thanks to my thesis coach – A. Prof Phan Dinh Nguyen for dedicated deep guidance, precious advice and teaching me data analysis guidance in his precious time. 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. Sep 2014 Pham Thi Ngoc Van ii ABSTRACT The speed of growing population in a recent decade together with the economic development, the demand of housing is more and more increasing while the price of ownership is big issue at Vietnam. Condominium is becoming the convenient living model for people stay in big cities such as: Ha Noi, HCM and Da Nang where the demand of living and working of immigration increasing. The beneficial view of condominium is the residents can enjoy convenient facilities from their own apartment to opening space with greenery system anywhere. The demand of condominium in big cities is certain and especially at Ho Chi Minh City where the research will pay attention real demand for middle income people. The researcher will identify factors or determinants influence on the demand of buying apartments at HCM City. The study aims to identify the key factors affecting the decision of customers to buy residential apartments in HCMC. For study purpose, a sample of 300 salaried class persons was taken by using purposive sampling technique. The sample consisted of those respondents who either bought an apartment or are planning to buy. Respondents were asked to give their opinion about listed variables on Five-point Likert Scale. By using Exploratory Factor Analysis, six factors were extracted which explained 73.916 per cent of total variance. iii Contents ADVISOR’S ASSESSMENT .i ACKNOWLEDGEMENTS .ii ABSTRACT . iii LIST OF TABLE .vii LIST OF FIGURE .ix LIST OF ABBREVIATIONS x CHAPTER 1. INTRODUCTION . 2.1. BACKGROUND . 2.2. PROBLEM STATEMENT . 2.3. RESEARCH OBJECTIVES 2.4. RESEARCH QUESTIONS . 2.5. SCOPE OF STUDY 2.6. METHODOLOGY 2.7. CHAPTER OVERVIEW CHAPTER 2. LITERATURE REVIEW . 2.1. APARTMENT OVERVIEW 2.2. LITERATURE REVIEW 11 2.2.1. Feature . 11 2.2.2. Finance 12 2.2.3. Distance . 12 2.2.4. Facilities 13 2.2.5. Environment 13 2.2.6. Purchase decision 14 2.3. CONCEPTUAL FRAMEWORK 14 iv CHAPTER 3. RESEARCH METHODOLOGY . 16 3.1. RESEARCH PROCESS 16 3.2. SAMPLE SIZE 19 3.3. MEASUREMENT SCALE . 19 3.3.1. Measurement scale 19 3.3.2. Pilot test . 19 3.4. MAIN SURVEY . 22 3.5. DATA ANALYSIS METHOD . 23 3.5.1. Reliability measure . 23 3.5.2. Validity measure by EFA (Exploratory Factor Analysis) 23 3.5.3. Multiple regression analysis . 24 CHAPTER 4. DATA ANALYSIS AND RESULTS . 26 4.1. PREPARATION 26 4.1.1. Editing . 26 4.1.2. Coding . 26 4.2. DESCRIPTIVE DATA . 29 4.3. ASSESSMENT MEASUREMENT SCALE 32 4.3.1. Cronbach’s Alpha . 32 4.3.2. Exploratory Factor Analysis (EFA) 37 4.4. HYPOTHESES TESTING BY MULTIPLE REGRESSION . 42 4.4.1. Checking assumption of Multiple Regression 42 4.4.2. Evaluating the model 43 4.4.3. Evaluating the independent of variables . 43 4.4.4. Checking hypotheses of model . 44 4.4.5. Analysis effect of control variables by Multiple Regression 46 CHAPTER 5. CONCLUSIONS AND IMPLICATIONS 47 5.1. RESEARCH OVERVIEW 47 v 5.2. RESEARCH FINDINGS 47 5.3. MANAGERIAL IMPLICATION . 48 5.4. RESEARCH LIMITATIONS & DIRECTIONS FOR FUTURE RESEARCH HYPOTHESIS . 49 REFERENCES . 50 Appendix 1: Vietnamese questionnaire . 64 Appendix 1: English questionnaire 69 vi LIST OF TABLE Table 3.1: Main factors affecting customers’ housing purchase decision . 21 Table 4.1: Codebook of questionnaire items . 26 Table 4.2: Characteristics of respondents 29 Table 4.3: Cronbach’s Alpha test results . 34 Table 4.4: EFA results 39 Table 4.5: Correlations among variables . 41 Table 4.6: Coefficient table of MLR 44 Table 4.7: Hypotheses results 45 Table 4.8: Descriptive statistics . 74 Table 4.9: Cronbach’s Alpha with full items for each constructs 75 Table 4.10: KMO and Bartlett’s test 76 Table 4.11: Total variance explained . 77 Table 4.12: Correlation among variables (Partial only) . 78 Table 4.13: Factor Matrix 79 Table 4.14: Factor Correlation Matrix . 80 Table 4.15: Model summary 80 Table 4.16: Anova 80 Table 4.17: Casewise diagnostics 81 Table 4.18: Residuals statistics 81 Table 4.19: Coefficients of MLR including Gender_Render 85 Table 4.20: Coefficients of MLR including Marital_Render 85 Table 4.21: Coefficients of MLR including Education_Render 86 vii Table 4.22: Coefficients of MLR including Age_Render 86 Table 4.23: Coefficients of MLR including Occupation_Render 87 Table 4.24: Coefficients of MLR including Income_Render 87 viii LIST OF FIGURE Figure 2.1 : Research Model 15 Figure 3.1: Research process 18 Figure 4.1: Scree plot . 78 Figure 4.2: Regression standardized residual 82 Figure 4.3: Normal P-P plot . 83 Figure 4.4: Scatterplot 84 ix Fin02 Maximum mortgage Fin03 Maximum monthly repayment Fin04 Interest rate Fin05 Income Fin06 Payment duration Fin07 Registration fee 3. DISTANCE Important level Distance Dis01 Location close to own family Dis02 Distance to workplace Dis03 Distance to CBD Dis04 Distance to schools Dis05 Distance to markets, shopping centers Dis06 Distance to recreation centers Dis07 Access to the main street 4. FACILIY Important level Facilities Fac01 Fire prevention & extinguish system Fac02 Electricity and water supply system Fac03 Basic facility Fac04 Sewage system Fac05 Parking place 5. ENVIRONMENT Important level Environment Env01 Community / Neighborhood Env02 Apartment security 24/24 72 Env03 View Env04 Pollution Env05 Living space Env06 Private 6. DECISION: Scale from to 5: 1. Totally disagree 2. Disagree 3. Neutral 4. Agree 5. Totally agree Decision Agreement level Dec01 Planning to buy a new apartment Dec02 Making effort to buy a new apartment Dec03 An important person affecting apartment purchase decision Thank you very much! 73 Table 4.8: Descriptive statistics Descriptive Statistics N Minimum Maximum Mean Std. Deviation Gender 230 1.68 0.47 Age 230 1.53 0.52 Education 230 3.24 0.60 Occupation 230 1.20 0.57 Marital 230 1.43 0.98 Income 230 2.08 1.04 Size 229 2.61 0.98 Price 229 1.16 0.45 Type 227 1.31 0.56 Valid N (listwise) 227 74 Table 4.9: Cronbach’s Alpha with full items for each constructs Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Fea01-Apartment size/usable area 22.45 7.340 .653 .690 .591 Fea02-Status of apartment legal 24.03 7.811 .465 .347 .641 Fea03-Interior design and decoration 23.15 8.319 .557 .511 .632 Fea04-External design 22.59 8.881 .400 .323 .665 Fea05-Construction quality 23.35 7.461 .743 .794 .580 Fea06-Construction duration 23.71 8.171 .253 .096 .712 Fea07-Type of apartment 23.48 9.037 .080 .032 .767 Fin01-Apartment price 23.59 14.391 .587 .588 .734 Fin02-Maximum mortgage 24.77 13.975 .360 .174 .782 Fin03-Maximum monthly repayment 24.36 11.673 .767 .750 .682 Fin04-Interest rate 24.14 12.356 .714 .708 .698 Fin05-Income 23.73 13.445 .705 .684 .710 Fin06-Payment duration 24.26 14.357 .489 .295 .748 Fin07-Registration fee 24.75 17.323 .013 .020 .834 Dis01-Location close to own family 22.66 12.278 .578 .670 .719 Dis02-Distance to workplace 22.53 9.831 .700 .859 .680 Dis03-Distance to CBD 22.93 11.197 .772 .877 .677 Dis04-Distance to schools 22.98 11.030 .767 .772 .676 22.05 13.569 .377 .155 .756 Dis05-Distance to markets, shopping centers Dis06-Distance to recreation centers 22.96 14.239 .139 .041 .806 Dis07-Access to the main street 22.78 13.824 .202 .053 .794 Fac01-Fire prevention & extinguish system 13.38 4.638 .468 .366 .497 Fac02-Electricity and water supply system 13.34 4.714 .536 .382 .473 Fac03-Basic facility 13.91 4.249 .520 .340 .461 Fac04-Sewage system 12.58 4.856 .371 .188 .549 Fac05-Parking place 13.09 6.158 .012 .002 .726 Env01-Community / Neighborhood 20.83 5.970 .700 .653 .696 Env02- Apartment security 24/24 20.67 6.537 .583 .534 .728 Env03-View 19.91 6.773 .284 .116 .785 Env04-Pollution 20.47 4.791 .728 .710 .664 Env05-Living space 20.15 5.306 .677 .649 .685 Env06-Private 20.96 6.300 .272 .114 .807 75 Dec01-Planning to buy a new apartment Dec02-Making effort to buy a new apartment Dec03-An important person affecting apartment purchase decision 6.33 1.693 .794 .785 .617 6.07 3.013 .461 .213 .928 6.26 2.141 .819 .786 .598 Table 4.10: KMO and Bartlett’s test KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity .779 Approx. Chi-Square 3861.507 df 276 Sig. 0.000 76 Table 4.11: Total variance explained Total Variance Explained Extraction Sums of Squared Loadings Initial Eigenvalues % of Variance Cumulative % 6.335 26.395 26.395 3.099 12.914 2.860 Rotation Sums of Squared Loadings % of Variance Cumulative % Cumulative % 6.047 25.196 25.196 3.227 39.309 2.746 11.440 36.636 4.706 11.917 51.226 2.560 10.666 47.302 3.129 2.259 9.412 60.638 1.954 8.144 55.446 4.02 1.647 6.864 67.502 1.224 5.101 60.547 3.491 1.166 4.857 72.359 .890 3.710 64.257 3.105 .846 3.524 75.883 .807 3.362 79.245 .684 2.849 82.094 10 .625 2.604 84.698 11 .541 2.255 86.953 12 .524 2.183 89.136 13 .473 1.972 91.108 14 .418 1.740 92.848 15 .348 1.450 94.298 16 .258 1.077 95.375 17 .249 1.038 96.413 18 .189 .786 97.199 19 .156 .650 97.849 20 .134 .558 98.407 21 .129 .540 98.947 22 .112 .469 99.416 23 .086 .360 99.776 24 .055 .228 100.004 Component Total Total Extraction Method: Principal Component Analysis. 77 Table 4.12: Correlation among variables (Partial only) Inter-Item Correlation Matrix Dis01-Location close to own family Dis02-Distance to workplace Dis03-Distance to CBD Dis04-Distance to schools Fin01-Apartment price Fin03-Maximum monthly repayment Fin04-Interest rate Dis01Location close to own family Dis02Distance to workplace Dis03Distance to CBD Dis04Distance to schools Fin01Apartment price Fin03Maximum monthly repayment Fin04Interest rate 1.000 .447 .567 .800 -.002 .032 .018 .447 1.000 .918 .667 .074 .189 .160 .567 .918 1.000 .735 .058 .148 .136 .800 .667 .735 1.000 .069 .105 .094 -.002 .074 .058 .069 1.000 .505 .751 .032 .189 .148 .105 .505 1.000 .763 .018 .160 .136 .094 .751 .690 1.000 Figure 4.1: Scree plot 78 Table 4.13: Factor Matrix Factor Matrix a Factor Dis02-Distance to workplace .578 Dis03-Distance to CBD -.320 .727 Dis04-Distance to schools -.301 .756 Dis05-Distance to markets, shopping centers -.386 .742 Fin01-Apartment price .677 Fin03-Maximum monthly repayment Fin04-Interest rate Fin05-Income .340 .767 .353 .796 .318 .712 Fin06-Payment duration .445 Fea01-Apartment size/usable area Fea02-Status of apartment legal .349 .773 .451 .419 Fea03-Interior design and decoration .629 Fea04-Construction duration .479 Fea05-Construction quality .393 Env01-Community / Neighborhood Env02- Apartment security 24/24 Env03-View Env06-Private Fac01-Fire prevention & extinguish system 79 .894 .597 .473 .368 .553 .590 .530 .469 .668 .435 .460 -.365 Fac02-Electricity and water supply system Fac03-Basic facility Dec01-Planning to buy a new apartment Dec02-Making effort to buy a new apartment Dec03-An important person affecting apartment purchase decision .426 .485 .407 .466 .759 -.384 .605 -.413 .691 -.476 -.303 .347 Table 4.14: Factor Correlation Matrix Factor 1.000 .149 .099 .140 .184 .107 .149 1.000 .216 .553 .436 .393 .099 .216 1.000 .136 .116 .299 .140 .553 .136 1.000 .214 .360 .184 .436 .116 .214 1.000 .352 .107 .393 .299 .360 .352 1.000 Extraction Method: Principal Axis Factoring. Rotation Method: Promax with Kaiser Normalization. Table 4.15: Model summary b Model Summary Model R R Square a Adjusted R Square .356 Std. Error of the Estimate .341 .66944 Table 4.16: Anova a ANOVA Model Regression Residual Total Sum of Squares Mean Square df 55.385 11.077 100.385 224 .448 155.770 229 80 F 24.717 Sig. .000 b a. Dependent Variable: Decision b. Predictors: (Constant), Environment, Feature, Finance, Facility, Distance t Table 4.17: Casewise diagnostics Casewise Diagnostics Case Number Std. Residual 105 205 a Predicted Value Decision Residual -3.230 1.67 3.8290 -2.16230 -3.366 1.67 3.9198 -2.25310 a. Dependent Variable: Decision Table 4.18: Residuals statistics Residuals Statistics Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a Maximum 1.5514 4.2230 3.1391 .4918 230 -3.228 2.204 .000 1.000 230 .049 .257 .101 .038 230 1.54400 4.21860 3.13920 .49203 230 -2.25310 1.68163 .00000 .66209 230 -3.366 2.401 .000 .989 230 -3.410 2.456 .000 1.004 230 -2.31343 1.68163 -.00011 .68290 230 -3.4950 2.484 -.001 1.010 230 .255 32.710 4.978 5.072 230 .000 .091 .005 .012 230 .001 .143 .022 .022 230 a. Dependent Variable: Decision 81 Mean Std. Deviation Minimum N Figure 4.2: Regression standardized residual 82 Figure 4.3: Normal P-P plot 83 Figure 4.4: Scatterplot 84 Table 4.19: Coefficients of MLR including Gender_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .360 .156 -.061 -.047 .868 1.151 1.594 .112 .189 .106 .082 .935 1.069 .535 9.111 .000 .574 .521 .469 .768 1.302 .066 .280 4.928 .000 .399 .313 .254 .820 1.220 -.135 .076 -.104 -1.780 .076 .214 -.118 -.092 .781 1.280 -.133 .080 -.087 -1.663 .098 -.053 -.111 -.086 .963 1.039 B Std. Error a Model (Constant) .779 .412 Feature -.070 .076 Finance .088 Distance Facility Beta t Sig. 1.892 .060 -.051 -.917 .055 .085 .492 .054 .326 Environment Gender VIF a. Dependent Variable: Decision Table 4.20: Coefficients of MLR including Marital_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .485 .156 -.047 -.036 .886 1.129 1.433 .153 .189 .096 .074 .943 1.060 .520 8.845 .000 .574 .510 .456 .770 1.298 .067 .290 5.064 .000 .399 .321 .261 .810 1.235 -.125 .076 -.096 -1.649 .101 .214 -.110 -.085 .785 1.274 -.136 .102 -.069 -1.329 .185 -.070 .089 .069 .984 1.017 B Std. Error a Model (Constant) .746 .412 Feature .053 .076 Finance .079 Distance Facility Beta t Sig. 1.811 .072 .038 .700 .055 .076 .478 .054 .338 Environment Marital a. Dependent Variable: Decision 85 VIF Table 4.21: Coefficients of MLR including Education_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .500 .156 -.045 -.035 .886 1.129 1.512 .132 .189 .101 .078 .937 1.067 .533 .9009 .000 .574 .517 .465 .764 1.309 .067 .280 4.911 .000 .399 .312 .254 .819 1.221 -.126 .076 -.096 -1.651 .100 .214 -.110 -.085 .785 1.274 -.143 .149 .050 .961 .338 .037 -.050 -.050 .970 1.031 B Std. Error a Model (Constant) .610 .407 Feature .051 .076 Finance .084 Distance Facility Beta t Sig. 1.502 .135 -.037 -.676 .056 .081 .490 .054 .327 Environment Education VIF a. Dependent Variable: Decision Table 4.22: Coefficients of MLR including Age_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .480 .156 -.047 -.036 .886 1.129 1.478 .141 .189 .098 .076 .943 1.071 .522 8.896 .000 .574 .312 .459 .773 1.294 .066 .279 4.902 .000 .399 .512 .253 .819 1.221 -.126 .076 -.097 -1.663 .098 .214 -.111 -.086 .785 1.274 -.558 .402 -.072 -1.389 .166 -.166 -.093 -.072 .994 1.006 B Std. Error a Model (Constant) 1.217 .578 Feature -.054 .076 Finance .082 Distance Facility Beta t Sig. 2.105 .036 -.039 .708 .055 .078 .480 .054 .325 Environment Age a. Dependent Variable: Decision 86 VIF Table 4.23: Coefficients of MLR including Occupation_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .522 .156 -.043 -.032 .885 1.129 1.467 .144 .189 .098 .074 .943 1.067 .526 9.135 .000 .574 .522 .463 .775 1.291 .065 .284 5.070 .000 .399 .321 .257 .820 1.220 -.137 .075 -.105 -1.833 .068 .214 -.122 -.093 .783 1.277 -.419 .133 -.160 -3.149 .022 -.163 -.206 -.160 .977 1.003 B Std. Error a Model (Constant) .695 .398 Feature .048 .074 Finance .080 Distance Facility Beta t Sig. 1.748 .082 -.035 -.641 .054 .077 .483 .053 .331 Environment Occupation VIF a. Dependent Variable: Decision Table 4.24: Coefficients of MLR including Income_Render Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Correlations Zeroorder Partial Part Tolerance .540 .156 -.041 -.032 .882 1.133 1.428 .155 .189 .095 .074 .943 1.060 .525 8.948 .000 .574 .514 .462 .775 1.291 .067 .276 4.829 .000 .399 .308 .249 .814 1.228 -.122 .076 -.094 -1.605 .110 .214 -.107 -.083 .783 1.277 -.144 .120 -.062 -1.200 .231 -.089 -.080 -.062 .990 1.010 B Std. Error a Model (Constant) .759 .416 Feature -.047 .076 Finance .079 Distance Facility Beta t Sig. 1.824 .069 -.039 -.613 .055 .076 .482 .054 .322 Environment Income a. Dependent Variable: Decision 87 VIF [...]... impact on buying decision of apartment  To suggest solutions to match demand of people and supply of residential apartments located in HCMC 4 The objective of thesis aims to conduct a survey on housing preference (condominiums /apartments) of people in Ho Chi Minh City and examine difficulties, challenges in choosing apartment for long term residence The thesis aims to understand buying behavior of people... strategies in the real estate field 1.4 RESEARCH QUESTIONS Consequently, in the term of real estate purchase decision of customers, the research questions of the thesis are raised as two following questions 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... 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... distance on customers house purchase decision 2.2.4 Facilities Apartment facilities” is one of most important factors affecting to “consumer housing decision Facilities consists of “Storey of apartment building”, “Fire prevention & extinguish system and exit system of apartment building”, “Basic facilities must have: ATM stations, branches of banks, convenient stores, mini-marts, pharmacist, clinics,... 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,... key determinants to making decision of buying apartment (Adair et al., 1996; Daly et al., 2003; Sengul et al., 2010, p.218; Opoku & Abdul-Muhmin, 2010) H1 There is a positive impact of house features on customers house purchase decision 2.2.2 Finance Each of buying decision made is based on financial capacity and especially in purchasing an apartment, financial attribute significant impact on customer... positive impact of financial status on customers house purchase decision 2.2.3 Distance Thirdly, 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., 2010, p.219) The “residential location” has an influence on “a person’s housing choice” (Zabel & Kiel, as cited in Opoku & Abdul-Muhmin, 2010, p.220)... limitations that the thesis would study after defining and collecting opinions and contribution through research methodology conduct This research is supported to capture the key factors influence on demand of people in choosing apartment for dwelling in HCM City 1.3 RESEARCH OBJECTIVES  To determine factors affect purchasing demand of residential apartment in HCMC  To study which critical factors. .. meaning of questionnaires quite well and knew the way to answer, so the questionnaire was the last version to carry out in the massive areas After that, a main survey was conducted 20 From above discussion above, a summary table of main factors affecting customer’ housing decision making is presented as following Table 3.1 Table 3.1: Main factors affecting customers housing purchase decision Status of. .. 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 . thesis aims to conduct a survey on housing preference (condominiums /apartments) of people in Ho Chi Minh City and examine difficulties, challenges in choosing apartment for long term residence 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. (BMBR5103) KEY FACTORS INFLUENCING ON APARTMENT PURCHASE DECISION OF CUSTOMERS IN HO CHI MINH CITY STUDENT ‘S FULL NAME : PHAM THI NGOC VAN STUDENT ID : CGSVN00015047 INTAKE : MBAOUM0313