Factors affecting to the selling price of luxury apartments - Research in Hanoi

and external attributes of the house; 2 / The second group is the quality of accompanying services; 3 / The third group associated with the demographic variable. 2.1.2. Overview of nationally published scientific works related to the topic Previous studies (Nguyen Manh Hung et al (2009), Pham Van Binh (2013), Nguyen Quang Thu et al (2013), Luc Manh Hien (2014), Le Van Binh (2017), Nguyen Tuan Anh) (2018)) presented and analyzed the impact of factors on real estate prices such as: Area of the campus; Distance to city center; Number of floors of construction and location of houses on fronts or in alleys; ) quality of apartment construction and services, apartment management, effects of customer support policies, financial policies, physical variables, location variables, ambient variables, multiplier financial factors, non-financial factors ... But these studies still have certain limitations on the scope of research, research samples; theoretical research and empirical research to fully present, analyze and synthesize the factors that affect real estate prices. The studies on the factors affectingto real estate prices are summarized in Table 2.5. 2.1.3. Theoretical model and research problems solved in the thesis The theoretical model is built on the research overview as follows: Draft scale Official scale and model adjustment Testing the research scale (Cronbach alpha + Total variable correlation) Cronbach Alpha Preliminary Quantification Theoretical basis Official quantification EFA Factor discovery analysis (EFA weight test, Explanatory variance, number of factors) Qualitative \ H1. Theoretical model is based on research overview. From the research overview, the scale system of factors in the theoretical model is also built with the independent variables of 43 component attributes and 6 component attributes of the demographic factor (this factor proposed additions from theoretical models); The dependent variable consists of 3 component attributes. The research problems solved in the thesis: The thesis mentioned and solved the problem still left open (gaps) from previous research works. The thesis inherits and develops theories about the formation of real estate prices and the factors affecting to the selling price of luxury apartments in the Hanoi real estate market; Research direction of this topic will contribute to supplementing previous studies that are left open. 2.2. Rationale for prices and factors affecting to real estate prices 2.2.1. Definition of real estate, luxury apartments & luxury apartments Based on the regulations and legal documents, the author said that: * Real estate is a type of property, including: land, houses and structures attached to the land; including properties associated with such houses and constructions; other assets attached to land or other assets as required by law 2.2.2. Definition of High-end condominiums and luxury apartments a / High-end apartment building is a high-rise building for mixed residential and service purposes; having investment rate of over 20 million VND / m2; have a high quality of life equivalent to 4-star hotels or more. b/ High-end apartment building is a self-contained apartment owned by a rich customers, has the right to co-own multi-facilities of a high-end apartment. 2.2.2 The concept and nature of the price category Smith (1776) and next to Ricacdo (1871) argued that: The price is a monetary expression of the value of the good. The seller defines the price of a good and a service as the income the seller receives through transactions. The price and value of the goods are closely related; price has a close relationship with the use value or the value of the good; prices and socio- economic relations. 2.2.3. Property value and price characteristics Value is the core of the commodity. The concept of market value forms the main basis for real estate valuation (Ozdilek et al., 2002). Basically, the market value is calculated by the market price of the most likely transaction. 2.2.4. Factors that influence prices Internal factors (Marketing goals, Marketing - mix; Production costs and other internal factors); External factors (Characteristics of the market and demand, the nature and structure of competition, and other external factors). - Through real estate value: The factors affecting to the price include: (Physical characteristics, Legal properties, Location of real estate ...). In addition, factors belonging to investors also affect to property prices. In particular, Smith (2010) emphasizes 9 factors that influence price perception. 2.3. Theories related to the research topic Among the theories related to the research topic, typically: Planning behavioral theory; Asset Effect Theory and Quality Position Theory. These theories are related to the factors affecting to the apartment selling price as well as some component attributes of the factors ... In addition, some theories about marketing, transmission information is also referenced in use. CHAPTER 3: BACKGROUND AND RESEARCH METHODS 3.1. Research background 3.1.1. Overview of real estate market in Hanoi in the period 2010-2018 Market demand is shown in Table 3.1 and Table 3.2 as follows Table 3.1: Demand for residential real estate in urban areas Table 3.2: Demand for housing in urban areas Period (year) Number of housingunits for new households (million units) Number of units to bereplaced (2% per year) (million units) Estimated total housing unit demand (million units) Equivalent to floor area (million meter) 2009-2014 1,37 0,68 2,05 317,7 2014-2019 1,52 0,68 2,2 341 Strivingtarget Unit 2010 2015 Population in major cities Million (people) 26,45 36 Percentage of urbanization % of total population 28,72 39 Per capital / household Person/ household 3,8 3,4 Average commercial floor area meter/person 19,0 28 Total number of apartments segments Million (units) 6,70 10,30 Total area of square meter of commercial floor Million meter 467,8 908 Market supply: Real estate products (real estate) in Hanoi are divided into many different segments: residential real estate (apartment buildings, land plots, villas, individual houses); Commercial real estate (office for lease, commercial center and retail space); Specialized real estate (industrial real estate). High-end apartments are the biggest backlog in the real estate market. Supply in districts is quite diverse, but mainly concentrated in the mid-end segment. Real estate prices in Hanoi tend to increase with a large fluctuation range; Property prices also change cyclically and are strongly influenced by government policy and objective environment. 3.1.2. Multi-family housing development is concentrated in Ha Noi city. The process of social development from collective housing to luxury apartments in Ha Noi has gone through the following stages: The period from 1954 to 1986 was the period of building a collective house made of wooden structures and simple prefab house. After that, the first commercial apartment building was built in Ha Noi in 1987 was the 9-storey CT4B Building in Bac Linh Dam urban area. Followed by a series of commercial apartments, resettlement apartments, cheap condominiums and new condominiums. Indispensable trend of building high-rise condominium models in big cities such as Ha Noi and Ho Chi Minh City. 3.1.3. Characteristics of some typical high-end apartment buildings in Ha Noi a- The highest selling price compared to commercial apartment segments; b- Full range of internal facilities and public services around; c- Quality of artificial landscape and classy living environment; d- Service quality and reputable building management unit; đ- The position and location of the apartment increases the living value and price; e- Customers in the segment with a lot of well-off money; 3.2. Research method and research model 3.2.1. Qualitative research methods Qualitative research methods include: Research objectives and subjects; method of sampling and deliberately applied techniques to subjects participating in interviews and group discussions. Open questions on factors related to supply and demand related to the selling price of apartments; Raising open questions related to observed variables of factors according to the opinions of interviewed subjects, comments on draft scale 1 of the thesis ...). 3.2.2. Quantitative research method Research sample: Sampling the preliminary study taken according to the rule of multiplication 5 (Hoang Trong& Chu Nguyen Mong Ngoc, 2009). The questionnaires were sent to organizations and individuals (anonymous respondents) for investigation. They are investors, owners, distribution floors, tenants, users, managers, building administrators and building management operators ... in Ha Noi. They also have different perceptions and assessments of high-end condominium prices. Data analysis software SPSS 22.0 and AMOS with the tools: Descriptive statistics; Confidence testing of research concepts; exploratory factor analysis; Factors confirmatory analysis; Correlation analysis; Regression analysis and testing of research hypotheses. 3.2.3. Qualitative research results Proposed research model and research hypotheses: Physical characteristics Apartment's position & location Factors affecting the selling price of luxury apartments Surroundings Quality of condominium management services Customer segmentation The dependent variable (target variable): perception of the selling price of a high-end apartment in Hanoi; Independent variable (factor variable): The group of internal factors belongs to real estate value (physical characteristics, location and position, surrounding environment ...); Quality of condominium management services; Demographic characteristics. Regulating variable (the factor associated with the investor): Characteristics of the investor (position and reputation in the market, investment and business capacity ...) Research theories: H1: The physical characteristics of a high-end apartment have an impact on the selling price of a high-end apartment (selling price is based on the area of meter). H2: The location of the apartment and the location of the building affect to the selling price of a high-end apartment H3: The surrounding environment affects to the selling price of a high-end apartment; H4: Service and management quality affects to the selling price of High-end apartment; H6: The investor's characteristics (position and reputation; finance, technology, management; marketing) affect to the selling price of a high-end apartment H7: High-end apartment's selling price factors have an interactive relationship Scale development: The scales of the independent and dependent variables are developed (2nd scale): 1 / The physical characteristics of the apartment include 10 component attributes; 2 / The surrounding environment consists of 10 component attributes; 3 / The location and position of the apartment include 10 component attributes; 4 / Quality of apartment management services includes 10 component attributes; 5 / Characteristics of the customer segment including 6 component attributes; 6 / The investor's characteristics include 4 component attributes and the selling price of a luxury apartment includes 3 component attributes. 3.2.3.4. Data processing The data is cleaned and processed based on SPSS software. After performing statistics to describe collected data, testing the value of the variable by exploratory factor analysis method EFA; assess the reliability of the scale by the Cronbach Alpha reliability coefficient; Verification of multivariate regression model and CFA confirmation factor analysis. - The thesis studies the impact of independent variables and control variables on the selling price of luxury apartments. Therefore, the author will analyze 2 linear regression models: Model 1 includes 05 independent variables and dependent variables. Model 2 includes 05 independent variables, 01 control variable and dependent variable. The multiple regression equation for the study is as follows: GBCHCC (1) = β1 + β1*VT + β2*VL + β3*NK + β4*MT + β5*CL GBCHCC (2) = β1 + β2*VT + β3*VL + β4*NK + β5*MT + β6*CL + β7*DT Inside: GBCHCC: Selling price of luxury apartment VT: Location of the apartment and the location of the apartment VL: Physical characteristics of the apartment MT: Ambient CL: Service quality & apartment management NK: Demographic characteristics DT: Investor's characteristics β 1: Constant β2, β3, β4, β5, β6, β7 are the regression coefficients. ε is the random error CHAPTER 4: RESULTS OF THE RESEARCH ON FACTORS AFFECTING TO THE SALE PRICE OF A HIGH-CLASS APARTMENT 4.1. Preliminary quantitative study results From the scale that has been adjusted through qualitative research, the author performed a test investigation on a sample of 130 subjects to evaluate the reliability of the scale through Cronbach Alpha coefficients. Of the 130 questionnaires collected, 115 can be used. Results of preliminary assessment (table 4.1) of specific scales are as follows: Attributes (observed variable): VL10, VT5, MT1, MT2, MT9, CL3, CL6, NK1 and NK4 have the total variable correlation coefficients less than (<) 0.3, so they are excluded. The remaining attributes have Cronbach Alpha coefficients> 0, 6, and at the same time, the observed variables have the total variable correlation coefficient> 0.3, so they are eligible to perform the next steps. Thus, after doing preliminary quantitative research and evaluating the reliability of the scale from the data obtained, some scales have changed in the number of attributes (observed variables) compared to the scale. Measurements have built up from qualitative research. The scales with the remaining observed variables were re-encoded to include in official quantitative research (table 4.3). 4.2. Official quantitative research results 4.2.1. Sample descriptive statistics Table 4.4: Characteristics of the research sample - Gender (male, female); - Age (from 18t-25; 26-30; 31-36; and over 36 years old. - Average income: (under 5 million /month; from 5-10 million; from 11 million-20 million; and over 20 million / month; - Education: Graduated from high school; College / professional high school graduate; Graduate; Graduate graduate; and other - Number of years participating in project management: less than 2 years; over 3 years, over 5 years, over 10 years The descriptive statistical results of the independent variables are presented in tables 4.5 to 4.10. The results show that the constituent attributes of the factors are highly appreciated; from 3.44 and up. For example, for the factor “Demographic characteristics”: The ability of home buyers to respond and solve problems (income) is assessed to have the strongest impact with an average score of 4,279 points; followed by Family Membership with 4,275 points; Age with 4.02 points; Education level with 3.93 points. 4.2.3. Discovery factor analysis Table 4.11: KMO's test results, Bartlett's TestKMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,897 Bartlett's Test of Sphericity Approx. Chi-Square 5.601,009 Df 406 Sig. 0,000 KMO coefficient = 0.897, satisfying the condition: 0.5 <KMO <1, discovery factor analysis is appropriate for actual data. Test the correlation of the observed variables in a representative measure Barlett test has Sig. = 0.000 <= 0.05, meaning that the representative factors and observed variables are linearly correlated, proving that the variables in the population are related to each other. Test the explanatory level of the observed variables for the factors Table 4.12: Cumulative column shows the variance extracted is 58,346%, this means that the observed variables explain 58,346% of the variation of the factors. Prove that the factor analysis research data is appropriate. Table 4.12, line 5, shows that there are 5 factors with Eigenvalues value greater than 1. Results of the EFA model Use the varimax method of the factors. The results of factor rotation times are shown in [table4.13]: Research results of factors affecting the selling price of high-end apartments according to decreasing degree. The results from table 4.13 show that load factor coefficient ≥ 0.5, proving that all component variables tend to converge (Hair et al., 2010). 4.2.4. Evaluate the reliability of the scale Independent variables: Table 4.14 shows that, the observed variables have correlation coefficients greater than 0.3 and Cronbach's Alpha coefficients greater than 0.6. Therefore, all variables are reliable and significant (Hoang Trong& Chu Nguyen Mong Ngoc, 2008). For example: The factor "Quality of condominium management services" includes 5 observed variables, with Cronbach Alpha coefficient = 0.835, and all observed variables have the total variable correlation coefficient> 0.3. Thus, this factor ensures reliability. The dependent variable "Selling price of luxury apartment": The dependent variable "Selling price of a luxury apartment" includes 3 observed variables, with Cronbach Alpha coefficient = 0,901, and all observed variables have total variable correlation> 0.3. Thus, this scale ensures reliability and significance (Hoang Trong and Chu Nguyen Mong Ngoc, 2008), as follows: Selling price of luxury apartment Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item- Total Correlation Cronbach's Alpha if Item Deleted Selling price of luxury apartment 1 7.2650 1.003 .835 .878 Selling price of luxury apartment 2 7.7626 .653 .832 .861 Selling price of luxury apartment 3 7.4171 .769 .835 .833 4.2.5. Analysis of regression model when there is no control variable EFA analysis of the scale of factors affecting the selling price of luxury apartments (GBCHCC) and the scale of the selling price of high-end condominiums of enterprises shows that there are 29 observed variables satisfying requirements classified into 5 groups of factors, including: 1 / Physical characteristics of a high-class apartment (VL) including 9 observed variables; 2 / The location of the apartment and the position of the apartment (VT) include 6 observed variables; 3 / The surrounding environment (MT) includes 6 observed variables; 4 / Quality of apartment management services (CL) includes 5 observed variables; 5 / Demographic characteristics (NK) include 4 observed variables; 6 / Investor's characteristics (DT) include 4 observed variables; 7 / The selling price of luxury apartments (GBCHCC) includes 3 observed variables (here is the perception of price for the respondents). Table 4.15. Synthesis index for multiple regression analysis Model Summary a. Dependent Variable: GBCHCC The Enter method is used to regression analysis of the factors affecting the selling price of a high-end apartment, with 5 factors of the scale being analyzed. Adjusted R2 square is used to evaluate the suitability of the model. The regression results showed that R2 was adjusted by 0.890 (the model explained 89% of the change in the GBCHCC variable). To test the suitability of the polyploid linear regression model, we use F value in the ANOVA analysis table and the data matching model with 95% confidence (the significance of F-statistic in the ANOVA is less than 0.05- through the ANOVA table). There are five factors: 1 / The physical characteristics of the apartment CCCC (VL), 2 / The location of the apartment and the location of the apartment (VT), 3 / Ambient (MT), 4 / Quality apartment management services (CL), 5/ Demographic characteristics (NK) have a positive influence on the selling price of luxury apartments (here is the perception of the price for the respondents. ) and statistically significant. The regression equation for the normalized variables is taken from the table with the significance of the partial regression coefficients in the model - Coefficientsa has the following form: GBCHCC = 0.843 + 0.156VT + 0.198MT + 0.175VL + 0.113NK + 0.174CL Test research hypotheses Based on the above results, hypotheses: H1, H2, H3, H4, H5, H6 are accepted. 4.2.6. Analysis of regression model with control variable (DT) Table 4.16. Synthesize index to analyze multiple regression factors affecting to GBCHCC a. Dependent Variable: GBCHCC b. Predictors: (Constant), CL, VT, MT, VL, NK c. Predictors: (Constant), CL, VT, MT, VL, NK, DT - When adding control variables to the study with 6 scale factors analyzed. Adjusted R square used to evaluate the suitability of the model has increased to 0.01. The regression results showed that R2 was adjusted by 0.910 (the model explained 91% of the change in the GBCHCC variable). To test the suitability of the polyploid linear regression model, we use F value in the ANOVA analysis table and the data matching model with 95% confidence (the significance of F-statistic in the ANOVA is less than 0.05 - through the ANOVA table). There are six factors: Physical characteristics of a high-end apartment (VL); The location of the apartment and the location of the apartment building (VT); Ambient (MT); Quality of apartment management services (CL); Demographic characteristics (NK); The characteristics of the investor (DT) have a positive influence on GBCHCC activities and are statistically significant (here is the perception of price for the respondents). Regression equations for normalized variables are taken from the table. The meaning of the partial regression coefficients in the model - Coefficientsa has the following form: GBCHCC = 0.299 + 0.265VT + 0.161VL + 0.190MT + 0.153NK + 0.008CL + 0.165DT Test research hypotheses Analysis results show: 1 / Physical characteristics of high-class apartment (VL); 2 / The position of the apartment and the location of the apartment (VT); 3 / Ambient (MT); 4 / Quality of apartment management services (CL); 5 / Demographic characteristics (NK); 6 / The investor's characteristics (DT) have a positive impact on the selling price of a luxury apartment (GBCHCC) and have statistical significance (P ≤ 0.05), proving that: - The physical characteristics of the apartment have a positive relationship with the selling price of a high-end apartment. - The location of the apartment and the apartment's position have a positive relationship with the selling price factors of high-end apartments. - The surrounding environment has a positive relationship with the selling price of luxury apartments; - Service quality & apartment management has a positive relationship with the selling price of luxury apartments. - The investor's characteristics have a positive relationship with the selling price of luxury apartments; - Demographic characteristics have a positive relationship with the selling price factor of luxury apartments; * The elements of the selling price of a high-end apartment are interrelated with each other. That is, hypotheses: H1, H2, H3, H4, H5, H6, H7 are accepted. Results of analysis of variance (ANOVA): Position and prestige with luxury apartment price, image and brand name with high-end apartment price, capacity and experience with high-end apartment price and Marketing and Communication Strategy for apartment price High-end apartments show no difference in the assessment results of respondents regarding position and prestige factors with the selling price of luxury apartments (due to factors with sig> 0.05). CHAPTER 5: CURRENT SITUATION AND SOLUTIONS 5.1. Reality 5.1.1. Selling price and product quality Situation: The investor's high-end apartment price is not commensurate with the quality of the apartment and building services according to the market mechanism; does not reflect the standard of an apartment building that is labeled as a luxury apartment project. Solution: To limit this, it is necessary to: (i) Approval plan on total investment and financial plan appraised / appraised by departments as the basis for construction department to issue construction license will be pasted. publicity at the project and at the office of the People's Committee where the project is located; (ii) The selling price of the investor for the first time will comply with the price list + coefficient as the public financial plan; (iii) Avoid customers who do not know about prices and brokers or investors raise prices unre