Andreas, (2008) presents five factors that are hindering the implementation of a

value-based pricing strategy. Nigel & partners (2010) show that the need for managers to take

a more strategic view of prices and test the possibility of price increases, especially in postcrisis situations. Stephan & Andreas (2013) find a positive relationship between value-based

pricing (not competitive pricing) and corporate performance.

Studies using Hedonic models such as Griliches (1971), Thibodeau and Malpezzi

(1980) . According to Malpezzi (2003), during the development process, the housing market

is one of the widely used the model valuation of Hedonic ; because housing is a

heterogeneous commodity; At the same time, consumers' demand is also different such as: an

apartment includes many separate factors in terms of area, quality, finishing materials .

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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

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