CUSTOMER SATISFACTION REAL ESTATE BROKERAGE GIA LÂM 2025

ASSESSING FACTORS AFFECTING CUSTOMER SATISFACTION WITH REAL ESTATE BROKERAGE SERVICES IN GIA LÂM DISTRICT, HÀ NỘI CITY

Nguyễn Văn Quân

Bùi Nguyên Hạnh

Nguyễn Thị Thúy Ngân

Vietnam National University of Agriculture

Abstract:

The research objective of this study is to determine the level of impact of factors affecting customer satisfaction with real estate brokerage services (REBS) in Gia Lâm District, Hanoi City. The data for the research was collected from surveys of 30 experts in the real estate brokerage sector and 130 customers who have used REBS in the district. Through the quantitative research method using SPSS20 software following these steps: scale testing, exploratory factor analysis (EFA), and linear regression. The study identified four factors affecting customer satisfaction with REBS in Gia Lâm District, namely: responsiveness, reliability, tangible means, and assurance, with impact coefficients respectively: 0.346, 0.283, 0.161, 0.132.

Keywords: Customer satisfaction, real estate brokerage services

I. INTRODUCTION

Under the influence of the rapid urban development in Vietnam, the demand for real estate transactions is increasing, especially in Gia Lâm District, Hà Nội City, which has witnessed the emergence of numerous new urban areas and has attracted thousands of people to live there in recent years. A significant number of real estate exchanges and individuals engaged in real estate brokerage are participating in real estate projects in the district (according to Thanh Vũ, 2023, Land prices in Gia Lâm District exceed 100 million VND/m2, Real Estate Investment Online Newspaper).

Based on this reality, we propose the research topic: “Assessing Factors Affecting Customer Satisfaction with Real Estate Brokerage Services in Gia Lâm District, Hà Nội City” to identify the factors influencing customer satisfaction when using real estate brokerage services, as a foundation for developing strategies to improve the quality of these services.

II. RESEARCH METHODOLOGY

The research methodology used is both qualitative and quantitative. The qualitative research was conducted by consulting 30 experts who identified 5 groups of factors with 22 criteria considered to affect customer satisfaction. Based on this, a research model and measurement scales were developed. The quantitative research was carried out using a Likert scale (5 levels) to measure the values of selected observed variables for exploratory factor analysis (EFA).

The quantification of factors affecting customer satisfaction with real estate brokerage services (REBS) includes three steps: (1) Scale testing; (2) Exploratory factor analysis (EFA); (3) Linear regression analysis.

Data for the research was collected through online survey questionnaires. According to Hair et al. (2006), the minimum sample size for using EFA is 50, preferably 100, and the ratio of observations to measurement variables is 5:1. Specifically, the proposed research model has 22 observed variables. Thus, the minimum sample size for the study is 22 x 5 = 110 samples. In practice, the research was conducted by surveying 130 customers during the period from March 2024 to April 2024. Therefore, the data collected ensures the effective implementation of the research model.

Figure 1. Proposed Research Model

Reliability (X1)	Customer satisfaction (CN)	Control variables: X6: Age (over 35) X7: Gender (Male) X8: Income (over 30 million VND) X9: Education level (Postgraduate)
Tangible means (X2)
Assurance (X3)
Responsiveness (X4)
Empathy (X5)

CN=f(X1, X2, X3, X4, X5, X6, X7, X8, X9)

III. RESEARCH RESULTS AND DISCUSSION

Reliability Assessment of the Scale (Cronbach Alpha Test)

The reliability of the scale measuring customer satisfaction with real estate brokerage services (REBS) was tested for 22 variables belonging to 5 factors. The Cronbach’s Alpha coefficient > 0.6 indicates that the scale meets the reliability criteria for conducting the research (according to Nunnally Bernstein, 1994). It was found that the factor correlation coefficient is > 0.3, thus the 22 observed variables are significant and adequately explain the factors.

Table 1. Results of Reliability Assessment of the Scale

Code	Content	Factor Correlation	Cronbach’s Alpha if Item Deleted
(DU) Responsiveness: Cronbach’s Alpha is 0.776
DU1	Always ready to serve	0.536	0.744
DU2	Ability to handle arising issues quickly	0.626	0.697
DU3	Meeting customer requirements	0.601	0.711
DU4	Diverse sources of goods	0.555	0.735
(TC) Reliability: Cronbach’s Alpha is 0.853
TC1	Reasonable transaction fees	0.705	0.812
TC2	Providing reliable information	0.716	0.809
TC3	Company always fulfills commitments to customers	0.686	0.817
TC4	Good customer information confidentiality	0.619	0.834
TC5	Providing services on time	0.599	0.839
(CT) Empathy: Cronbach’s Alpha is 0.794
CT1	Empathy with customers	0.661	0.701
CT2	Caring for customers	0.691	0.662
CT3	Understanding customers	0.577	0.782
(HH) Tangible Means: Cronbach’s Alpha is 0.835
HH1	Comfortable working environment for customers	0.698	0.783
HH2	Human resources meeting customer requirements	0.562	0.820
HH3	Facilities meeting customer requirements	0.721	0.775
HH4	Legal status of the brokerage company	0.663	0.793
HH5	Communication materials suitable for customers	0.536	0.827
(BD) Assurance: Cronbach’s Alpha is 0.856
BD1	Professional brokerage services	0.778	0.796
BD2	Brokers have good attitudes	0.752	0.805
BD3	Brokers have high professional knowledge	0.709	0.817
BD4	Brokers grasp market prices	0.731	0.809
BD5	Brokers have good communication skills	0.397	0.887
(Dependent Variable CN) Satisfaction: Cronbach’s Alpha is 0.852
CN1	I feel comfortable and secure using REBS	0.716	0.799
CN2	I will continue to use REBS	0.717	0.797
CN3	I will recommend friends and family to use REBS	0.733	0.783

Exploratory Factor Analysis

The results of the first exploratory factor analysis showed that the variable BD5 did not converge in the BD group but rather in the CT group. We moved BD5 to the CT group, renamed it CT4 (employees with good communication skills), and reran the analysis. The second results with the tests ensured the following: The reliability of the observed variables > 0.5; KMO model adequacy test = 0.88 (within the range of 0.5 to 1); Bartlett’s test of sphericity for correlation among observed variables Sig = 0.00 < 0.05; Cumulative variance test = 66.64% > 50%.

Table 2. Factor matrix after rotation

Code	Observed Variables	Factor
Code	Observed Variables	1	2	3	4	5
DU1	Always ready to serve				0.648
DU2	Ability to handle arising issues quickly				0.771
DU3	Meeting customer requirements				0.748
DU4	Diverse sources of goods				0.798
TC1	Reasonable transaction fees	0.709
TC2	Providing reliable information	0.757
TC3	Company always fulfills commitments to customers	0.781
TC4	Good customer information confidentiality	0.694
TC5	Providing services on time	0.653
HH1	Comfortable working environment for customers		0.680
HH2	Human resources meeting customer requirements		0.611
HH3	Facilities meeting customer requirements		0.790
HH4	Legal status of the brokerage company		0.681
HH5	Communication materials suitable for customers		0.663
BD1	Professional brokerage services			0.755
BD2	Brokers have good attitudes			0.851
BD3	Brokers have high professional knowledge			0.819
BD4	Brokers grasp market prices			0.687
CT1	Empathy with customers					0.633
CT2	Caring for customers					0.718
CT3	Understanding customers					0.773
CT4	Good communication skills					0.608

The results identified five groups of factors affecting customer satisfaction, namely: reliability (X1), tangible means (X2), assurance (X3), responsiveness (X4), empathy (X5).

Linear Regression Analysis

The research team conducted a regression model analysis, where the independent variables X1, X2, X3, X4, and X5, along with additional variables X6, X7, X8, and X9, influence customer satisfaction (the dependent variable is Customer Satisfaction).

Table 3. Results of Linear Regression Analysis

Factor	Beta Coefficient	Standardized Beta Coefficient	VIF
Constant α	0.040
X1: Reliability	0.312 (0.00)	0.283	1.712
X2: Tangible Means	0.145 (0.11)	0.132	1.970
X3: Assurance	0.161 (0.04)	0.161	1.772
X4: Responsiveness	0.406 (0.00)	0.346	1.239
X5: Empathy	-0.092 (0.34)	-0.083	2.134
X6: Age over 35	0.266 (0.14)	0.131	2.299
X7: Male	-0.332 (-0.00)	-0.162	1.076
X8: Income over 30 million	-0.338 (-0.12)	-0.096	1.112
X9: Postgraduate	0.262 (0.12)	0.128	1.970
Adjusted R²	55.6%
Sig. F Coefficient	0.000

The regression analysis results of the model show that the R2 coefficient = 55.6%. The Durbin-Watson coefficient of the model is within the range of 1.5 to 2.5, indicating no autocorrelation (Yahua Qiao, 2011). The Variance Inflation Factor (VIF) of the variables in the model is less than 10, so we conclude that there is no multicollinearity (Mai, 2008).

Based on the regression analysis results, with 90% confidence, the factors affecting customer satisfaction from largest to smallest are: responsiveness, reliability, assurance, tangible means, and empathy does not affect customer satisfaction with REBS.

The standardized regression equation of the model is:

CN = 0.346*DU + 0.283*TC + 0.161*BD + 0.132*HH

The regression analysis results indicate a 90% confidence level that there are differences in satisfaction between male and female customers using REBS. Female customers have higher satisfaction levels than male customers when using REBS. The results do not confirm differences in satisfaction based on income, education level, and age when using REBS.

IV. CONCLUSION

The research results have achieved the set objective of identifying factors affecting customer satisfaction with real estate brokerage services (REBS) in Gia Lâm District, Hà Nội City. The results have identified factors affecting customer satisfaction, namely: responsiveness, reliability, assurance, tangible means, and customer gender. The factor with the most substantial impact on customer satisfaction is responsiveness. This serves as a basis for managers, business leaders, and company executives to develop strategies to improve service quality and meet customer expectations when using REBS.

References

Hoàng Trọng and Chu Nguyễn Mộng Ngọc, 2008. “Data Analysis with SPSS,” Volume 1-2. Hồng Đức Publishing House.
Nguyễn Quốc Nghi, Nguyễn Thị Bảo Châu, Trần Thị Diễm Cần, Nguyễn Thị Đinh Phượng (2012). “Factors Affecting Customer Satisfaction with Real Estate Consultancy and Brokerage Services,” Journal of Science, Ho Chi Minh City Open University, Issue 7.
Parasuraman, Zeithaml, and Berry (1985). “A conceptual model of service quality and its implications for future research,” Journal of Marketing, Vol. 49: 41-50.
Parasuraman, Zeithaml, and Berry (1988). “Servqual: A Multi-Item Scale for Measuring Consumer Perception of Service Quality,” Journal of Retailing, Vol 64, No 1.
Parasuraman, Zeithaml, and Berry (1991). “Refinement and reassessment of Servqual scale,” Journal of Retailing, Vol.67: 420-50.

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