Empirical Analysis Using a Hedonic Model of High-End Apartment Pricing

This study identifies and analyzes factors influencing the sale prices of high-end apartments in Nam Tu Liem District, Hanoi City, from 2022 to 2024. Using direct surveys of 350 residents in June 2024 and multivariate regression analysis, six statistically significant factors were identified: developer's competency, location, surrounding environment, physical characteristics of the apartments, service quality, and market conditions. The research employed reliability testing using Cronbach’s Alpha, exploratory factor analysis (EFA), and multivariate regression analysis to ensure accurate identification of influencing variables. The research results indicate the degree of influence of each factor on high-end apartment prices as follows: Location has the greatest impact with a Beta coefficient of 0.391, followed by Physical Characteristics of Apartments with a Beta of 0.335, and Service Quality with a Beta of 0.259. Surrounding Environment has a Beta of 0.084, while Developer Competency and Market Conditions have the lowest impact, with Beta coefficients of 0.078 and 0.057, respectively. The empirical evidence derived from this study provides practical implications for real estate companies and businesses, enabling them to formulate more effective policies for real estate operations and management.

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Publication Details

Journal
International Journal of Engineering
Published
2025-01-01
DOI
https://doi.org/10.5829/ije.2025.38.10a.18
Primary Topic
Housing Market and Economics
Type
article
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article

Empirical Analysis Using a Hedonic Model of High-End Apartment Pricing

Phạm Anh Tuấn, Tae-Hwan Son, Dang Duy Khanh
International Journal of Engineering
Housing Market and Economics
article

Empirical Analysis Using a Hedonic Model of High-End Apartment Pricing

Phạm Anh Tuấn, Tae-Hwan Son, Dang Duy Khanh
article en

Abstract

This study identifies and analyzes factors influencing the sale prices of high-end apartments in Nam Tu Liem District, Hanoi City, from 2022 to 2024. Using direct surveys of 350 residents in June 2024 and multivariate regression analysis, six statistically significant factors were identified: developer's competency, location, surrounding environment, physical characteristics of the apartments, service quality, and market conditions. The research employed reliability testing using Cronbach’s Alpha, exploratory factor analysis (EFA), and multivariate regression analysis to ensure accurate identification of influencing variables. The research results indicate the degree of influence of each factor on high-end apartment prices as follows: Location has the greatest impact with a Beta coefficient of 0.391, followed by Physical Characteristics of Apartments with a Beta of 0.335, and Service Quality with a Beta of 0.259. Surrounding Environment has a Beta of 0.084, while Developer Competency and Market Conditions have the lowest impact, with Beta coefficients of 0.078 and 0.057, respectively. The empirical evidence derived from this study provides practical implications for real estate companies and businesses, enabling them to formulate more effective policies for real estate operations and management.

International Journal of EngineeringVol. 38(10)
Saint Petersburg Mining University (RU), Hanoi University of Natural Resources and Environment (VN)
Openalex Percentile: Top 90%
Housing Market and Economics
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