Abstract:Since the Doi Moi policy of economic reform in 1986, Vietnam has experienced economic development and housing market growth with increasing foreign direct investment. While high-end apartment development has dominated since the emergence of the privatized housing market, more recent focus is on the affordable apartment segment with the remarkable surge of middle-income households in Ho Chi Minh City (HCMC). While most previous studies have analyzed housing price determinants based on locational classification, this study is based on the affordability framework of the housing market in HCMC. It aims to investigate the price determinants of affordable and unaffordable apartment units using the hedonic regression model. The study identified common factors between the two types of apartments, such as vertical shared access and proximity to downtown, as well as unique factors for each, such as more high-rise towers, foreign development, proximity to main roads, and shopping malls only for the affordable segments. The findings have valuable implications, not only for future investors and developers in setting up successful housing development strategies, but also for the public sector in strongly encouraging public-private partnerships for sustainable housing development in Vietnam.

Since the introduction of the Doi Moi economic reform in 1986, the real estate market in Vietnam has witnessed a sharp increase in foreign investment inflows and a remarkable growth in the housing market, particularly for high-rise apartments in large cities. This study investigates the determinants of apartment prices in Ho Chi Minh City (HCMC) and Hanoi, the two most representative cities in Vietnam. The spatial distribution of apartments and their price determinants were addressed by the spatial analysis of Geographic Information System (GIS) and the hedonic model. The price determinants of both cities were closely associated with downtown-related factors; moreover, the externalities of urbanization affected each city. While HCMC was more related to the locational attributes of urban amenities and community density as well as programs because of unmanaged urbanization, Hanoi was more related to housing attributes, since the majority of apartment projects were developed under urban infrastructure development supported by the central government. Apartment cluster maps of each city clearly show the contrast of housing distribution. Our findings clarify the impact of government policies on housing price determinants and can be a reference for private-and public-sector stakeholders seeking to undertake economically and socially sustainable housing development projects in Vietnam.

This study investigates the integration of methods for real estate development planning and feasibility studies in the changing business environments of emerging big-data. It examines high-rise mixed-use development projects for the highest best use by combining fuzzy theory; thus, it identifies a big data-based innovative decision-making method for systemizing the various factors expected to influence real estate development. In this context, the study creates new evaluation fields and factors by integrating both conventional and big-data based high-rise mixed-use projects. The weight of each value was calibrated by relative significance and fuzzy measure using the Analytic Hierarchy Process (AHP) method. A measuring technique that applies analysis methodology to the evaluation areas was developed for more objective and clearer evaluation, and its application in the field was proposed. Evaluators can systematically assess the concerned evaluation areas during development project planning by examining the process. The findings also provided implications for the evaluation system’s operation by reflecting the variability of specific conditions of the varying projects in real estate and urban and land use planning.

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