Price Determinants and GIS Analysis of the Housing Market in Vietnam: The Cases of Ho Chi Minh City and Hanoi

Optimization of United States Residential Real Estate Investment through Geospatial Analysis and Market Timing

In this study, we examined the long-term spatial patterns and trends of home values within the United States from 1996 to 2019. The Zillow Home Value Index (ZHVI) data were obtained from the Zillow's housing data portal. The overall trends indicated both coasts of the United States having the highest concentration of hotspots. The ideal time to sell varied seasonally across the country. We used geo-statistical analysis techniques, such as cluster analysis and emerging hot spot analysis (EHSA), to reveal the average and long-term trends in spatial patterns of home values. Washington was the only state with sporadic hot spots. The Western United States showed consecutive hotspots, most notably in California, but in surrounding states as well. The Northeast, Mid-Atlantic, and Florida were dominated by oscillating hotspots. Texas and the Southeast display new hotspots that signal change, indicative of southward migration of population. Finally, the Midwest has been a historical cold spot, but Cleveland has improved to a diminishing cold spot, pointing to the revitalization of the region. The seasonal level analysis displayed southern and coastal states as those benefiting most from winter home sales, and the colder northern states captured the most value and sold quicker in the summer months. This intuitive analysis of the country's variation in ideal sale month reveals a local view of when to sell rather than a generalized view of the entire United States.

The Potential of GIS Tools for Diagnosing the SFS of Multi-Family Housing towards Friendly Cities—A Case Study of the EU Member State of Poland

Motives: The need for sustainable urban development, including an improvement in residents’ quality of life, requires ongoing urban diagnostics. Assessments of multi-family housing estates play a very important role in this process. Population growth influences the expansion of housing estates in limited urban space. The extent to which spatial and functional structures (SFS) in housing developments meet the residents’ current needs should be evaluated. These needs undergo dynamic change and are influenced by economic, socio-cultural, sanitary, and ecological factors. Aim: The main objective of this study was to develop a methodology for assessing SFS solutions in open spaces in multi-family residential estates (MFREs) based on a complete list of SFS indicators, and to determine the potential of GIS tools and selected open data sources for automating this process. GIS was used to represent data. The intermediate goal was to determine differences in the SFS solutions of two MFREs that were built with different technologies and urban layouts in the last 70 years in the city of Olsztyn (Poland). Methods: An empirical study was conducted with the use of qualitative and quantitative methods based on a review of the literature, the results of a resident survey, and an analysis of spatial data in ArcGIS and QGIS software. Results: The residents’ needs for SFS in MFREs were identified. A list of 26 SFS indicators and their values (on a 3-point scale) was developed to assess multi-family housing. The applicability of GIS software and spatial data from the national spatial data infrastructure (NSDI) and other sources was assessed in the process. The research method was tested to reveal differences in SFS solutions in the compared MFREs.

Impact of Induced Seismicity on the Housing Market: Evidence from Pohang

In this study, we analyze the case of induced seismicity in Pohang, South Korea, in 2017 to investigate the effect of seismic risk perception on the local residential property market. Based on a hedonic pricing model with a difference-in-differences method, we examine the geographic distribution of the effects of unexpected earthquake hazards. Our results indicate an overall reduction in local property values, but the magnitudes of negative externality for housing prices decrease with respect to the distance from the epicenter. In areas within 3 km of the epicenter, the asset value reduced by approximately 20% after an earthquake event, but if the distance from the epicenter was higher than 12 km, the negative effect on the price was not significant. In addition, we examine how the experience of seismic events affect the preference on the anti-seismic building structure. The results show that the market valuation on the anti-seismic system significantly escalated after the earthquake.

The Delphi method to identify attributes for a valuation approach for residential property exposed to flood risk

Purpose

This study is aimed to identify the attributes for a valuation approach of flood risk exposure, in particular for residential property. With frequent flood events in Malaysia, there is a need for valuation methods to evolve and represent the increased risk of natural disasters.

Design/methodology/approach

This study employed the Delphi method which is a systematic and interactive research technique in obtaining variables for a valuation approach for residential property exposed to flood risk.

Findings

Results from the Delphi method revealed four categories of attributes, namely environmental, locational, structural and economical.

Originality/value

The findings from this research will transform the valuation approach in Malaysia to identify the value of residential property exposed to flood risk. The determination of variables will represent the current risk in valuations, especially for residential property in flood-prone areas.