Assessment of Living Environment in Tama New Town Based on Factors in Real Estate Prices

2006 ◽  
Vol 41 (0) ◽  
pp. 114-114
Author(s):  
Aya NAKABAYASHI ◽  
Eiji SATOH ◽  
Tohru YOSHIKAWA
Author(s):  
Nguyen Van Binh ◽  
Ho Nhat Linh ◽  
Tran Thi Anh Tuyet

This study focuses on determining the impact of factors on property prices in Hue city, Thua Thien Hue province. The study used quantitative and qualitative analysis in SPSS to statistically characterize the investigated subjects; using Likert scale with five levels and regression method to evaluate the influences of relevant factors on real estate; surveying 115 samples in 03 wards of An Tay, An Cuu and An Dong of Hue city. The results showed that, 6 factors affecting real estate prices were identified, including: (i) Location, (ii) Topographic and shape, (iii) Legal, (iv) Social factors, (v) Infrastructure and (vi) Environment. The impact level of 6 factors on real estate prices are: Environment (0.416), Terrain (0.408), Location (0.225), Infrastructure (0.197), Legal (0.195) and Social factors (0.120). For factors affecting real estate prices, depending on the type of street that the factors affecting real estate prices have different roles. For streets with good business potential, the important factor is that the location of the land plot provides high profitability and stability leading to high buyer demand, followed by parcel shape factors, infrastructure conditions, living environment. The main purpose of a street to build houses is the natural environment, social factors, infrastructure, followed by shape and area. Among the 3 surveyed wards, An Cuu ward had the highest real estate price; followed by An Dong and An Tay wards.


2013 ◽  
Author(s):  
Andrew Narwold ◽  
Stephen J. Conroy ◽  
Dirk Yandell

2021 ◽  
Vol 13 (4) ◽  
pp. 2236
Author(s):  
Francesco Riccioli ◽  
Roberto Fratini ◽  
Fabio Boncinelli

Using spatial econometric techniques and local spatial statistics, this study explores the relationships between the real estate values in Tuscany with the individual perception of satisfaction by landscape types. The analysis includes the usual territorial variables such as proximity to urban centres and roads. The landscape values are measured through a sample of respondents who expressed their aesthetic-visual perceptions of different types of land use. Results from a multivariate local Geary highlight that house prices are not spatial independent and that between the variables included in the analysis there is mainly a positive correlation. Specifically, the findings demonstrate a significant spatial dependence in real estate prices. The aesthetic values influence the real estate price throughout more a spatial indirect effect rather than the direct effect. Practically, house prices in specific areas are more influenced by aspects such as proximity to essential services. The results seem to show to live close to highly aesthetic environments not in these environments. The results relating to the distance from the main roads, however, seem counterintuitive. This result probably depends on the evidence that these areas suffer from greater traffic jam or pollution or they are preferred for alternative uses such as for locating industrial plants or big shopping centres rather than residential use. Therefore, these effects decrease house prices.


Sign in / Sign up

Export Citation Format

Share Document