Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

Liu, Lingbo; Yu, Honghui; Zhao, Jie; Wu, Hao; Peng, Zhenghong

doi:10.3390/ijgi11010057

Cited by 32 publications

(14 citation statements)

References 47 publications

(63 reference statements)

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“…It concluded that hospitals have a positive influence on the price of surrounding houses. Liu et al (2022) compared the multi-scale effects of accessibility to various facilities on housing prices and demonstrated that hospitals have a positive influence on housing prices, indicating that the closer the proximity, the higher the housing prices.…”

Section: Variability In the Results Of The Influence Of Hospital Acce...mentioning

confidence: 99%

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Chen

Lin²,

Cao³

et al. 2022

Front. Environ. Sci.

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This study investigates the interaction between the accessibility of various urban public facilities and the price of urban space by analysing the influence of urban hospitals and rail accessibility on housing prices. In recent years, with the development of social civilisation and the influence of COVID-19, people have become increasingly interested in the quality of hospitals in their living environment. This makes medical convenience (hospital accessibility) a crucial element in determining housing prices. At the same time, people regard rail as one of the important means to access hospitals. Therefore, demonstrating the intrinsic value of accessibility to hospitals and rail in residential areas is essential. As a point of reference, this paper presents an empirical analysis of Fuzhou, Fujian Province, China, a city in a developing nation with relatively widespread access to hospitals during a significant rail construction period. The study demonstrates the interaction between hospital and rail accessibility and their moderate influence on housing prices, which is geographically heterogeneous. The study also determines the optimal metric model for assessing geographical interaction based on the significance and stability of the interaction in geographic space. It concludes with a discussion of the findings and social recommendations.

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Section: Variability In the Results Of The Influence Of Hospital Acce...mentioning

confidence: 99%

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Chen

Lin²,

Cao³

et al. 2022

Front. Environ. Sci.

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“…e house age, floor area ratio, and distance to subway stations commonly show negative effects [44,45].…”

Section: Discussionmentioning

confidence: 99%

Classification of Housing Submarkets considering Human Preference: A Case Study in Shenyang, China

Liu

Guo

Lei

et al. 2022

Mathematical Problems in Engineering

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Housing submarket is affected by the quality of public facilities in neighborhood. In this article, a three-step framework is proposed to classify the housing market in Shenyang city, China. The saliences of point of interest, POI, are used to quantify the degree of activities using social media data and merged into the model of density-field hotspot detector to extract high-quality of urban facilities, aiming at exploring the influences on the housing price. The multiscale geographically weighted regression model, MGWR, is applied to investigate relations between the housing price and attribute variables geographically and to identify multiscale impacts on the housing price with flexible bandwidths. The spatial “k”luster analysis by the tree edge removal method, SKATER, is applied to delimit urban housing submarkets based on the MGWR betas, where ten groups of the housing submarkets are recognized. The proposed classification method captures multiscale spatial heterogeneity of the housing price and predominant influencing factors for each housing submarket in Shenyang, China. It also offers suggestions for urban planners to restrain the unbalanced development of the housing market.

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“…This observation of spatial heterogeneity is consistent with a recent study that suggested that residents of downtown and suburban areas may value different spatial characteristics [61]. With regard to schools as an influencing factor, the general view of previous studies is that all types of schools increase house prices in surrounding residential neighborhoods [62], while some scholars argue that only elementary and junior high schools are globally correlated with house prices [63], and there is also a recent study that used MGWR to analyze house prices in Wuhan and showed that only junior high schools and kindergartens are positively correlated, and elementary schools are negatively correlated [64]. The results of this paper differ from previous studies in that elementary schools and junior high schools are negatively correlated with house prices in high-house-price areas and are one of the main factors affecting the sale price of housing in the area: the closer to the school, the higher the house price.…”

Section: Spatial Distribution and Discrete Heterogeneity Of Commercia...mentioning

confidence: 99%

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

Wang

Zhao

Zhang

2022

IJGI

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Geographically weighted regression (GWR) is an effective method for detecting spatial non-stationary features based on the hypothesis of proximity correlation. In reality, especially in the social and economic fields, research objects not only have spatial non-stationary characteristics, but also spatial discrete heterogeneity characteristics. Therefore, how to improve the accuracy of GWR estimation in this case is worth studying. In this paper, a regionally geographically weighted regression (RGWR) is proposed. Using incoming dummy variables, the zoning discrimination is added to the spatial kernel function of GWR, the spatial kernel function is modified, the spatial weight is optimized, and the influence of “near heterogeneous” observation points is reduced. In this paper, the residential sale price in Wuhan City is taken as an example in the analysis of three aspects: model performance, fitting effect and influencing factors. The results show that the introduction of a zoning dummy variables can significantly improve the model accuracy of a fixed bandwidth and adaptive bandwidth. Under a fixed bandwidth, compared with the GWR model, RGWR increases R2 and R2adj from 0.6776 and 0.6732 to 0.777 and 0.7746, respectively, and the Akaike information criterion, corrected (AICc) standard decreases by 37.4006 compared with GWR, which proves the effectiveness of the method.

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Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

Cited by 32 publications

References 47 publications

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Classification of Housing Submarkets considering Human Preference: A Case Study in Shenyang, China

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

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