Influence of POI Accessibility on Temporal–Spatial Differentiation of Housing Prices: A Case Study of Hangzhou, China

Zhang, Ling; Shi, Dingyin; Zhu, Lifei; Wen, Haizhen

doi:10.1061/(asce)up.1943-5444.0000878

Cited by 5 publications

(2 citation statements)

References 39 publications

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“…The shortest distance between the block center and the urban center and the secondary commercial center [36] Traffic Number of bus and metro stations within the block [24] Landscape Sum of the shortest path between the block center and two large landscapes [37] Employment Number of government offices, public institutions and commercial buildings within the block [24] Supporting services…”

Section: Central Areamentioning

confidence: 99%

Heterogeneity, Differentiation Mechanisms and Social Effects of Urban Residential Space in China’s Large Cities: A Case Study of Wuhan

Cai,

Shen

2024

Land

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Different choices of living space for urban residents are concrete reflections of a social class divide. Emerging residential space differentiation is a critical issue in Chinese cities. This paper aims to explore the current situations and mechanisms of residential spatial differentiation, and reveal its social responses in Chinese cities. Taking Wuhan, the largest city in central China, as an example, this research divides the residential space based on social resource structures. It analyzes and compares spatial differentiation and influencing factors of different residential areas and houses with different prices in Wuhan by spatial differentiation indicators and geographic detector. The results show that residential areas are divergent due to differences in urban resource spatial structure, with few and concentrated high-quality residential areas. The spatial differentiation level of different residential areas also varies, with central location, landscape, educational resources, and other dominant scarce resources being the key to residential spatial differentiation in most of China’s big cities. In addition, residential spatial differentiation can lead to issues including housing wealth inequality, resource deprivation, and class identity solidification. In the end, this paper puts forward policy implications on alleviating residential spatial differentiation and optimizing allocation of residential resources.

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Section: Central Areamentioning

confidence: 99%

Heterogeneity, Differentiation Mechanisms and Social Effects of Urban Residential Space in China’s Large Cities: A Case Study of Wuhan

Cai,

Shen

2024

Land

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“…Wang et al, 2020; Zhao et al, 2018), and the law of spatial differentiation between economic development and price levels (Y. Liu & Fang, 2022; Wu et al, 2020; Xing & Ye, 2023; Yu et al, 2023; L. Zhang et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Spatial Pattern and Driving Mechanism of Urban Taxi Fares in China

Wenkang,

Jie

2024

Sage Open

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Taxi fare is related to the daily life of residents. Reasonable taxi fare not only meets the travel demand of residents but also improves the income of drivers and promotes employment. The spatial variation of taxi fares exists between different regions and cities. Previous studies on taxi fares have been conducted mostly in individual cities, and there has been no study on the spatial differentiation pattern of taxi fares on a national scale. Taking 336 cities across China as the research object, a multiple linear regression model of taxi fares was established by demonstrating the spatial variation pattern of taxi fares, the global differentiation index, spatial autocorrelation analysis, and kernel density analysis, etc. The significance of the study is to explore the law of spatial differentiation of taxi fares in China and to provide a stenographic record of taxi fare adjustment. The results show that: (1) the spatial variation of taxi fares across the country is significant, with the starting taxi fare range being between RMB 4 and RMB 14. (2) The global differentiation index of taxi fares is large, with two low-low clusters and three high-high clusters appearing spatially, and the results of the kernel density analysis surface a dispersion distribution centered on provincial capitals. (3) The divergence pattern of taxis nationwide is influenced by several factors. A multiple linear regression model is selected to establish a multiple linear regression model of urban disposable income per capita, regional GDP, urbanization rate, and urban population density, which shows that urban disposable income per capita has the greatest influence on taxi fares. The model shows that urban disposable income per capita has the greatest influence on taxi fares, and the fare of a 5 km taxi ride is 6.07. Taxi fares have a clear pattern of spatial differentiation in China and are most affected by urban disposable income per capita. Through this study, we can gain a deeper understanding of the variation in taxi fares across the country and provide data and theoretical support for the rationality of taxi fare adjustments.

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Influencing factors and spatial differentiation of rental housing in a smart city: A GWR model analysis

Zhao,

Zhong,

2024

Measurement: Sensors

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Influence of POI Accessibility on Temporal–Spatial Differentiation of Housing Prices: A Case Study of Hangzhou, China

Cited by 5 publications

References 39 publications

Heterogeneity, Differentiation Mechanisms and Social Effects of Urban Residential Space in China’s Large Cities: A Case Study of Wuhan

Heterogeneity, Differentiation Mechanisms and Social Effects of Urban Residential Space in China’s Large Cities: A Case Study of Wuhan

Spatial Pattern and Driving Mechanism of Urban Taxi Fares in China

Influencing factors and spatial differentiation of rental housing in a smart city: A GWR model analysis

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