Which types of shopping malls affect housing prices? From the perspective of spatial accessibility

Zhang, Ling; Zhou, Jiantao; Hui, Eddie C.M.

doi:10.1016/j.habitatint.2020.102118

Cited by 36 publications

(11 citation statements)

References 61 publications

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“…Mixed-use significantly affects the price of traffic adjacent to the housing, and rail transit accessibility has a higher value-added effect that is more likely to occur where land use is more mixed. Zhang et al (2020b) used the gravity model. They concluded that the spatial accessibility of shopping malls has a significant positive effect on housing prices throughout the city.…”

Section: Environmental Dimensionsmentioning

confidence: 99%

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Jotikasthira

2022

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PurposeThis paper aims to explore the factors that affect housing prices as per Chinese articles indexed in the Chinese Science Citation Database (CSCD). There were different foci regarding what drove housing prices in China in Chinese articles, and international journal articles in English. As most previous English articles only threw light on international research, it motivated the researchers to systematically review Chinese literature’s factors that affected housing prices in China.Design/methodology/approachThis paper reviewed housing price research articles indexed in the two largest Chinese academic research databases: the CSCD and China Knowledge Infrastructure Engineering Database (CNKI.NET). It systematically collected the data and adopted descriptive analysis techniques and synthesis.FindingsThis research reviewed the literature published from 2015 to 2020 and revealed some unique factors affecting China's housing prices. For example, research focused on administrative aspects such as macroeconomic regulation and control (often known as macro control). Authors of Chinese articles suggested that the two-child policy affected housing prices, which differed from that in the English journal articles. The research results implied that researchers should read top Chinese journals on top of good international journals when they study China's real estate market in the future.Research limitations/implicationsBecause the domestic real estate market started late, domestic real estate transaction data and real estate-related statistics are more difficult to obtain. The research is mostly based on the relationship between supply and demand, government policy and individual consumer factors, and the sample has a short time span.Practical implicationsAs China is a planned economy country, administrative factors are one main factor that affects the housing price. There were a significant number of articles in Chinese that considered this factor to be the main driver of the real estate price. It included government investment and macro-control, i.e. direct government intervention to cool down the overheated economy. Yet, there are few English articles that threw light on this factor including the commodity housing supply and government behaviour that affect housing price. The second-child policy, which is unique in China, also played an important role in the determination of the housing price. In the articles indexed in CNKI, the second-child rate, willingness to have a second child or having a second child were mentioned in the Chinese articles but not the English ones.Social implicationsIn this paper, the economic, social, administrative and environmental factors were summarised, which basically covered all the factors affecting housing prices. The administrative factors were a special group of factors that affect the housing price because of the country's planned economic system. Secondly, it provided useful information to real estate development enterprises in China. To make a correct investment and management decision, real estate development enterprises must understand the actual situation and possible problems of the industry. In this study, we analysed the research literature on the real estate industry in China for the period from 2015 to 2020 one by one and determined the influencing factors of the housing price, which provided references for effective cost control. Thirdly, it allows the public to understand and grasp the real estate industry. As the housing price has been continuously increasing, the public pays increasing attention to the real estate industry. Through the literature analysis of the impact of real estate prices, this paper revealed the elements of house price expenses, which makes it convenient for ordinary people to understand the real estate industry.Originality/valueThis study allows foreigners who do not know Chinese to know more about factors that drove housing prices from the Chinese perspective. It also provides insights to overseas developers who wish to enter the property market in China. The results can be generalised to other non-English-speaking real estate research.

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Section: Environmental Dimensionsmentioning

confidence: 99%

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Jotikasthira

2022

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“…The density radius was set to 1 km after optimisation. We used Euclidean distance for all the locational attributes due to its straightforwardness, which is also a popular measurement in similar housing studies [37][38][39]. Drum Tower, a famous historic site located in the city centre, was set up as the only CBD.…”

Section: Factors For 2d and 3d Modelsmentioning

confidence: 99%

“…Based on the theories proposed by Rosen [7] and Lancaster [8], the hedonic price model (HPM) has been widely recognised as a consistent and general theoretical basis in current literature to estimate property values by deconstructing the property characteristics into different attributes [37,43]. The fundamental concept is that the property is regarded as a heterogeneous product, whose value consists of a complex variety of attributes (e.g., environmental, physical and locational attributes) [44,45].…”

Section: Statistical Models For 2d: Ols and Gwrmentioning

confidence: 99%

Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China

Ying

Koeva

Kuffer

et al. 2020

Land

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Recent rapid population growth and increasing urbanisation have led to fast vertical developments in urban areas. Therefore, in the context of the dynamic property market, factors related to the third dimension (3D) need to be considered. Current hedonic price modelling (HPM) studies have little explicit consideration for the third dimension, which may have a significant influence on modelling property values in complex urban environments. Therefore, our research aims to narrow the cognitive gap of the missing third dimension by assessing both 2D and 3D HPM and identifying important 3D factors for spatial analysis and visualisation in the selected study area, Xi’an, China. The statistical methods we used for 2D HPM are ordinary least squares (OLS) and geographically weighted regression (GWR). In 2D HPM, they both have very low R2 (0.111 in OLS and 0.217 in GWR), showing a very limited generalisation potential. However, a significant improvement is observed when adding 3D factors, namely view quality, sky view factor (SVF), sunlight and property orientation. The obtained higher R2 (0.414) shows the importance of the third dimension or—3D factors for HPM. Our findings demonstrate the necessity to include such factors into HPM and to develop 3D models with a higher level of details (LoD) to serve more purposes such as fair property taxation.

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“…Accordingly, this paper studies the spatial accessibility of facilities, which is the main focus of existing research on accessibility. Accessibility measurement can be combined with various research projects on society and the humanities, and also can serve as input data to aid evaluation of other indicators, for example, the influence of shopping facility accessibility on housing prices [11,12], decisions on store location based on accessibility [13], the relationship between the accessibility of shops and place attractiveness [14], and the impact of accessibility on social space equity [15]. Thanks to the significant role of accessibility research in various fields, spatial accessibility research methods have gradually developed involving the cumulative model [16], gravity model [17], proximity model [18,19], the kernel density method [20], and their deformation and extension.…”

Section: Introductionmentioning

confidence: 99%

Measuring Cluster-Based Spatial Access to Shopping Stores under Real-Time Travel Time

Qin

Luo

et al. 2022

Sustainability

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Shopping stores are an important part of retail facilities and indispensable public facilities in a city. They are not only concentrated in shopping malls, but also distributed independently throughout the city, and often agglomerated in space. This paper attempts to measure the rationality of the spatial layout of all shopping stores in the city. Residents will visit multiple shopping stores in one trip to meet their demands. Based on this characteristic, this paper studies shopping store clusters and proposes a cluster two-step floating catchment area (C-2SFCA) method to analyze the accessibility differences of shopping stores in urban areas. Using the case of Beijing within the Fifth Ring Road, this paper implements the C-2SFCA method in a study unit of traffic analysis zones (TAZ) considering three transport modes (car, public transport, walking) with the support of real-time travel time collected from an internet map. The results show that spatial accessibility differed greatly under different transport modes and also had an uneven distribution pattern. Among these three results, the spatial variation of public transport accessibility was the highest. The results can provide references for urban planners in facility configuration and decision-making.

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Which types of shopping malls affect housing prices? From the perspective of spatial accessibility

Cited by 36 publications

References 61 publications

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China

Measuring Cluster-Based Spatial Access to Shopping Stores under Real-Time Travel Time

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