Analyzing the effects of walkable environments on nearby commercial property values based on deep learning approaches

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초록

Interest in the economic effects of walkable environments is growing as the multidimensional benefits of walkability can be capitalized into surrounding property values. Commercial properties may be more sensitive to the economic effects of walkability compared to other types of properties due to their distinct attributes, but not many studies have investigated the relationships between walkable environments and commercial property values. Additionally, previous studies identified walkable environments on a neighborhood-scale, not at a meso -and micro-scale. This study fills these gaps by examining the effects of multifaceted walkable environments on commercial property values in Seoul, Korea. Based on sales transaction data between 2017 and 2019, we employed the hedonic price model to clarify the relationships between walkable environments and commercial property values. This study estimated walkable environments using semantic segmentation based on Google Street View images. Furthermore, we accounted for commercial submarkets to identify how the impacts of walkability vary across areas stratified by living population density. The results show that various walkable environments positively affect nearby commercial property values. Additionally, these effects vary across commercial submarkets' heterogeneity. Our findings provide a variety of suggestions for encouraging the creation of walkable environments and increasing the economic benefits of commercial properties.

키워드

Walkable environmentsStreetscapesDeep learningCommercial property valuesPHYSICAL-ACTIVITYNEIGHBORHOOD WALKABILITYBUILT ENVIRONMENTURBAN DESIGNWALKINGTRANSPORTATIONAUSTINTRAVELSENSE
제목
Analyzing the effects of walkable environments on nearby commercial property values based on deep learning approaches
저자
Shin, Hyung-SupWoo, Ayoung
DOI
10.1016/j.cities.2023.104628
발행일
2024-01
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Article
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