Presenter Information

Location

Hilton Waikoloa Village, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

7-1-2025 12:00 AM

End Date

10-1-2025 12:00 AM

Description

Research have suggested that TOD (transit-oriented development) in sub-centers with transit stations is an approach to increase foot traffic and the overall vitality of the area. However, current development of sub-centers mostly follows the established TOD model in CAZs (central activity zone), and most TOD studies do not deliberately distinguish or emphasize between CAZs and sub-centers. Therefore, this study aims to examine the influence of factors in the built-up area of Shanghai's urban sub-center on TOD-ness around the station. The four main factors are accessibility to private cars, land use, inner connectivity, and functionality. A regression model was introduced to validate the factors that significantly influence transit ridership. Results show that most of factors are relative to metro usage, with a lower correlation index, indicating the extent of the impact they bring varies remarkably with the urban context. while some factors have conversed influence as in urban centers.

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Jan 7th, 12:00 AM Jan 10th, 12:00 AM

Examining Common Factors Influencing Suburban Transit Ridership – A Case Study of Metro Stations outside Center-Shanghai

Hilton Waikoloa Village, Hawaii

Research have suggested that TOD (transit-oriented development) in sub-centers with transit stations is an approach to increase foot traffic and the overall vitality of the area. However, current development of sub-centers mostly follows the established TOD model in CAZs (central activity zone), and most TOD studies do not deliberately distinguish or emphasize between CAZs and sub-centers. Therefore, this study aims to examine the influence of factors in the built-up area of Shanghai's urban sub-center on TOD-ness around the station. The four main factors are accessibility to private cars, land use, inner connectivity, and functionality. A regression model was introduced to validate the factors that significantly influence transit ridership. Results show that most of factors are relative to metro usage, with a lower correlation index, indicating the extent of the impact they bring varies remarkably with the urban context. while some factors have conversed influence as in urban centers.

https://aisel.aisnet.org/hicss-58/li/data_analytics/5