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A platform for research: civil engineering, architecture and urbanism
Calendar events' influence on the relationship between metro ridership and the built environment: A heterogeneous effect analysis in Shenzhen, China
https://orcid.org/0000-0001-6070-9044
Highlights Relationship between the built environment (BE) and metro ridership (MR) is explored. Four calendar events are considered during the modeling of the BE-MR relationship. Global (OLS) and local (GWR) regression approaches are adopted. BE factors that significantly affect MR are unlike between workdays and non-workdays.
Abstract This study examines the associations between the built environment (BE) and metro ridership (MR) during different calendar events (workdays, weekends, Spring Festival, and Valentine's Day) in Shenzhen. Utilizing 18-day metro smart card and points of interest (POIs) data, we employ ordinary least squares (OLS) and geographically weighted regression (GWR) models to compare the BE-MR relationship across different calendar events. The findings show that MR during different calendar events follows the pattern: unofficial holiday (Valentine's Day) > workdays > weekends > public holidays (Spring Festival). Moreover, BE factors significantly affecting MR differ between workdays and non-workdays, with slight differences observed among non-workdays (i.e., weekends and holidays). Specifically, during non-workdays, especially Spring Festival, metro trips related to leisure and tourism activities are more prevalent in the southwest area of Shenzhen, while potential cross-city travel is more active in the north. On workdays, metro trips associated with hotel check-in activities concentrate in central urban areas (e.g., Luohu and Futian districts), whereas they are more active in the northeast suburbs during the Spring Festival. These findings can aid in predicting metro usage, enabling more efficient and productive resource allocation.
Calendar events' influence on the relationship between metro ridership and the built environment: A heterogeneous effect analysis in Shenzhen, China
https://orcid.org/0000-0001-6070-9044
Highlights Relationship between the built environment (BE) and metro ridership (MR) is explored. Four calendar events are considered during the modeling of the BE-MR relationship. Global (OLS) and local (GWR) regression approaches are adopted. BE factors that significantly affect MR are unlike between workdays and non-workdays.
Abstract This study examines the associations between the built environment (BE) and metro ridership (MR) during different calendar events (workdays, weekends, Spring Festival, and Valentine's Day) in Shenzhen. Utilizing 18-day metro smart card and points of interest (POIs) data, we employ ordinary least squares (OLS) and geographically weighted regression (GWR) models to compare the BE-MR relationship across different calendar events. The findings show that MR during different calendar events follows the pattern: unofficial holiday (Valentine's Day) > workdays > weekends > public holidays (Spring Festival). Moreover, BE factors significantly affecting MR differ between workdays and non-workdays, with slight differences observed among non-workdays (i.e., weekends and holidays). Specifically, during non-workdays, especially Spring Festival, metro trips related to leisure and tourism activities are more prevalent in the southwest area of Shenzhen, while potential cross-city travel is more active in the north. On workdays, metro trips associated with hotel check-in activities concentrate in central urban areas (e.g., Luohu and Futian districts), whereas they are more active in the northeast suburbs during the Spring Festival. These findings can aid in predicting metro usage, enabling more efficient and productive resource allocation.
Calendar events' influence on the relationship between metro ridership and the built environment: A heterogeneous effect analysis in Shenzhen, China
https://orcid.org/0000-0001-6070-9044
Highlights Relationship between the built environment (BE) and metro ridership (MR) is explored. Four calendar events are considered during the modeling of the BE-MR relationship. Global (OLS) and local (GWR) regression approaches are adopted. BE factors that significantly affect MR are unlike between workdays and non-workdays.
Abstract This study examines the associations between the built environment (BE) and metro ridership (MR) during different calendar events (workdays, weekends, Spring Festival, and Valentine's Day) in Shenzhen. Utilizing 18-day metro smart card and points of interest (POIs) data, we employ ordinary least squares (OLS) and geographically weighted regression (GWR) models to compare the BE-MR relationship across different calendar events. The findings show that MR during different calendar events follows the pattern: unofficial holiday (Valentine's Day) > workdays > weekends > public holidays (Spring Festival). Moreover, BE factors significantly affecting MR differ between workdays and non-workdays, with slight differences observed among non-workdays (i.e., weekends and holidays). Specifically, during non-workdays, especially Spring Festival, metro trips related to leisure and tourism activities are more prevalent in the southwest area of Shenzhen, while potential cross-city travel is more active in the north. On workdays, metro trips associated with hotel check-in activities concentrate in central urban areas (e.g., Luohu and Futian districts), whereas they are more active in the northeast suburbs during the Spring Festival. These findings can aid in predicting metro usage, enabling more efficient and productive resource allocation.
Calendar events' influence on the relationship between metro ridership and the built environment: A heterogeneous effect analysis in Shenzhen, China
Liu, Zhewei (author) / Liu, Jianxiao (author) / Hu, Runqi (author) / Yang, Bokai (author) / Huang, Xiao (author) / Yang, Linchuan (author)
2023-08-31
Article (Journal)
Electronic Resource
English
Effects of built environment on metro ridership at a microscopic scale: a case study of Xi’an, China
| Taylor & Francis Verlag | 2024