The Influence of the Built Environment on School Children’s Metro Ridership: An Exploration Using Geographically Weighted Poisson Regression Models

Yang Liu,Zhuangbin Shi,Yanjie Ji,Liangpeng Gao

doi:10.3390/su10124684

Abstract

Long-distance school commuting is a key aspect of students’ choice of car travel. For cities lacking school buses, the metro and car are the main travel modes used by students who have a long travel distance between home and school. Therefore, encouraging students to commute using the metro can effectively reduce household car use caused by long-distance commuting to school. This paper explores metro ridership at the station level for trips to school and return trips to home in Nanjing, China by using smart card data. In particular, a global Poisson regression model and geographically weighted Poisson regression (GWPR) models were used to examine the effects of the built environment on students’ metro ridership. The results indicate that the GWPR models provide superior performance for both trips to school and return trips to home. Spatial variations exist in the relationship between the built environment and students’ metro ridership across metro stations. Built environments around metro stations, including commercial-oriented land use; the density of roads, parking lots, and bus stations; the number of docks at bikeshare stations; and the shortest distance between bike stations and metro stations have different impacts on students’ metro ridership. The results have important implications for proposing relevant policies to guide students who are being driven to school to travel by metro instead.

Highlights

School children’s reliance on cars is harmful to their daily travel behaviors towards sustainability and aggravates traffic congestion on urban roads [1,2,3,4]; governments in many developed and developing countries have committed to encouraging school children to go to school using active modes of travel including walking and bicycling [5,6,7,8]
The other tested variables are included in the global Poisson regression models for to school (TS) and return trips to home (RTH) separately
This paper focuses on the primary and secondary school students’ commuting behavior in the metro system and explores metro ridership at the station level for TS and RTH by using the smart card data (SCD) of Nanjing

Summary

Introduction

School children’s reliance on cars is harmful to their daily travel behaviors towards sustainability and aggravates traffic congestion on urban roads [1,2,3,4]; governments in many developed and developing countries have committed to encouraging school children to go to school using active modes of travel including walking and bicycling [5,6,7,8]. Active modes are most suitable for short-distance travel. When students travel a long distance to school, policies and measures that encourage them to walk or bicycle to school would be ineffective. To reduce the number of car trips needed for escorting caused by spatial inequality, studies focusing on students who have medium and long-distance school commutes are essential

Methods

Results

Discussion

Conclusion