Citation

Ma L, Xiong H, Wang Z, Xie K. Transp. Res. D Trans. Environ. 2019; 68: 39-51.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trd.2018.05.008

PMID

unavailable

Abstract

Weather conditions have been recognized as important factors affecting school commute mode choices. This paper aims to explore the modal shift of middle school commutes with respect to the variation in weather-related variables, with empirical emphases on the situation in Beijing, China. Data from the latest Beijing School Commute Survey (2014-2015) were adopted, and multinomial probit (MNP) and multinomial logit (MNL) models were developed. The modeling results are in favor of the MNP model because it has better statistical performance. Weather-related variables, including sky condition, wind speed, highest temperature, humidity, air quality index (AQI), and some interaction terms, were found to have a significant impact on students' commute mode choices. Based on these models, an empirical sensitivity measure was defined as the expected percentage change in the probability of choosing each mode with respect to an order of magnitude change in the influential factors. Most of the results are in line with those of previous studies, and some unique results reflect features of Beijing. For example, on days with extremely poor air quality, students are more likely to turn to public transport rather than use a car from active transportation modes. This is probably due to the special urban traffic regulations that restrict household car ownership and car travel in Beijing. These findings could have implications for promoting active transportation for students and serve as references for policymakers and planners.

Language: en

Keywords

Empirical sensitivity; Mode choice; Multinomial probit model; School commute; Weather condition