李晓伟 Likes:

Impact Factor:

5.7

Key Words:

Bayesian logistic regression; Choice behavior; Factor analysis; Intercity travel; Multimodal choice

Abstract:

This paper investigates influential factors in passengers' intercity multimodal choice behaviors in a touristy city. By collecting large individual-level data through a comprehensive field survey that was carried out at the major transportation hubs in Xi'an, China, we studied four travel modes of the surveyed travelers in this touristy city, including air, high-speed rail, traditional passenger train, and express bus. For factor analysis, 12 variables, including not only individual-related attributes but also ticketing methods and mental perceptions, were used as the independent factors after the correlation analysis and collinearity test. The regression relationships between the travel mode choice and the independent variables were studied using Bayesian multinomial logistic regression. The results indicate that those 12 factors have significant and various influences on passengers' mode choices. In particular, travel distance, fare rate, intercity travel time per hundred kilometers, quality of service, accessibility of transportation hubs, and ticketing methods have influential contributions for explaining the choice decision-makings. The findings demystify the effects of several unexplored factors in intercity multimodal travel choice behaviors and shed new light on formulating traffic management strategies for service providers and decision-makers in practice. • This paper studies intercity travels in a touristy city in China. • Modes of air, high-speed rail, traditional train, and express bus were investigated. • The BMNL was applied to model the multimodal choice behaviors. • The paper demystifies the effects of several unexplored factors.

Co-author:

汤俊卿,Hu Xiaojiao,王炜

First Author:

李晓伟

Translation or Not:

no

Date of Publication:

2020-01-01

Included Journals:

SSCI