Public transport mode choice behavior of different-income passengers during large-scale public health incidents

IF 6.3 2区 工程技术 Q1 ECONOMICS
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引用次数: 0

Abstract

Public transport ridership has been hit hard by the COVID-19 pandemic in many countries. Investigating passengers' public transport mode choice behavior during large-scale public health incidents can uncover the major influential factors and help propose policies and strategies to reduce the pandemic transmission and recover the public transport revenue. This study develops an integrated choice and latent variables (ICLV) model by income based on structural equation model to model passengers' public transport choice behavior during the normalized stage of the pandemic. The model considers passengers' socioeconomic attributes, travel attributes, and attitude-perception attributes, and can appropriately capture passengers' psychological latent attributes. Taking Beijing China as an example, we collect some revealed preference survey data online. The modeling results show that the risk perception as a mediator variable has a significant impact on mode preference. Moreover, the convenience of public transport has the largest influence on risk perception. These findings suggest that risk perception and the convenience of public transport play a major role in passengers' mode choice behavior. In addition, the impacts of the various influential factors on the public transport mode choices are significantly different across different income groups. Further, the ICLV model can achieve better performance and is superior to the traditional Multinomial Logit model. The modeling framework can help propose targeted and instructive strategies during the normalized stage of the pandemic by uncovering the major influential factors in passengers’ public transport mode choices, which is applicable to similar pandemics in the future.

大型公共卫生事件中不同收入乘客的公共交通模式选择行为
在许多国家,COVID-19 大流行对公共交通乘客造成了沉重打击。调查大规模公共卫生事件中乘客的公共交通模式选择行为,可以发现主要的影响因素,有助于提出减少疫情传播和恢复公共交通收入的政策和策略。本研究在结构方程模型的基础上,建立了一个按收入划分的综合选择和潜变量(ICLV)模型,以模拟大流行常态化阶段乘客的公共交通选择行为。该模型考虑了乘客的社会经济属性、出行属性和态度感知属性,能够恰当地捕捉乘客的心理潜在属性。以中国北京为例,我们在网上收集了一些显现偏好调查数据。建模结果显示,风险感知作为中介变量对出行方式偏好有显著影响。此外,公共交通的便利性对风险感知的影响最大。这些结果表明,风险认知和公共交通的便利性在乘客的模式选择行为中发挥着重要作用。此外,在不同收入群体中,各种影响因素对公共交通方式选择的影响也存在显著差异。此外,ICLV 模型可以获得更好的性能,优于传统的多项式 Logit 模型。该模型框架通过揭示影响乘客公共交通方式选择的主要因素,有助于在疫情常态化阶段提出有针对性和指导性的策略,适用于未来类似的疫情。
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来源期刊
Transport Policy
Transport Policy Multiple-
CiteScore
12.10
自引率
10.30%
发文量
282
期刊介绍: Transport Policy is an international journal aimed at bridging the gap between theory and practice in transport. Its subject areas reflect the concerns of policymakers in government, industry, voluntary organisations and the public at large, providing independent, original and rigorous analysis to understand how policy decisions have been taken, monitor their effects, and suggest how they may be improved. The journal treats the transport sector comprehensively, and in the context of other sectors including energy, housing, industry and planning. All modes are covered: land, sea and air; road and rail; public and private; motorised and non-motorised; passenger and freight.
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