Zhao Pengjun, Gao Yukun
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 508055, China.
Travel Behav Soc. 2022 Jul;28:181-195. doi: 10.1016/j.tbs.2022.04.002. Epub 2022 Apr 5.
It is widely reported that the COVID-19 pandemic has reduced ridership and brought severe challenges to urban public transit systems in many countries. The impact of the COVID-19 pandemic on individual people's choice of public transit may continue for a while after the peak of the crisis. However, there is insufficient detailed knowledge of how individuals respond in the post-pandemic context and make choices on public transit travel. This paper contributes fresh evidence for this by looking at Beijing as a case. The theoretical framework of the Theory of Planned Behavior is used to model individuals' public transit travel choice-making processes along with three additional constructs representing the impact of the pandemic and the nature of urban mobility behaviors, namely perceived knowledge of COVID-19, the psychological risks of COVID-19, and travel habits. Structural equation modeling is used in model estimation. We point out that there may be potential differences between the effects and meanings of model constructs in the post-pandemic context and in normal daily context. Interestingly, despite the higher psychological risk's negative effects, higher perceived knowledge of COVID-19 has significantly positive effects on people's decision-making processes. A strong pre-pandemic personal habit of traveling by public transit has significant and positive effects on post-pandemic intention and perceived behavioral control. Group comparisons show that "captive" transit users have higher psychological risk of COVID-19 than "choice" transit users, yet their transit use decisions are less influenced by it. Based on the modeling results, more behavioral experiments are needed to further inform efficient policy-making.
据广泛报道，新冠疫情导致乘客数量减少，给许多国家的城市公共交通系统带来了严峻挑战。新冠疫情对个人选择公共交通的影响在危机高峰期过后可能还会持续一段时间。然而，对于个人在疫情后如何做出反应以及如何选择公共交通出行，我们还缺乏足够详细的了解。本文以北京为例，为这一问题提供了新的证据。我们运用计划行为理论的理论框架，对个人的公共交通出行选择过程进行建模，并加入了另外三个代表疫情影响和城市出行行为本质的结构变量，即对新冠病毒的认知、感染新冠病毒的心理风险和出行习惯。模型估计采用结构方程模型。我们指出，在疫情后背景和正常日常背景下，模型结构变量的影响和意义可能存在潜在差异。有趣的是，尽管较高的心理风险具有负面影响，但对新冠病毒的较高认知对人们的决策过程具有显著的积极影响。疫情前较强的乘坐公共交通出行的个人习惯对疫情后的出行意愿和感知行为控制具有显著的积极影响。群体比较表明，“非自主选择”的公共交通使用者感染新冠病毒的心理风险高于“自主选择”的公共交通使用者，但他们的公共交通使用决策受其影响较小。基于建模结果，需要更多的行为实验来为高效决策提供进一步的参考。
