[Supporting Data and Software] The perception of COVID-19 infection risk in Long-distance travel

The files included below are part of a research on passengers' perception of infection risk with COVID-19 and its relation to long-distance (international) travel. Data was collected through a Hierarchical Information Integration (HII) approach, where respondents were first asked to rate their perceived risk of infection, based on various safety measures. This subjective risk was then included in a mode choice experiment for long-distance trips, where respondents could choose between car, train and aircraft.<br>Information on the data and model can be found in the README file and the python script below.

下文包含的文件均属于一项探究乘客新冠病毒（COVID-19）感染风险感知及其与长途（国际）旅行关联的研究。本研究采用层级信息集成（Hierarchical Information Integration, HII）方法采集数据：首先要求受访者基于各类安全防控措施对自身感知的感染风险进行评分，随后将该主观风险指标纳入长途出行方式选择实验，受访者可在私家车、火车与民航客机之间进行选择。有关该数据集与对应模型的详细信息，可参阅README文件以及下述Python脚本。