After the outbreak of COVID-19 pandemic, crowding has been highlighted as a risk factor for contracting acute respiratory infections (ARIs) such as COVID-19, which has affected the demand for public transport. Although several countries, including the Netherlands, have implemented differential fare systems for peak and off-peak travel to reduce crowding during the rush hours, the problem of overcrowding on trains has remained prevalent and is expected to cause more disutility than even before the pandemic. A stated choice experiment in the Netherlands is conducted to understand the extent to which people can be motivated to change their departure time to avoid crowded trains during rush hours by offering them real-time information on on-board crowding levels and a discount on the train fare. To gain further insights into how travelers respond to crowding and capture unobserved heterogeneity in the data, latent class models have been estimated. Unlike the previous studies, the respondents were segregated into two groups before the start of the choice experiment based on their indicated preference to schedule a delay earlier or later than their desired departure. To study the change in travel behavior during the pandemic, the context of different vaccination stages was also provided in the choice experiment. Background information collected in the experiment was broadly categorized as socio-demographic, travel and work-related factors, and attitudes towards health and COVID-19. It was found that the coefficients obtained for the main attributes which were presented in the choice experiment (on-board crowd levels, scheduled delay and discount offered on full fare) were found statistically significant, and in line with previous research. It was concluded that when most of the people are vaccinated in the Netherlands, the travelers become less averse to on-board crowding. The research also indicates that certain groups of respondents, such as those who are highly crowd averse, and are not students, can be motivated to change their departure time if real-time crowding information was provided. Other groups of respondents who were found to value fare discounts can also be motivated to change their departure by similar incentives.

COVID-19 大流行爆发后，拥挤被强调为感染 COVID-19 等急性呼吸道感染 (ARI) 的风险因素，这影响了公共交通的需求。尽管包括荷兰在内的几个国家已经对高峰期和非高峰期旅行实施了差别票价制度，以减少高峰时段的拥挤，但火车过度拥挤的问题仍然普遍存在，预计会造成比大流行之前更大的负效用。在荷兰进行了一项既定选择实验，以了解通过向人们提供有关车上拥挤程度的实时信息和火车折扣，人们可以在多大程度上改变出发时间以避免在高峰时段拥挤的火车票价。为了进一步了解旅行者如何应对拥挤并捕捉数据中未观察到的异质性，我们估计了潜在类别模型。与之前的研究不同，在选择实验开始之前，受访者根据他们表示的偏好将延误安排在他们希望的出发时间之前或之后被分成两组。为了研究大流行期间旅行行为的变化，在选择实验中还提供了不同疫苗接种阶段的背景。实验中收集的背景信息大致分为社会人口统计学、旅行和工作相关因素，以及对健康和 COVID-19 的态度。结果发现，为选择实验中呈现的主要属性获得的系数（机上人群水平，计划延误和提供全价折扣）具有统计学意义，并且与之前的研究一致。得出的结论是，当大多数人在荷兰接种疫苗时，旅行者对船上拥挤的反感程度就会降低。该研究还表明，如果提供实时拥挤信息，某些受访者群体（例如高度厌恶人群且不是学生的人）可能会改变出发时间。其他被发现重视票价折扣的受访者群体也可以通过类似的激励措施改变他们的离开。旅客对机上拥挤的反感程度降低。该研究还表明，如果提供实时拥挤信息，某些受访者群体（例如高度厌恶人群且不是学生的人）可能会改变出发时间。其他被发现重视票价折扣的受访者群体也可以通过类似的激励措施改变他们的离开。旅客对机上拥挤的反感程度降低。该研究还表明，如果提供实时拥挤信息，某些受访者群体（例如高度厌恶人群且不是学生的人）可能会改变出发时间。其他被发现重视票价折扣的受访者群体也可以通过类似的激励措施改变他们的离开。