In post-COVID era, more agencies will seek to incorporate long-distance or overnight travel into their travel forecasting. This paper leverages a unique survey dataset (n = 440) that queried participants’ propensity to make simultaneous or bundled decisions on mode and destination location for their most recent overnight out-of-town personal trip. The random representative sample of Vermont residents indicated they mostly make bundled decisions of destination and mode choice. Binary logistic regressions were estimated to determine (a) sociodemographic factors (e.g. age, income) and trip travel distance influence the likelihood an individual will bundle their mode and destination choice and (b) mode-specific travel times, distances traveled and bundled decisions influence mode choices. Results validate that out-of-town travel destination and mode decisions are sometimes integrated, and different populations treat this decision process differently. Moreover, choice models of this behavior require more complex predictors in addition to distance, including whether it is part of a bundled decision.

在后 COVID 时代，更多机构将寻求将长途或过夜旅行纳入其旅行预测。本文利用一个独特的调查数据集 (n = 440)，该数据集询问参与者在最近一次出城过夜的个人旅行中对模式和目的地位置做出同时或捆绑决定的倾向。佛蒙特州居民的随机代表性样本表明，他们大多会做出目的地和方式选择的捆绑决定。估计二元逻辑回归以确定 (a) 社会人口因素（例如年龄、收入）和旅行距离影响个人将他们的模式和目的地选择捆绑在一起的可能性，以及 (b) 模式特定的旅行时间、旅行距离和捆绑决策的影响模式选择。结果证实，外出旅游目的地和出行方式的决定有时是综合的，不同的人群对待这个决定过程的方式不同。此外，这种行为的选择模型除了距离之外还需要更复杂的预测因素，包括它是否是捆绑决策的一部分。