This paper focuses on empirically investigating the inertia effects of past behavior in commuting modal shift behavior and contributes to the current state of the art by three aspects. Firstly, this study introduces and tests the potential influences of the inertia effects of past behavior on the traveler’s preferences regarding level-of-service (LOS) variables, besides the impacts of inertia effects on the preference for the frequently used transport mode in the past. Secondly, the mode-specific inertia effects are investigated to distinguish the differences in the inertia effects for different transport modes based on posterior individual-specific parameter estimations. Thirdly, the factors contributing to the heterogeneity of inertia effects including demographics and travel contexts, are quantitatively examined. A joint random parameter logit model using a revealed and stated preference survey regarding commuting behavior is employed to unravel the three aspects. The results reveal significant interactions of inertia terms with LOS variables indicating the influences of past behavior on travelers’ evaluations on attributes of their previous choices. The mean values and variances of inertia effects for different transport modes are significantly and substantially distinct. For instance, the inertia effects of frequently using car are substantially positive representing strong stickiness to the car, while the inertia effects of frequently using the metro have large variances among travelers and mostly appear as dispositions to change. Besides, the effects of personal characteristics and travel contexts on the magnitude of the inertia effects of different transport modes are identified as well. A demand estimation analysis is utilized to investigate the influences of three aspects on predicting travel demands in various contexts. Incorporating the interactions and mode-specific inertia effects can remarkably improve the model performance. The demand estimation will be biased if they are neglected.

本文侧重于实证研究过去行为在通勤模式转换行为中的惯性效应，并从三个方面对当前的技术状态做出贡献。首先，本研究介绍并检验了过去行为的惯性效应对旅行者对服务水平（LOS）变量偏好的潜在影响，以及惯性效应对过去常用交通方式偏好的影响。 . 其次，研究了特定模式的惯性效应，以基于后验个体特定参数估计来区分不同运输模式的惯性效应差异。第三，定量研究了导致惯性效应异质性的因素，包括人口统计和旅行环境。使用关于通勤行为的揭示和陈述的偏好调查的联合随机参数 logit 模型被用来解开这三个方面。结果揭示了惯性项与 LOS 变量之间的显着相互作用，表明过去行为对旅行者对其先前选择属性的评估的影响。不同运输方式的惯性效应的平均值和方差有显着差异。例如，频繁使用汽车的惯性效应显着为正，代表对汽车的强烈粘性，而频繁使用地铁的惯性效应在出行者之间存在较大差异，并且大多表现为倾向改变。除了，还确定了个人特征和旅行环境对不同交通方式惯性效应大小的影响。需求估计分析用于研究三个方面对预测各种情况下的旅行需求的影响。结合相互作用和模式特定的惯性效应可以显着提高模型性能。如果忽略它们，需求估计将有偏差。