This study investigates how age, period, and birth cohorts are related to altering travel distances. We analyze a repeated cross-sectional survey of German pleasure travels for the period 1971–2018 using a holistic age–period–cohort (APC) analysis framework. Changes in travel distances are attributed to the life cycle (age effect), macro-level developments (period effect), and generational membership (cohort effect). We introduce ridgeline matrices and partial APC plots as innovative visualization techniques facilitating the intuitive interpretation of complex temporal structures. Generalized additive models are used to circumvent the identification problem by fitting a bivariate tensor product spline between age and period. The results indicate that participation in short-haul trips is mainly associated with age, while participation in long-distance travel predominantly changed over the period. Generational membership shows less association with destination choice concerning travel distance. The presented APC approach is promising to address further questions of interest in tourism research.

这项研究调查了年龄，时期和出生人群与旅行距离的变化之间的关系。我们使用整体的年龄-时期-队列（APC）分析框架，对1971-2018年间德国休闲旅行的重复横断面调查进行了分析。出行距离的变化归因于生命周期（年龄效应），宏观发展（时期效应）和世代成员（队列效应）。我们介绍山脊线矩阵和部分APC图作为创新的可视化技术，有助于直观地解释复杂的时间结构。通过在年龄和时期之间拟合双变量张量积样条，使用广义加性模型来规避识别问题。结果表明，参加短途旅行主要与年龄，在此期间，参加长途旅行的方式主要发生了变化。世代成员资格显示与旅行距离有关的目的地选择的关联较少。提出的APC方法有望解决旅游研究中感兴趣的其他问题。