Commuting, like other types of human travel, is complex in nature, such as trip-chaining behavior involving making stops of multiple purposes between two anchors. According to the 2001 National Household Travel Survey, about half of weekday U.S. workers made a stop during their commute. In excess commuting studies that examine a region’s overall commuting efficiency, commuting is, however, simplified as nonstop travel from homes to jobs. This research fills this gap by proposing a trip-chaining-based model to integrate trip-chaining behavior into excess commuting. Based on a case study of the Tampa Bay region of Florida, this research finds that traditional excess commuting studies underestimate both actual and optimal commute and overestimate excess commuting. For chained commuting trips alone, for example, the mean minimum commute time is increased by 70 percent from 5.48 minutes to 9.32 minutes after trip-chaining is accounted for. The gaps are found to vary across trip-chaining types by a disaggregate analysis by types of chain activities. Hence, policymakers and planners are cautioned with regards to omitting trip-chaining behavior in making urban transportation and land use policies. In addition, the proposed model can be adopted to study the efficiency of nonwork travel.

与其他类型的人类旅行一样，通勤本质上是复杂的，例如涉及在两个锚点之间多次停靠的行程链行为。根据 2001 年全国家庭旅行调查，大约一半的工作日美国工人在上下班途中停下来。然而，在检查一个地区整体通勤效率的超额通勤研究中，通勤被简化为从家到工作的不间断旅行。本研究通过提出一种基于出行链的模型来将出行链行为整合到过度通勤中，从而填补了这一空白。本研究基于佛罗里达州坦帕湾地区的案例研究，发现传统的过度通勤研究低估了实际和最佳通勤，并高估了过度通勤。例如，仅对于连锁通勤旅行，考虑到行程链后，平均最短通勤时间增加了 70%，从 5.48 分钟增加到 9.32 分钟。通过按链活动类型进行分解分析，发现差距因旅行链类型而异。因此，政策制定者和规划者在制定城市交通和土地使用政策时应注意避免行程链行为。此外，所提出的模型可用于研究非工作旅行的效率。