Abstract
Activity-travel chaining involves an interconnected series of activities and associated trips that occur between a pair of anchors or primary activities. By this definition, activity-travel chaining includes both the attributes of activities (e.g., location, duration, activity type, etc.) and trips (e.g., schedule, distance, route, mode, etc.). Prior research suggests that activity-travel chaining propensity can greatly influence travel demand and its temporal distribution. With the motivation to support reliable travel forecasting and inform travel demand management strategies, we investigate the direct and indirect effects of activity-travel chaining propensity for three activity types on peak and off-peak motorized person miles traveled (PMT). To perform the investigation, we employ a structural equation modeling (SEM) framework with five mediator variables (i.e., travel time savings ratio, activity space area, average daily trips, non-motorized travel mode share, and transit share) to capture the indirect effects of trip chain propensity (as well as socio-demographic and land use) on motorized PMT. We also compare workers and non-workers by specifying and estimating separate models for each group. The results indicate that activity-travel chaining propensities increase peak-hour motorized PMT for workers and non-workers. Also, non-workers chain maintenance activities during off-peak hours to avoid conducting or traveling to these activities during peak hours. We also find significant effects of location characteristics and mediator variables on peak-hour motorized PMT that policymakers can leverage when formulating travel demand management strategies.