Interactive Methods for Activity Scheduling Processes
In the field of transportation, a strong argument has been made for the use of an activity-based approach to improve the behavioral foundations of travel forecasting models (Axhausen and Gärling, 1992; Ettema and Timmermans, 1997). While this approach offers considerable theoretical appeal and potential, the data collection that it has inspired has been largely limited to a retooling of traditional diary-based survey methods from recording
. While activity diaries have several practical advantages, the implications for analysts is the more challenging task of trying to understand and model a more complex set of observed activities
travel patterns. The main criticism of diary-based methods is that they focus on revealed outcomes, providing little, if
any, information on the underlying behavioral process that led to the outcomes in the first place. To meet this need, a new class of survey methods has emerged that focuses on the activity scheduling decision process. Their main point of departure from traditional diary methods is an explicit focus on tracing the underlying process of
activity-travel decisions are planned, adapted, and executed over time, space, and across individuals — often termed an
activity scheduling process.