A Random Utility Maximization (RUM) Based Dynamic Activity Scheduling Model: Application in Weekend Activity Scheduling

The paper presents a modelling framework for activity scheduling process. The modelling framework considers Random utility maximization (RUM) assumption for its components in order to dynamically capture the joint activity type, location and continuous time expenditure choice tradeoffs over the course of the day. The dynamics of activity scheduling process are modeled by considering the history of activity participation as well as changes in time budget availability over the day. For empirical application, the model is estimated for weekend activity scheduling using a dataset (CHASE) collected in Toronto in 2002-2003. The data set classifies activities into nine general categories. For the empirical model of a 24-hour weekend activity scheduling only activity type and time expenditure choice are considered. The estimated empirical model explains many behavioral details and gives a high degree of fit to the observed weekend scheduling patterns. Some examples of such findings are the effects of the time of day on choosing an activity to schedule and on the corresponding time expenditure; the effects of travel time requirements on the utility of scheduling specific activities and on the corresponding time expenditure, etc. Among many other findings, the empirical model captures the fact that on the weekend the utility of scheduling Recreational activities for later in the day and over a longer duration of time is high. On the weekend, Social activity scheduling is not affected by travel time requirements, but longer travel time requirements typically lead to longer-duration social activities.