Parameter estimation of a dynamic need-based activity generation model

Several activity-based models made the transition to practice over the last decade. However, modelling dynamic activity generation and especially, the mechanisms underlying activity generation are not well incorporated in the current activity-based models. This paper describes a first step in estimating the parameters of a need-based activity generation model. A survey was carried out to collect activity data for a typical week and a specific day among an adequate sample of individuals. The diary data include detailed information on activity history and future planning. Furthermore, person-level needs on relevant dimensions were measured using Likert scales. Estimation of the model involves a range of shopping, social, leisure and sports activities, as dependent variables, and socioeconomic, day preference, and need variables, as explanatory variables. The results show that several person, household, and dwelling attributes, and person-level needs influence activity-episode timing decisions in a longitudinal time frame and, thus, the frequency and day choice of conducting the social, leisure and sports activities.