| Several activity-based models made the transition to practice over the last decade. However, modeling 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 a relatively large sample of individuals. The diary data includes detailed information about 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 have an influence on activity-episode timing decisions in a longitudinal time frame and, thus, on frequency and day choice of conducting the social, leisure and sports activities. |
