A nested logit model of commuters' activity schedules

TLDR: In this article, a nested logit model of activity scheduling behavior is proposed to predict a daily activity pattern for commuters, which suggests a two-stage decision process in which commuters first plan or identify the non-work activities that need to be undertaken during the day, and second, schedule these activities in relation to the work activity schedule.

Abstract: This paper presents a nested logit model of activity scheduling behavior that can be used to predict a daily activity pattern for commuters. The behavioral paradigm embodied in the model suggests a two-stage decision process in which commuters first plan or identify the nonwork activities that need to be undertaken during the day, and second, schedule these activities in relation to the work activity schedule. Three possible scheduling periods are considered in the model: before work, at work, and after work. Alternative nested logit model structures are estimated on the 1996 San Francisco Bay Area activity survey sample to identify a plausible and statistically acceptable structure. Numerical examples are presented to show how the model, when combined with a Monte Carlo simulation and simple heuristics, can be used to generate daily activity schedule for commuters.