Dynamic Model of Weekly Activity Pattern

This paper presents a model of weekly activity pattern, based on a theory of individual behavior. The week is divided into time periods, and the following dynamic decision-making process is suggested. At the beginning of the first period, the individual selects his/her activity pattern for the entire week. At the beginning of the second period, the individual updates his/her plans for the remaining periods of the week on the basis of the actual behavior and the additional information that was acquired during the first time periods. In this way, the individual proceeds from period to period and the observed weekly activity pattern is the outcome of successive decisions. Based on utility maximizing principles, a parametric model of this dynamic decision-making process that can be estimated with revealed preferences data is formulated. A version of the model for weekly shopping activity behavior is estimated with survey data from Israel. The model is then applied to predict the effects of shortening the workweek. The empirical results support the dynamic behavior hypothesis and demonstrate the potential biases that may arise from the omission in a travel demand model of the interdependencies among the days of the week.