Dynamic model of activity-type choice and scheduling

Abstract

This paper presents a model for the choice of activity-type and timing, incorporating the dynamics of scheduling estimated on a six-week travel diary. The main focus of the study is the inclusion of past history of activity involvement and its influence on current activity choice. The econometric formulation adopted, explicitly accounts both for correlation across alternatives and for state dependency. The results indicate that behavioral variables are superior to socio-economic variables and that consideration of the correlation pattern over alternatives clearly improves the fit of the model. This is a first but significant contribution to changing the current static demand models into dynamic activity based ones. The availability of other multi-week travel surveys and the progress made recently on advanced econometric techniques should encourage the transferability of this study to different regions or model scale.

Discretionary activity location choice: in-home or out-of-home?

“…Different mode choice models are estimated for different activity types (active, passive, social, meals). The reason for segmenting the data activity types and estimating separate mode choice models is the fact that people have different value of times (the monetary amount that a person is willing to pay to decrease the travel time by 1 min) for different activity types (Cirillo and Axhausen 2009).…”

Dynamic travel mode searching and switching analysis considering hidden model preference and behavioral decision processes

“…Pendyala et al 2004;Cirillo and Axhausen 2010;Cirillo and Xu 2011). For example, Cirillo and Axhausen (2010) incorporated dynamic variables in the systematic utility function of a discrete choice model when modeling activity type and timing.…”

On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates

“…In particular, a "long survey panel" including data for the same respondents at separate times allows us to study dynamic effects over waves, such as habit formation, learning and the reaction to important policies (Yáñez and Ortúzar, 2009;Yáñez et al, 2009b). A "short survey panel", on the other hand, such as a multi-day panel over only one continuous period of time allows to detect effects such as rhythms of daily life (Axhausen et al, 2002), to explain current behaviour on the basis of the individuals' history and experience (Cirillo and Axhausen, 2006) and to account for interpersonal variability and correlation across individuals over different time periods (Cherchi and Cirillo, 2008).…”