Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data

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Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data

Calastri, Chiara / Hess, Stephane / Daly, Andrew / Carrasco, Juan Antonio

AbstractAn understanding of activity choices and duration is a key requirement for better policy making, in transport and beyond. Previous studies have failed to make the important link with individuals’ social context. In this paper, the Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) model is applied to the choice of activity type and duration over the course of two days, using data from the Chilean city of Concepción. In common with other studies, heterogeneity across decision makers is accommodated in the model by analysing the impact of different socio-demographic, mobility and residential location variables on both the activity choice and the time allocation decision. In addition, different social network and social capital measures are found to be significantly correlated with the choice and duration of different activities, and we show how these relationships seem to differ from the effects of socio-demographic variables. Finally, we perform a forecasting exercise using the MDCNEV model, highlighting the differences in substitution patterns from a standard MDCEV model.

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Title :

Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data

Contributors:

Calastri, Chiara (author) / Hess, Stephane (author) / Daly, Andrew (author) / Carrasco, Juan Antonio (author)

Published in:

Transportation Research Part A: Policy and Practice ; 104 ; 1-20

Publication date :

2017-07-12

Size :

20 pages

ISSN :

0965-8564

DOI :

https://doi.org/10.1016/j.tra.2017.07.003