Dr. Chiara Calastri – PhD Thesis Presentation-“Capturing and modelling complex decision-making in the context of travel, time use and social interactions”

  • Date: Tuesday 12 December 2017
  • Location: University of Leeds, Institute for Transport Studies (ITS) Room 1.11

Differently from many other countries, a PhD in the UK does not involve a public defence.

For this reason, we decided to start a new series of seminars for CMC students, hoping that other research groups will find this interesting and hopefully adopt the idea for their students as well.

Shortly after the Viva, we will organise an evening seminar (held around 5 PM) where the PhD student will have the opportunity to present an overview of his/her PhD work in a way that is accessible to people from outside the immediate research area. The events will be open not only to colleagues from the whole institute and the wider university but also friends and family. The seminars will be followed by refreshments.

The first seminar of the series will be presented by Chiara Calastri.

Capturing and modelling complex decision-making in the context of travel, time use and social interactions

Tuesday, 12th December, 17:00-18:30
University of Leeds, Institute for Transport Studies (ITS) Room 1.11

Abstract:

The field of choice modelling is facing the challenge of constantly improving its complex mathematical structures while correctly accommodating real-life behavioural aspects in these models. In this thesis, different methodological contributions aimed at improving the understanding and forecasting of discrete-continuous choices and representing heterogeneity are made, while substantial attention is devoted to a correct representation of social network processes and choices and to the investigation of the factors affecting time use. The thesis proposes both methodological and applied contributions making use of diverse revealed preference datasets from different countries, and puts forward ideas for improved data collection approaches. The findings from this thesis represent an advancement in the field of choice modelling and travel behaviour and a potential resource for policy making.