A mixed random utility - random regret model linking the choice of decision rule to latent character traits
Cancelled
Event details
| Date | 28.11.2014 |
| Hour | 12:15 › 13:15 |
| Speaker | Prof. Stephane Hess, University of Leeds, UK |
| Location | |
| Category | Conferences - Seminars |
An increasing number of studies are concerned with the use of alternatives to random utility maximisation as a decision rule in choice models, with a particular emphasis on regret minimisation over the last few years. The initial focus was on revealing which paradigm fits best for a given dataset, while later studies have looked at variation in decision rules across respondents within a dataset.
However, only limited effort has gone towards understanding the potential drivers of decision rules, i.e. what makes it more or less likely that the choices of a given respondent can be explained by a particular paradigm. The present paper puts forward the notion that unobserved character traits can be a key source of this type of heterogeneity and proposes to characterise these traits through a latent variable within a hybrid framework. In an empirical application on stated choice data, we make use of a mixed random utility-random regret structure, where the allocation to a given class is driven in part by a latent variable which at the same time explains respondents' stated satisfaction with their real world commute journey. Results reveal a linkage between the likely decision rule and the stated satisfaction with the real world commute conditions. Notably, the most regret-prone respondents in our sample are more likely to have aligned their real-life commute performance more closely with their aspirational values.
Bio: Stephane Hess is Professor of Choice Modelling in the Institute for Transport Studies and Director of the Choice Modelling Centre at the University of Leeds. He is also Honorary Professor in Choice Modelling in the Institute for Transport and Logistics Studies at the University of Sydney, and affiliated Professor in Demand Analysis at KTH Royal Institute of Technology in Stockholm. His area of work is the analysis of human decision using advanced discrete choice models, and he is active in the fields of transport, health and environmental economics. Hess has made contributions in the specification, estimation and interpretation of such models, notably in a valuation of travel time savings context, while also publishing widely on the benefits of advanced structures in actual large-scale transport analyses. His contributions have been recognised by a number of major awards. He is also the founding editor in chief of the Journal of Choice Modelling, the founder and steering committee chair of the International Choice Modelling Conference, and the co-chair for the14th International Conference on Travel Behaviour Research, to be held in London in 2015. He is an associate editor of Transportation Research Part E, and serves on the editorial advisory board of Transportation Research Part B and Transportation.
However, only limited effort has gone towards understanding the potential drivers of decision rules, i.e. what makes it more or less likely that the choices of a given respondent can be explained by a particular paradigm. The present paper puts forward the notion that unobserved character traits can be a key source of this type of heterogeneity and proposes to characterise these traits through a latent variable within a hybrid framework. In an empirical application on stated choice data, we make use of a mixed random utility-random regret structure, where the allocation to a given class is driven in part by a latent variable which at the same time explains respondents' stated satisfaction with their real world commute journey. Results reveal a linkage between the likely decision rule and the stated satisfaction with the real world commute conditions. Notably, the most regret-prone respondents in our sample are more likely to have aligned their real-life commute performance more closely with their aspirational values.
Bio: Stephane Hess is Professor of Choice Modelling in the Institute for Transport Studies and Director of the Choice Modelling Centre at the University of Leeds. He is also Honorary Professor in Choice Modelling in the Institute for Transport and Logistics Studies at the University of Sydney, and affiliated Professor in Demand Analysis at KTH Royal Institute of Technology in Stockholm. His area of work is the analysis of human decision using advanced discrete choice models, and he is active in the fields of transport, health and environmental economics. Hess has made contributions in the specification, estimation and interpretation of such models, notably in a valuation of travel time savings context, while also publishing widely on the benefits of advanced structures in actual large-scale transport analyses. His contributions have been recognised by a number of major awards. He is also the founding editor in chief of the Journal of Choice Modelling, the founder and steering committee chair of the International Choice Modelling Conference, and the co-chair for the14th International Conference on Travel Behaviour Research, to be held in London in 2015. He is an associate editor of Transportation Research Part E, and serves on the editorial advisory board of Transportation Research Part B and Transportation.
Practical information
- General public
- Free
Organizer
- Prof. Dr Nikolas Geroliminis & Katrin Beyer
Contact
- Prof. Dr Nikolas Geroliminis