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SUMMARY:A mixed random utility - random regret model linking the choice of
   decision rule to latent character traits
DTSTART:20141128T121500
DTEND:20141128T131500
DTSTAMP:20260406T161354Z
UID:ebb6fe6148ded57a6026fa3a3625b9f6f04895267bac0601bb66284d
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Stephane Hess\, University of Leeds\, UK\nAn increasing 
 number of studies are concerned with the use of  alternatives to random u
 tility maximisation as a decision rule in choice models\, with a particula
 r emphasis on regret minimisation over the last few years. The initial foc
 us was on revealing which paradigm fits best for a given dataset\, while l
 ater studies have looked at variation in decision rules across respondents
  within a dataset.\nHowever\, only limited effort has gone towards underst
 anding the potential drivers of decision rules\, i.e. what makes it more o
 r less likely that the choices of a given respondent can be explained by a
  particular paradigm. The present paper puts forward the notion that unobs
 erved character traits can be a key source of this type of heterogeneity a
 nd 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 al
 location to a given class is driven in part by a latent variable which at 
 the same time explains respondents' stated satisfaction with their real wo
 rld commute journey. Results reveal a linkage between the likely decision 
 rule and the stated satisfaction with the real world commute conditions. N
 otably\, the most regret-prone respondents in our sample are more likely t
 o have aligned their real-life commute performance more closely with their
  aspirational values.\nBio: Stephane Hess is Professor of Choice Modelling
  in the Institute for Transport Studies and Director of the Choice Modelli
 ng Centre at the University of Leeds. He is also Honorary Professor in Cho
 ice 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 analys
 is of human decision using advanced discrete choice models\, and he is act
 ive in the fields of transport\, health and environmental economics. Hess 
 has made contributions in the specification\, estimation and interpretatio
 n of such models\, notably in a valuation of travel time savings context\,
  while also publishing widely on the benefits of advanced structures in ac
 tual large-scale transport analyses. His contributions have been recognise
 d 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 t
 he14th International Conference on Travel Behaviour Research\, to be held 
 in London in 2015. He is an associate editor of Transportation Research Pa
 rt E\, and serves on the editorial advisory board of Transportation Resear
 ch Part B and Transportation.
LOCATION:GC C330 http://plan.epfl.ch/?lang=fr&room=GCC330
STATUS:CANCELLED
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