There has been an increasing effort to increase the behavioural realism of the mathematical models of choice, resulting in efforts to move away from random utility maximisation (RUM) models. Many of the alternative structures tested thus far, such as random regret minimisation (RRM), however only represent modest departures from RUM, and differences in results have consequently been small. In this paper, we address this research gap by investigating the applicability of models based on quantum theory, leading to structures that are radically different from the state-of-the-art choice modelling techniques. These models emphasise the importance of contextual effects, state dependence and the impact of choice or question order. As a result, quantum probability models have had some success in better explaining several phenomena in cognitive psychology. This presentation looks at how to best operationalise quantum probability into a choice model, and presents a number of different applications.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, Honorary Professor of Modelling Behaviour in Africa at the University of Cape Town. He has made contributions to the state of the art in the specification, estimation and interpretation of choice models, as well as in facilitating the transition of ideas and approaches across disciplines, notably by also working in mathematical psychology and behavioural economics. Although a majority of his applied work has been conducted in the field of transport, he is also very active in health and environmental economics. Together with his research team at the Choice Modelling Centre, he is setting the research agenda in applying choice modelling in new fields, including education, lifestyle choices, social (network) interactions and joint decision making. Advanced choice models require high quality data, and Hess and his team are leading the field in exploring and exploiting novel data sources, with numerous applications using ‘big data’. He is also the founding editor in chief of the Journal of Choice Modelling and the founder and steering committee chair of the International Choice Modelling Conference. Together with David Palma, he is the author of Apollo, a highly flexible and powerful free tool for estimating and applying choice models.