Prospect Theory and Behavioural Change

One of the goals of modelling travel behaviour, little addressed in the literature, is to provide theoretic insights on why and how people travel – and applying these insights in the development and implementation of a range of design, planning and policy measures, with an ultimate goal of making effective improvements to social and individual wellbeing (Avineri, 2012). The 'predicted irrationality (a term coined by Ariely, 2008) of individuals could (and some argue that it should) play a role in the design of behavioural change interventions. Thaler and Sunstein (2008) advocate the use of 'choice architecture' to influence behavioural change: 'nudges', small features designed in the environment of choice making, could help individuals to overcome cognitive biases and to highlight the better choices for them – without restricting their freedom of choice, and without making big changes to the physical environment, the set of choices, or the economic attributes of the choices.

Few studies in transport research literature have suggested to apply theoretic insights emerging from PT in the design of measures to change travellers' behaviour. As travellers exhibit aversion to loss and have a strong tendency to avoid choices associated with losses, Avineri (2006) suggested to 'nudge' travellers to a better user equilibrium on a traffic network by changing the perceived value of a reference point associated with travel times on the alternative routes. The reference point may be influenced by the presentation of the outcomes or expectations of the decisionmaker and by social norms. This approach is based on the gain/loss asymmetry, and the shape of PT's value function.

Another behavioural change approach associated with gain/loss asymmetry is valence framing. Valence framing is a framing technique that highlights gains or losses associated with the choice outcome. According to PT, loss framing would be more effective than gain framing. Loss framing can be incorporated in the design of a variety of information-based measures to promote travel behaviour change. These could include web-based journey planners, carbon calculators or 'tailored' travel information provided to individuals and households who participate in a personal travel plan. For example, Avineri and Waygood (2013), applying an experimental approach, describe how loss framing could increase the differences about the mass of transport-related CO2 emissions, as perceived by survey participants, and improve the effectiveness of such information.