February 01, 2010, 11:00, Room GC B3 424 (click here for the map)
The mode choice process, especially in the case of commuter trips, reflects the strong tendency people have to simplify the assessment of their options when confronted with successive well-known decisions. Thus, it is common to repeat the “habitual” choice over time involving a potentially important inertia element. However, while inertia effects increase the probability of maintaining the same choice in a stable situation, in a changing environment i.e. one that is disrupted by a radical or significant policy intervention, user behaviour may be affected by a specific response to abrupt changes. Shock effects of this kind could increase the probability of individuals leaving their habitual choices. Temporal effects have been commonly ignored in practical studies, as most demand models to date have been based on cross-sectional data. A few recent studies dealing with panel data have managed to incorporate inertia effects, but there are no studies that have included both inertia and shock effects. To address this, I started by building a data panel around the introduction of a new and radical policy for the conurbation of Santiago de Chile. The final aim was to develop mode choice models incorporating the effects of three main forces involved in the choice process: (1) the relative values of the modal attributes, (2) the inertia effect, and (3) the shock resulting from and abrupt policy intervention. This research includes the formulation of an inertia-shock model and its application to each of simulated and real data. The results obtained provide empirical evidence that inertia-and-shock models are superior to the traditional approach (i.e. ignoring the consequences of not including temporal effects) both in terms of explaining a real phenomenon (estimation), and in terms of predictive capability. So, these findings reinforce the belief that real systems should be modelled with data which allows capturing the effect of new policies and habit/inertia effects in individuals’ choice processes. Apart from the research backbone summarised above, a related investigation has been conducted. The last wave of the Santiago Panel included a latent variable section that allowed estimating hybrid choice models in a panel data context, and to test empirically the performance of the preferred estimation methods for this type of models.