In-depth, Breadth-first or Both? Toward the Development of a RUM-DFT Discrete Choice Model

Abstract

Development and innovation in discrete choice modelling has been dominated by Random Utility Maximization approaches due to their ease of application and high economic interpretability. However, this model assumes that decision-makers perform an in-depth information search process implicitly and instantaneously. In particular, it has not been investigated in detail whether the information search process of transport users is in-depth or breadth-first in a public transport choice context, a gap that this research aims to fill. To this end, the information search process of public transport users has been characterized by stated preference surveys with click-tracking. Specifically, three pivoted SP surveys concerning morning peak trips were designed and applied, varying in the number of alternatives and attributes (areas of interest shown: AOI). These values were displayed as an information board, where only one attribute is visible at a time, and clicks were recorded to evaluate the respondents' information search process. Three main conclusions can be drawn from the findings. First, the pattern of searching for information in breadth-first predominates independently of the AOIs displayed. Second, more searches are performed than the amount of information displayed and this value increases at a decreasing rate with increasing AOIs. Third, the most likely transitions during the deliberation process are those that arise from breadth-first searches. In summary, the evidence found suggests that there is a dominance of breadth-first searches, so the RUM model would not be able to describe the deliberation process adequately and that the assumptions of the RRM or DFT models would be more appropriate for these purposes.