A survey to measure cognitive biases influencing mobility choices
Carole Adam
TL;DR
This study addresses why car-dominated mobility persists despite policies promoting soft mobility by eliciting perceived values and priorities across four mobility modes from a 650-person French sample. It combines descriptive statistics with a multi-criteria evaluation framework to infer mode scores from individual priorities and perceived mode performance, then assesses rationality and the role of cognitive biases (halo, post-purchase rationalisation, and reactance) in decision-making. The authors demonstrate gender differences, mode-based priority/evaluation patterns, and constrained-choice effects, arguing that biases plausibly explain observed inertia and can be leveraged in agent-based simulations and serious-game policy experiments. The work provides open data and a method to initialise synthetic populations for mobility simulators, offering a practical path to test urban policies under bias-informed dynamics and to tailor interventions to diverse user profiles.
Abstract
In this paper, we describe a survey about the perceptions of 4 mobility modes (car, bus, bicycle, walking) and the preferences of users for 6 modal choice factors. This survey has gathered 650 answers in 2023, that are published as open data. In this study, we analyse these results to highlight the influence of 3 cognitive biases on mobility decisions: halo bias, choice-supportive bias, and reactance. These cognitive biases are proposed as plausible explanations of the observed behaviour, where the population tends to stick to individual cars despite urban policies aiming at favouring soft mobility. This model can serve as the basis for a simulator of mobility decisions in a virtual town, and the gathered data can be used to initialise this population with realistic attributes. Work is ongoing to design a simulation-based serious game where the player takes the role of an urban manager faced with planning choices to make their city more sustainable.