# Bridging the attitude-behaviour gap: An explanation of travel mode choice using analytical sociology

## TL;DR

This paper introduces xMooBe, a new model that explains why people's travel choices don't always match their attitudes, helping to improve sustainable transport policies.

## Contribution

The novel xMooBe model integrates attitudinal and choice-based approaches with analytical sociology to better explain transport mode decisions.

## Key findings

- xMooBe achieves up to 80% accuracy in explaining travel behavior.
- Contextual factors like car ownership and cycle network quality explain the attitude-behavior gap.
- The model identifies effective interventions for promoting sustainable transport choices.

## Abstract

The aim of this work is to improve the explanatory power of models of transport mode choice and thus contribute to the mobility transition. The authors develop a new model of mobility behaviour called xMooBe: It incorporates elements from attitudinal and choice models and combines them with a sociological theory of action, which has its roots in analytical sociology. xMooBe is based on a simple model of decision-making (with a manageable number of variables) and expands it by taking into account additional contextual factors such as car ownership and public transport availability. The study uses a mixed-methods approach that combines statistical analysis of survey data (including regression analysis), theory-based modelling of (bounded-rational) everyday decision making and thought experiments to identify options for behavioural change. Instead of relying on manifest statements of behavioural intentions, xMooBe applies an extended version of the subjective expected utility theory, which refers to latent preferences and subjective perceptions (plus contextual factors). The mixed-methods approach was used to validate xMooBe and to test different assumptions about (policy) measures that could influence transport mode choice in terms of sustainability. xMooBe achieves up to 80 percent accuracy in explaining behaviour – and thus differs from many other studies with partly inconsistent results. xMooBe helps to understand why people behave in ways that are inconsistent with their attitudes, e.g., in the case of car-using cyclists, and thus helps to bridge the gap between attitude and behaviour. In most cases, known contextual factors (such as car ownership, state of the cycle network, etc.) help to explain this gap. At the same time, they serve as a starting point for interventions whose potential impact has been tested through experimentation.