Attitudinal Tension & Moral Dilemma Dynamics: The Role of Psychological Determinants in Overcoming the Behaviour Inertia in Car Use

Tackling climate change has become a priority of the political agenda in many countries around the world. The problems related to global warming have been mainly attributed to human actions, as anthropogenic behaviours are responsible for the excess of CO2 and other greenhouse gases. Therefore, understanding the factors that drive these behaviours are the first step to create effective policies, in order to know how to change people’s non-environmentally friendly behaviours.

This thesis assesses the usefulness of system dynamics to create a simulation model that can explain the main theories proposed in environmental psychology to reduce car use. In the UK, transportation has become one of the major responsible for emitting more greenhouse gases than any other sector. Therefore, understanding the psychological determinants that impede drivers to consider alternative transport modes becomes essential to fight climate change.

Based on the data collected by Department for Transport (UK), this thesis tests several changes on psychological determinants that can trigger important changes in the levels of car use. The factors involved in explaining car use are described, as well as the causes that play a key role in determining the behavioural intention towards car use. The study reveals several feedback loops that explain individual’s car choice. It also demonstrates that creating multi-level interventions may be designed, so as to obtain important behavioural changes in this matter. For example, modifying car habit, as well as personal norms, and attitudes lead to faster changes than focusing on one variable at a time. In theoretical terms, the model reveals the supremacy of changing factors related to the Theory of Planned Behaviour (TPB), suggesting a reason it has become so popular. Nevertheless, the model demonstrates that modifying TPB alongside other factors from other theoretical frameworks lead to more satisfactory results.