Abstract for: Capturing Behavioural Diversity in Transport Decarbonisation by Integrating Persona-based Data in Car Ownership and Fleet Turnover Model of England

Transportation behaviours are influenced by entrenched socio-economic disparities which create uneven capacities and incentives for behavioural change, contributing to delays or resistance in shifts toward more sustainable travel. The contrast – yet inherent complementarity – between macro-level systemic modelling and micro-level behavioural insights suggests the potential for integrating the two approaches – system dynamics and human-centred design – to simulate how different community groups respond over time to decarbonisation transport policy interventions. We develop a system dynamics model showing how commuters choose between driving and public transport and how these choices affect fleet size, driving demand, and emissions. We identify which behaviours operate at the population level and which differ across community groups. We then describe the model’s baseline dynamics for England and analyse key feedback shaping mode choice before comparing outcomes once persona-level differences are introduced. This research advances systems thinking and system dynamics by demonstrating how behavioural diversity can be represented within a dynamic, feedback based modelling framework. This enhances the behavioural realism of system dynamics modelling and illustrates a novel approach for linking human centred insights with system level feedback structures, which contributes to understanding transport decarbonisation by analysing both population-level dynamics and the differentiated responses of distinct community groups with shared characteristics (e.g., personas). refine language