The Circular Economy is a growing research field and policy agenda. Yet, integrating the social dimensions of sustainability into the Circular Economy remains a challenge. The significance of reactions to an implemented Circular Economy is poorly understood.  Contrary to the narrative that consumer demand shapes supply, affordance theory stresses the significance of considering the exogenous physical context that shapes user decisions. Building on affordance theory and insights from the social sciences, this study develops an agent-based model, TransportTransform, to analyse the interactions of the individual-, meso-, and system-levels. The agent-based model connects individual mobility choices with network decision-making mechanisms. Looking at user decision-making on transportation modes, the model yields insights into the interaction of mode occupancy and social norms to assess system patterns of user behaviour. The model design was informed by eleven interviews with researchers in the field and is initialized with data from an empirical survey conducted in Germany. The TransportTransform agent-based model confirms the importance of affordances as an important factor in modal choice. Model results show the relevance of including habitual behaviour when modelling transport mode choice, with the car being the most popular mode, followed by biking and public transport. Incorporating mode occupancy significantly reduces car usage, offering potential policy avenues for redirecting mode capacities towards desired modes. The impact of social norms on mode choice was less pronounced, highlighting the need to further explore norm internalisation and the indirect effects of social norms in future model iterations. The study emphasizes the need for further model expansions to better understand the impact of Circular Economy policies on user decision-making. Overall, the study highlights the importance of considering the social dimensions of sustainability in the Circular Economy and provides a valuable framework and implemented agent-based model for analysing user behaviour in this context.