The rise of e-hailing services has transformed urban transportation, offering on-demand rides via mobile apps that outpace traditional taxis and fixed public transport schedules. These services enhance mobility for diverse user needs, optimizing efficiency by matching riders with nearby drivers and reducing urban congestion. Trust becomes one of the critical success factors towards this acceptance. Current trust models often lack empirical validation through practical simulations. This paper addresses this gap by proposing an agent-based computational model to simulate trust dynamics within e-hailing services. Through extensive simulation experiments and mathematical analyses, our model explores the interplay of trust among individual users and communities, aiming to enhance understanding and predict trust behaviours in complex service environments. Future research will focus on developing community-aware analytics to effectively monitor and intervene in trust dynamics.