  Ride-sourcing platforms such as Uber and Lyft offer drivers (i.e., platform
suppliers) considerable freedom of choice in multiple aspects. At the
operational level, drivers can freely accept or decline trip requests that can
significantly impact system performance in terms of travellers' waiting time,
drivers' idle time and income. Despite the extensive research into the
supply-side operations, the behavioural aspects, particularly drivers' ride
acceptance behaviour remains so far largely unknown. To this end, we reproduce
the dynamics of a two-sided mobility platform on the road network of Delft
using an agent-based simulator. Then, we implement a ride acceptance decision
model enabling drivers to apply their acceptance strategies. Our findings
reveal that drivers who follow the decision model, on average, earn higher
income compared to drivers who randomly accept trip requests. The overall
income equality between drivers with the acceptance decision is higher and
travellers experience lower waiting time in this setting.
