  The performance of ride-sourcing services such as Uber and Lyft is determined
by the collective choices of individual drivers who are not only chauffeurs but
private fleet providers. In such a context, ride-sourcing drivers are free to
decide whether to accept or decline ride requests assigned by the ride-hailing
platform. Drivers' ride acceptance behaviour can significantly influence system
performance in terms of riders' waiting time (associated with the level of
service), drivers' occupation rate and idle time (related to drivers' income),
and platform revenue and reputation. Hence, it is of great importance to
identify the underlying determinants of the ride acceptance behaviour of
drivers. To this end, we collected a unique dataset from ride-sourcing drivers
working in the United States and the Netherlands through a cross-sectional
stated preference experiment designed based upon disparate information conveyed
to the respondents. Using a choice modelling approach, we estimated the effects
of various existing and hypothetical attributes influencing the ride acceptance
choice. Employment status, experience level with the platform, and working
shift are found to be the key individual-specific determinants. Part-time and
beginning drivers who work on midweek days (Monday-Thursday) have a higher
tendency to accept ride offers. Results also reveal that pickup time, which is
the travel time between the driver's location and the rider's waiting spot, has
a negative impact on ride acceptance. Moreover, the findings suggest that a
guaranteed tip (i.e., the minimum amount of tip that is indicated upfront by
the prospective rider, a feature that is currently not available) and an
additional income due to surge pricing are valued noticeably higher than trip
fare. The provided insights can be used to develop customised matching and
pricing strategies to improve system efficiency.
