It depends: Platform dependence, schedule control, and satisfaction among gig workers on Amazon's Mechanical Turk platform

Abstract Understanding the risks and rewards of gig work requires examining how gig workers themselves feel about their work and how work satisfaction may vary even among workers on the same gig platform. Platform dependence theory posits that financially disadvantaged workers who depend on gig work for essential income will be less satisfied, in part, because they are less able to work their preferred schedules. These predictions, however, have not been tested quantitatively. Using survey data from workers who do gig microtasks on Amazon's Mechanical Turk platform (MTurk), we examine how platform dependence, schedule mismatches (between preferred and actual work schedules), and work stress are related to work satisfaction. We find that all three factors are associated with lower satisfaction. Furthermore, we find support for a hypothesized mediating mechanism: platform dependence lowers satisfaction, in part, because it is associated with more mismatches between workers' preferred and actual schedules. We conclude by discussing reforms that could improve satisfaction for all microtask workers.