The Selection and Assessment of Gig Economy Workers

Abstract

The latest iteration of the gig economy (e.g., ridesharing through apps like Uber) comprises a litany of differences from the traditional work setting. How well does industrial-organizational psychology apply in a situation with no boss and no coworkers, legal limits on the amount of training that can be provided, and an algorithm assigning the work? This chapter first summarizes the key contextual factors that we should consider in understanding the selection and assessment of gig workers. Then it reports on the state of our knowledge about the recruitment and attraction of gig workers; the self-selection, platform selection, and client selection processes that occur; and the assessment and development of gig worker performance. Throughout all of these, one can see the impact of algorithmic management practices. There is also a quick summary of salient points about attrition, and the chapter closes with additional and broader considerations for our continued research on the selection and assessment of gig workers.