Dynamic pricing in a labor market: Surge pricing and flexible work on the Uber platform

This paper studies how the dynamic pricing of tasks in the “gig” economy influences the supply of labor. A large economic literature has explored labor supply when workers can flexibly choose how long to work each day. In a study of taxi drivers, Camerer et al. (1997) claim that drivers quit when they hit a daily income target, consequently driving less when hourly earnings are high. If general, this behavior would undermine the benefits of emerging “sharing economy” markets where tasks are dynamically priced. In this paper, we study how driver-partners on the Uber platform respond to the dynamic pricing of trips, known as “surge” pricing. In contrast to income-target findings, we find that Uber partners drive more at times when earnings are high, and flexibly adjust to drive more at high surge times. A discontinuity design confirms that these effects are causal, and that surge pricing significantly increases the supply of rides on the Uber system. We discuss the implications of these findings for earnings, flexible work, and the efficiency of dynamically-priced labor markets.

Chen, M. and Sheldon, M. (2016), Dynamic pricing in a labor market: Surge pricing and flexible work on the Uber platform, UCLA Anderson.

Metadata

  • Uber
  • transport
  • On-location platform-determined routine work
  • United States
  • 2016
  • Research publication, Case study-worker
  • income, motivation, autonomy, flexibility and control
  • English
  • UCLA Anderson (Research institute)
  • Quantitative research
  • Open access
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