On Optimal Pricing of Services in On-demand Labor Platforms
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I consider the optimal pricing problem faced by a freelance worker on an on-demand labor platform. Service requests arriving while the worker is busy are lost forever. Thus an hourly (or per-unit-time in general) pricing strategy appropriately captures the opportunity cost of accepting a job. With the view of improving capacity utilization in the face of arrival uncertainty, the worker may be tempted to subsidize longer jobs by offering a lower hourly rate as compared to shorter jobs, even if the customers' hourly willingness to pay is believed to be statistically identical across jobs. I show that this intuition is unfounded. If the customer arrival process is Poisson, then the optimal policy charges an identical hourly rate for all jobs irrespective of their length. This result holds even when earnings are discounted over time. I derive the optimal pricing policy in this case under standard regularity assumptions.
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