Revenue Management on an On-Demand Service Platform
Vijay Kamble

TL;DR
This paper analyzes optimal pricing strategies for freelance workers on on-demand platforms, revealing conditions under which uniform or differentiated pricing is optimal, and providing practical methods for setting prices in competitive environments.
Contribution
It establishes when price discrimination is necessary based on customer classes and arrival processes, and offers an iterative procedure for computing optimal prices.
Findings
Uniform pricing is optimal under Poisson arrivals.
Price discrimination is needed with customer class heterogeneity.
The proposed iterative method efficiently computes optimal prices.
Abstract
I consider the optimal hourly (or per-unit-time in general) pricing problem faced by a freelance worker (or a service provider) on an on-demand service platform. Service requests arriving while the worker is busy are lost forever. Thus, the optimal hourly prices need to capture the average hourly opportunity costs incurred by accepting jobs. Due to potential asymmetries in these costs, price discrimination across jobs based on duration, characteristics of the arrival process, etc., may be necessary for optimality, even if the customers' hourly willingness to pay is identically distributed. I first establish that such price discrimination is not necessary if the customer arrival process is Poisson: in this case, the optimal policy charges an identical hourly rate for all jobs. This result holds even if the earnings are discounted over time. I then consider the case where the customers…
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