UCL School of Management

Research seminar

Arash Asadpour, Lyft


Tuesday, 19 November 2019
15:00 – 16:30
Research Group
Operations and Technology

UCL School of Management is delighted to welcome Arash Asadpour, Lyft, to host a research seminar discussing ‘Minimum Wage Regulation and the Stability of Marketplaces’ and ‘Escrow Payments: A Smoother Driver Pay Mechanism’

Abstract - ‘Minimum Wage Regulation and the Stability of Marketplaces’ 

Concerns about the welfare of sharing economy workers are motivating many localities to consider imposing minimum wage rules on such work. In particular, New York City enacted in 2019 a new minimum wage rule that applies to the four largest ridesharing companies in the city. This new regulation is unique in that it takes into account worker utilization in order to account for worker idle time. We analyze a potential instability that can arise under this regulation, where stability is defined as the ability of platforms to eventually earn non-negative profits while maintaining bounded wages and the current flexible (free-entry) work model. We identify conditions under which a utilization-based minimum wage causes instability and provide a precise characterization of the maximum hourly earnings that can be sustained in a stable marketplace given supply and demand curves. We also calibrate our model using elasticity estimates from the literature. Affected ridesharing companies are likely to implement driver entry restrictions into their marketplaces to avoid negative profits in response to such laws. (Joint work with Ilan Lobel and Garrett van Ryzin)

Abstract - ‘Escrow Payments: A Smoother Driver Pay Mechanism’
Dynamic pricing is a frequently used tool to match supply and demand in the gig economy. The comparatively fast-paced dynamics of supply and demand have also led to dynamic pricing featuring prominently in the recent operations research literature. In practice, ridesharing platforms like Lyft and Uber no longer employ the strictly proportional commission. Further, beyond the driver’s expected pay, the volatility in prices affects drivers’ decision-making. We discuss a mechanism to smooth the driver’s dynamic pay and analyze its properties in a stylized stochastic setting. We demonstrate both numerically and analytically the characteristics of the mechanism and discuss its potential benefits. (Join work with Daniel Freund and Garrett van Ryzin.)
Open to
PhD Programme
Last updated Wednesday, 20 November 2019