Reproduce “Driver Surge Pricing” on OpenResearch
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About this paper
Nikhil Garg, Hamid Nazerzadeh
This research develops incentive-compatible pricing mechanisms for ride-hailing platforms facing dynamic, stochastic demand, demonstrating theoretically and empirically that additive driver surge mechanisms are more effective than multiplicative surge at aligning driver incentives and enhancing marketplace reliability.
Key insights
- Multiplicative surge pricing is inherently not incentive-compatible in dynamic, stochastic environments due to temporal externalities, leading drivers to strategically reject certain trips to maximize future earnings.
- Incentive-compatible pricing must explicitly account for the probability of market state changes during a trip, compensating drivers for potential lost opportunities in more lucrative future states.
- The feasibility of achieving full incentive compatibility, where drivers accept all trips, depends on a specific ratio of target earning rates between non-surge and surge states.
Summary by alphaXiv.
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