Solving the Ride-Sharing Productivity Paradox: Priority Dispatch and Optimal Priority Sets
| Autor: | Varun Krishnan, Ramon Iglesias, Sebastien Martin, Su Wang, Varun Pattabhiraman, Garrett Van Ryzin |
|---|---|
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | INFORMS Journal on Applied Analytics. 52:433-445 |
| ISSN: | 2644-0873 2644-0865 |
| DOI: | 10.1287/inte.2022.1134 |
| Popis: | Ride-sharing platforms face a “productivity paradox,” whereby any efficiency gained through improved dispatch or pricing strategies will not benefit drivers or riders. We show that this is a limit of the traditional ride-hailing model and a consequence of the Hall-Horton driver equilibrium earning hypothesis. In response to this challenge, Lyft introduced Priority Mode (PM), which allows drivers to concentrate their work during specific prioritized hours. We prove that PM solves the productivity paradox. As a result, the average driver earnings increase, and the platform and the riders also benefit. Implementing PM requires significant changes to the platform’s dispatch and pricing policy but most importantly requires careful control of the number of drivers that can be offered the opportunity to be prioritized at any given time. In this paper, we introduce a queuing setting to model the market dynamics of PM and illustrate the challenges of this control problem. We then leverage this intuition to build a real-time priority admission control system that can balance the number of drivers offered priority and achieve the desired productivity increase. Lyft has successfully rolled out PM throughout North America, and drivers have completed hundreds of thousands of driving hours thus far. It has generated tens of millions of dollars of value that the drivers, the riders, and Lyft have shared, with the potential to generate much more when rolled out in all markets. Finally, our internal driver surveys reveal that it has been well received by drivers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|