Threshold-based incentives for ride-sourcing drivers: Implications on supply management and welfare effects

Ride-sourcing companies have been widely using threshold-based incentive programs to encourage drivers to extend their work hours. In such programs, a driver receives a certain amount of monetary reward if she completes a given supply task within a predetermined time window. However, despite the popularity of these incentives, little is known about how drivers respond to them in practice, and currently, there are no means to comprehensively evaluate and optimize their designs. To fill the void, the authors develop a dynamic discrete choice model that formulates ride-sourcing drivers’ working decisions influenced by threshold-based incentives and then calibrate it using real-world data from a ride-sourcing company. The authors' results provide fresh insights into the market and welfare effects of the threshold-based incentive and its various designs. It is found that the threshold-based incentive could increase welfare significantly for full-time drivers but marginally for part-time drivers. In contrast, involving part-time drivers in the incentive programs generally can yield higher profits for the platform, while incentivizing full-time drivers is mostly unprofitable. On incentive design, the incentive threshold and reward must be closely paired for different driver groups to avoid inferior consequences for the platform and drivers. In addition, switching from threshold-based incentives to direct wage increments may benefit both full-time drivers and the ride-sourcing company.

• Record URL:
  • https://doi.org/10.1016/j.trc.2023.104323
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0968090X23003121
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Liu, Tianming
  • Xu, Zhengtian
  • 0000-0001-5626-285X
  • Vignon, Daniel
  • 0000-0002-8190-3564
  • Yin, Yafeng
  • 0000-0003-3117-5463
  • Qin, Zhiwei
  • Li, Qingyang
• Publication Date: 2023-11

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 104323
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 156
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Decision making; Incentives; Labor market; Optimization; Profits; Ridesourcing
• Identifier Terms: Didi Chuxing; Lyft; Uber
• Subject Areas: Administration and Management; Economics; Finance; Highways; Public Transportation;

Filing Info

• Accession Number: 01894325
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 25 2023 2:46PM