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Time-Based Payout Ratio for Coordinating Supply and Demand on an On-Demand Service Platform

  • Jiaru BaiEmail author
  • Kut C. So
  • Christopher S. Tang
  • Xiqun (Michael) Chen
  • Hai Wang
Chapter
Part of the Springer Series in Supply Chain Management book series (SSSCM, volume 6)

Abstract

Many on-demand service platforms use a fixed payout ratio (i.e., the percentage of the platform’s revenue that is paid to the providers) regardless of the customer demand and the number of participating providers that tend to vary over time. In this chapter, we examine the implications of time-based payout ratios. To do so, we first present a queueing model with endogenous supply (number of participating providers) and endogenous demand (customer request rate) to model this on-demand service platform. In our model, earnings-sensitive independent providers have heterogeneous reservation price (for work participation) to serve wait-time and price-sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We use the steady state performance (associated with the M/M/1 queue) in equilibrium to characterize the optimal price, optimal wage and optimal payout ratio that maximize the profit of the platform. We find that it is optimal for the platform to offer time-based payout ratios by offering a higher payout ratio during peak hours and a lower payout ratio during non-peak hours.

Notes

Acknowledgements

The authors are grateful to Didi Chuxing (www.xiaojukeji.com) for providing us some sample data. The authors also thank Professors Ming Hu and Terry Taylor for their constructive comments on an earlier version of this paper. This paper was completed when the third author was serving as a visiting professor of the Institute for Advanced Study at the Hong Kong University of Science and Technology.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jiaru Bai
    • 1
    Email author
  • Kut C. So
    • 2
  • Christopher S. Tang
    • 3
  • Xiqun (Michael) Chen
    • 4
  • Hai Wang
    • 5
  1. 1.School of ManagementBinghamton UniversityBinghamtonUSA
  2. 2.The Paul Merage School of BusinessUniversity of CaliforniaIrvineUSA
  3. 3.Anderson SchoolUniversity of California, Los AngelesLos AngelesUSA
  4. 4.College of Civil Engineering and ArchitectureZhejiang UniversityHangzhouChina
  5. 5.School of Information SystemsSingapore Management UniversitySingaporeSingapore

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