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

  • Jiaru Bai
  • , Kut C. So
  • , Christopher S. Tang
  • , Xiqun (Michael) Chen
  • , Hai Wang
  • University of California at Irvine
  • University of California at Los Angeles
  • Zhejiang University
  • Singapore Management University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationSpringer Series in Supply Chain Management
PublisherSpringer Nature
Pages115-136
Number of pages22
DOIs
StatePublished - 2019

Publication series

NameSpringer Series in Supply Chain Management
Volume6
ISSN (Print)2365-6395
ISSN (Electronic)2365-6409

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