Alternative Title

Coordinating supply and demand on an on-demand platform: Price, wage, and payout ratio

Publication Type

Journal Article

Version

submittedVersion

Publication Date

6-2019

Abstract

We consider an on-demand service platform using earning sensitive independent providers with heterogeneous reservation price (for work participation) to serve its 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 present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a queueing model in the customer utility function to characterize the optimal price and wage rates that maximize the profit of the platform (as well as the total welfare). We first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price), and then extend our model to allow the platform to adopt a time-based payout ratio. We find that it is optimal for the platform to charge a higher price when demand increases; however, the optimal price is not necessarily monotonic when the provider capacity or the waiting cost increases. Furthermore, the platform should offer a higher payout ratio as demand increases, capacity decreases or customers become more sensitive to waiting time. We also find that the platform should lower its payout ratio as it grows with the number of providers and customer demand increasing at about the same rate. We use a set of actual data from a large on-demand ride-hailing platform to calibrate our model parameters in numerical experiments to illustrate some of our main insights.

Keywords

On-Demand Services, Endogenous Supply and Demand, Queueing Models

Discipline

Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering | Technology and Innovation

Research Areas

Intelligent Systems and Optimization

Publication

Manufacturing and Service Operations Management

Volume

21

Issue

3

First Page

556

Last Page

570

ISSN

1523-4614

Identifier

10.1287/msom.2018.0707

Publisher

INFORMS

Copyright Owner and License

Authors

Additional Files
msom.2018.0707-sm.pdf (471 kB)
Supplementary material with numerical illustrations

Additional URL

https://doi.org/10.1287/msom.2018.0707

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