Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers

64 Pages Posted: 30 Aug 2016 Last revised: 21 Dec 2017

Jiaru Bai

SUNY at Binghamton - School of Management

Kut C. So

University of California, Irvine - Paul Merage School of Business

Christopher S. Tang

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area

Xiqun Chen

Zhejiang University

Hai Wang

Singapore Management University - School of Information Systems

Date Written: December 20, 2017

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

JEL Classification: R41

Suggested Citation

Bai, Jiaru and So, Kut C. and Tang, Christopher S. and Chen, Xiqun and Wang, Hai, Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers (December 20, 2017). Available at SSRN: https://ssrn.com/abstract=2831794 or http://dx.doi.org/10.2139/ssrn.2831794

Jiaru Bai (Contact Author)

SUNY at Binghamton - School of Management ( email )

P.O. Box 6015
Binghamton, NY 13902-6015
United States

HOME PAGE: http://jiarubai.net

Kut C. So

University of California, Irvine - Paul Merage School of Business ( email )

Irvine, CA California 92697-3125
United States

Christopher S. Tang

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

HOME PAGE: http://www.anderson.ucla.edu/x980.xml

Xiqun Chen

Zhejiang University ( email )

38 Zheda Road
Hangzhou, Zhejiang 310058
China

Hai Wang

Singapore Management University - School of Information Systems ( email )

School of Information Systems
80 Stamford Road
Singapore 178902, 178899
Singapore

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