Courteous or Crude? Managing User Conduct to Improve On-Demand Service Platform Performance

Yunke Mai, Bin Hu, Saša Pekeč

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

In this paper, we study how an on-demand service platform could improve its performance through managing user conduct. In such a platform, service providers may reject certain platform-proposed service requests, and their responses, in turn, incentivize users to adjust their conduct. We develop an evolutionary game theory model of user conduct and provider responses that shows that the platform could improve user conduct through either setting a low wage for service providers or implementing priority matching. Building upon these results, we further model providers and users joining and leaving the platform by once again utilizing the evolutionary game theory approach. We find that wage setting alone is a blunt instrument to improve platform performance via managing user conduct, whereas supplementing the wage decision with priority matching could overcome its limitations and serve as an effective strategy to further improve platform performance in terms of growth and profitability. This finding suggests that matching prioritization could be an important strategy for managing platforms with user and provider heterogeneities. In addition, our analysis and results also demonstrate the potential of the evolutionary game theory approach for analyzing the impact of pricing and matching decisions on the performance of large markets.

Original languageEnglish
Pages (from-to)996-1016
Number of pages21
JournalManagement Science
Volume69
Issue number2
DOIs
StatePublished - Feb 2023

Bibliographical note

Publisher Copyright:
Copyright: © 2022 INFORMS.

Keywords

  • evolutionary game theory
  • on-demand service platform
  • priority matching

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

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