Pricing strategy and collusion in a market with delay sensitivity

Liron Ravner, Noam Shamir

Research output: Contribution to journalArticlepeer-review

Abstract

Collusion describes a situation in which firms coordinate their strategies to increase their profit compared with the competitive outcome. In this work, we explore the incentives and ability of service providers, serving delay-sensitive customers to form a cartel. To do so, we develop an infinitely repeated game in which two service providers, each modeled as an M/M/1 queue, interact in the market repeatedly. We demonstrate that the incentives to collude depend on the competitive landscape in the market. When the competition in the market is high the incentives to form a cartel are strong since the cartel allows the service providers to extract all the surplus from the customers. However, operating under these market conditions does not imply that the ability to collude exists as well. We discuss the effect of market parameters such as delay sensitivity, service value and capacity level on the ability of the service providers to collude. We show that a high service value, high delay sensitivity and asymmetric capacity levels can actually hurt the service providers as they may impede their ability to form the cartel. We further discuss the welfare implications of collusive behavior, and the way it affects the incentives to invest in capacity.

Original languageEnglish
Pages (from-to)577-602
Number of pages26
JournalNaval Research Logistics
Volume68
Issue number5
DOIs
StatePublished - Aug 2021

Bibliographical note

Funding Information:
The authors thank the editor, Opher Baron, the AE and the anonymous referees for their guidance and constructive comments. Noam Shamir was partially supported by the Henry Crown Institute of Business Research in Israel.

Publisher Copyright:
© 2020 Wiley Periodicals, Inc.

Keywords

  • capacity
  • collusion
  • pricing
  • repeated games

ASJC Scopus subject areas

  • Modeling and Simulation
  • Ocean Engineering
  • Management Science and Operations Research

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