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The potentially negative effects of cooperation in service systems

Part of: Operations research and management science Special processes

Published online by Cambridge University Press:  29 April 2020

Hakjin Chung ,
Hyun-Soo Ahn  and
Rhonda Righter
Hakjin Chung*
Affiliation:
Korea Advanced Institute of Science and Technology
Hyun-Soo Ahn*
Affiliation:
University of Michigan
Rhonda Righter*
Affiliation:
University of California, Berkeley
*
*Postal address: KAIST College of Business, Seoul, 02455, Republic of Korea. Email address: [email protected]
**Postal address: Ross School of Business, University of Michigan, Ann Arbor, MI 48109, USA. Email address: [email protected]
***Postal address: Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720, USA. Email address: [email protected]
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Abstract

The ‘Price of Anarchy’ states that the performance of multi-agent service systems degrades with the agents’ selfishness (anarchy). We investigate a service model in which both customers and the firm are strategic. We find that, for a Stackelberg game in which the server invests in capacity before customers decide whether or not to join, there can be a ‘Benefit of Anarchy’, that is, customers acting selfishly can have a greater overall utility than customers who are coordinated to maximize their overall utility. We also show that customer anarchy can be socially beneficial, resulting in a ‘Social Benefit of Anarchy’. We show that such phenomena are rather general and can arise in multiple settings (e.g. in both profit-maximizing and welfare-maximizing firms, in both capacity-setting and price-setting firms, and in both observable and unobservable queues). However, the underlying mechanism leading to the Benefit of Anarchy can differ significantly from one setting to another.

Keywords

QueueingPrice of Anarchybalkingindividual versus social welfare

MSC classification

Primary: 90B22: Queues and service
Secondary: 60K25: Queueing theory
Type
Original Article
Information
Advances in Applied Probability , Volume 52 , Issue 1 , March 2020 , pp. 319 - 347
Copyright
© Applied Probability Trust 2020

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