Optimal Strategy and System Performance in a Feedback Queue with Customer-intensive Services and Boundedly Rational Customers

Yang Song () and Xinying Liu ()
Additional contact information
Yang Song: Nanjing University of Aeronautics and Astronautics
Xinying Liu: Nanjing University of Aeronautics and Astronautics

Methodology and Computing in Applied Probability, 2025, vol. 27, issue 1, 1-16

Abstract: Abstract In this paper, we consider a feedback queue with one server providing customer-intensive services. The service reward increases with service time, while extended service time results in longer waiting time. Customers are boundedly rational and decide whether to join the system based on a logit model upon their arrival. From the perspective of revenue maximization and social welfare maximization, this paper considers the trade-off between speed and quality of service, also studies the optimal service rate, service price and some system performances. Under two different strategies, we study the price of anarchy (PoA), i.e., the ratio of corresponding welfare, which quantifies the harm of service provider’s selfish behavior, and we obtain the interval of PoA and its characteristics. Additionally, we conduct numerical simulations to illustrate the quantitative outcomes of system operations.

Keywords: Feedback queue; Optimal strategy; Customer-intensive services; Bounded rationality; Price of anarchy; 90B22 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-025-10144-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:27:y:2025:i:1:d:10.1007_s11009-025-10144-y

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-025-10144-y

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().