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Strategic Customer Behaviors in Observable Multi-server Batch Service Queueing Systems with Shared Fee and Server Maintenance Cost

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Performance Evaluation Methodologies and Tools (VALUETOOLS 2022)

Abstract

We consider an observable multi-server batch service queueing model where a shared server admission fee and maintenance cost for the monopolist are considered. Specifically, customers observe the number of full batches and waiting customers for an uncompleted batch, and then afterward decide to join or balk depending on their utility function. We analyze strategic customer behavior and find the equilibrium strategy. We also show numerical results for social welfare and monopolist’s revenue in various settings depending on fee, batch size, and number of servers. Based on our results, we discuss the existence of optimal fee, batch size, and number of servers.

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Authors and Affiliations

  1. Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan

    Ayane Nakamura

  2. Institute of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan

    Tuan Phung-Duc

Authors
  1. Ayane Nakamura
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  2. Tuan Phung-Duc
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Corresponding author

Correspondence to Ayane Nakamura .

Editor information

Editors and Affiliations

  1. University of Iceland, Reykjavik, Iceland

    Esa Hyytiä

  2. Indian Institute of Technology Bombay, Mumbai, India

    Veeraruna Kavitha

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Nakamura, A., Phung-Duc, T. (2023). Strategic Customer Behaviors in Observable Multi-server Batch Service Queueing Systems with Shared Fee and Server Maintenance Cost. In: Hyytiä, E., Kavitha, V. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 482. Springer, Cham. https://doi.org/10.1007/978-3-031-31234-2_1

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  • DOI: https://doi.org/10.1007/978-3-031-31234-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31233-5

  • Online ISBN: 978-3-031-31234-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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