Impact of Server Capability on Pooling Configuration in Stochastic Service Systems

Resource pooling is often introduced in service systems to cope with the variability in customer demand. The primary motivation behind creating a more flexible system is to utilize resources efficiently—namely, assigning customers whose dedicated resources are fully occupied to available non-dedicated resources (referred to as off-service placement). In such a setup, the service system manager expects to serve more customers within a fixed timeframe. However, recent empirical evidence shows that, due to limited server capability, the service time at non-dedicated providers can be significantly longer than that at dedicated ones. In this study, we develop a two-server stochastic model to examine how server capability levels and other factors—such as overall workload and demand asymmetry—affect pooling configurations. We derive conditions that specify the optimal system flexibility configuration across these parameters. Our findings reveal that a partially flexible system can outperform a fully flexible one, particularly in asymmetric scenarios with low server capability. This advantage is also pronounced when considering a range of system costs, including server capability, cross-serving, and other related costs in stochastic service systems with and without buffers. These insights from our two-server model offer guidance on designing more efficient flexibility in complex multi-class, multi-server service systems.

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Publication Details

Journal
Production and Operations Management
Published
2026-01-13
DOI
https://doi.org/10.1177/10591478261417819
Primary Topic
Advanced Queuing Theory Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Impact of Server Capability on Pooling Configuration in Stochastic Service Systems

Taozeng Zhu, Yanting Chen, Zhe George Zhang, Nan Yang et al.
Production and Operations Management
Advanced Queuing Theory Analysis
article

Impact of Server Capability on Pooling Configuration in Stochastic Service Systems

Taozeng Zhu, Yanting Chen, Zhe George Zhang, Nan Yang, Jingui Xie
article en

Abstract

Resource pooling is often introduced in service systems to cope with the variability in customer demand. The primary motivation behind creating a more flexible system is to utilize resources efficiently—namely, assigning customers whose dedicated resources are fully occupied to available non-dedicated resources (referred to as off-service placement). In such a setup, the service system manager expects to serve more customers within a fixed timeframe. However, recent empirical evidence shows that, due to limited server capability, the service time at non-dedicated providers can be significantly longer than that at dedicated ones. In this study, we develop a two-server stochastic model to examine how server capability levels and other factors—such as overall workload and demand asymmetry—affect pooling configurations. We derive conditions that specify the optimal system flexibility configuration across these parameters. Our findings reveal that a partially flexible system can outperform a fully flexible one, particularly in asymmetric scenarios with low server capability. This advantage is also pronounced when considering a range of system costs, including server capability, cross-serving, and other related costs in stochastic service systems with and without buffers. These insights from our two-server model offer guidance on designing more efficient flexibility in complex multi-class, multi-server service systems.

Production and Operations Management
Dongbei University of Finance and Economics (CN), University of Shanghai for Science and Technology (CN), Simon Fraser University (CA), Western Washington University (US), Technical University of Munich (DE)
Openalex Percentile: Top 91%
Advanced Queuing Theory Analysis
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