Reference Dependence in Queue Design and Pricing Strategies

Jian Liu (), Yongpin Zhou (), Jian Chen () and Peng Li ()
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Jian Liu: Kummer Institute Center for Artificial Intelligence and Autonomous Systems, Missouri University of Science and Technology, Rolla, Missouri 65409; and Foster School of Business, University of Washington, Seattle, Washington 98195
Yongpin Zhou: Foster School of Business, University of Washington, Seattle, Washington 98195
Jian Chen: School of Economics and Management, Tsinghua University, Beijing 100084, China
Peng Li: School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China

Service Science, 2024, vol. 16, issue 4, 272-296

Abstract: This research investigates the effect of reference dependence on waiting times in service systems which formerly used a first-in-first-out (FIFO) service but have introduced a priority line with a fee. Our model combines reference-dependent gain-loss utility with standard customer utility, and we posit that customers are pleased with shorter-than-expected waiting times, whereas longer-than-expected times lead to dissatisfaction and an increased likelihood of balking. The study explores two scenarios: a captive customer system (CCS) and a noncaptive customer system (NCCS), with a focus on optimal pricing and segmentation strategies for revenue and social welfare maximization. The results reveal that, in a CCS, the service provider should implement observed and unobserved customer segmentation to optimize revenue and social welfare, respectively. In an NCCS, the impact of customer segmentation on revenue maximization depends on the value of regular customers, their loss reference-dependent preferences, and the system’s offered load. Alternatively, if the service provider seeks to maximize social welfare, the provider’s use of customer segmentation relies solely on the system’s offered load and customers’ reference-dependent preferences. Our findings also indicate that reference dependence can have varying impacts under different conditions, suggesting the effectiveness of tailored service and pricing strategies. Notably, a CCS generates more revenue than does an NCCS because of its captive nature, and, surprisingly, increasing the service rate can decrease revenue while improving social welfare. These insights have significant implications for service management strategies for a CCS and an NCCS.

Keywords: nonpreemptive M/M/1 service system; customer segmentation; reference dependence; psychological impact; revenue and social welfare (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orserv:v:16:y:2024:i:4:p:272-296

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