Pooling Agents for Customer-Intensive Services

Zhongbin Wang (), Luyi Yang (), Shiliang Cui (), Sezer Ülkü () and Yong-Pin Zhou ()
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Zhongbin Wang: College of Management and Economics, Tianjin University, Tianjin 300072, China
Luyi Yang: Haas School of Business, University of California, Berkeley, Berkeley, California 94720
Shiliang Cui: McDonough School of Business, Georgetown University, Washington, DC 20057
Sezer Ülkü: McDonough School of Business, Georgetown University, Washington, DC 20057
Yong-Pin Zhou: Foster School of Business, University of Washington, Seattle, Washington 98195

Operations Research, 2023, vol. 71, issue 3, 860-875

Abstract: In customer-intensive services where service quality increases with service time, service providers commonly pool their agents and give performance bonuses that reward agents for achieving greater customer satisfaction and serving more customers. Conventional wisdom suggests that pooling agents reduce customer wait time while performance bonuses motivate agents to produce high-quality service, both of which should boost customer satisfaction. However, our queueing-game-theoretic analysis reveals that when agents act strategically, they may choose to speed up under pooling in an attempt to serve more customers, thus undermining service quality. If this happens, pooling can backfire and result in both lower customer satisfaction and agent payoff. We propose a simple solution to resolve this issue: pooling a portion of the performance bonuses (incentive pooling) in conjunction with pooling agents (operational pooling).

Keywords: Special Issue on Behavioral Queueing Science; quality-speed tradeoff; pooling; pay-for-performance; strategic server; customer satisfaction; agent payoff (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:71:y:2023:i:3:p:860-875

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