The Distributional Impact of Fatigue on Performance

船员 工作量 差异(会计) 分位数 服务(商务) 分位数回归 工作(物理) 运营管理 统计 计算机科学 计量经济学 业务 数学 经济 营销 工程类 航空学 机械工程 会计 操作系统
作者
Hessam Bavafa,Jónas Oddur Jónasson
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
被引量:1
标识
DOI:10.1287/mnsc.2023.4855
摘要

Little is known about how people-centric factors affect the shape of service time distributions despite distributional statistics (variance or quantiles) being key drivers of system performance in many service industries. We investigate the impact of one people-centric factor—worker fatigue—on the average, variance, and quantiles of service times in paramedic operations. Our analysis uses data on the performance of 368,634 paramedic teams in the London Ambulance Service over 10 years. We measure fatigue by the number of prior jobs a paramedic crew has completed during a shift and estimate its impact on the time it takes the crew to respond to incidents and bring patients to hospitals. Using a recentered influence function regression approach with multiple fixed effects, we find that the average time to hospital increases by 5% throughout the course of an average shift. In addition, the workers become less consistent with fatigue; service time variance increases by 39% during a normal shift. Furthermore, we find that in addition to an upward shift in mean service times, both the upper and lower tails of the distribution have more weight for fatigued paramedics. These effects are driven mostly by the performance of paramedics at the scene, rather than their driving to or from the incident. The distributional effects of fatigue are only slightly mitigated by increased experience or reduced system workload. Our work demonstrates that the impact of people-centric factors can be highly nonuniform across the service time distribution. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: The authors are grateful for financial research support from the Wisconsin Alumni Research Foundation at the University of Wisconsin–Madison. Supplemental Material: The data files and e-companion are available at https://doi.org/10.1287/mnsc.2023.4855 .
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