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Characteristics of service requests and service processes of fire and rescue service dispatch centers

Analysis of real world data and the underlying probability distributions

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Abstract

A sufficient staffing level in fire and rescue dispatch centers is crucial for saving lives. Therefore, it is important to estimate the expected workload properly. For this purpose, we analyzed whether a dispatch center can be considered as a call center. Current call center publications very often model call arrivals as a non-homogeneous Poisson process. This bases on the underlying assumption of the caller’s independent decision to call or not to call. In case of an emergency, however, there are often calls from more than one person reporting the same incident and thus, these calls are not independent. Therefore, this paper focuses on the dependency of calls in a fire and rescue dispatch center. We analyzed and evaluated several distributions in this setting. Results are illustrated using real-world data collected from a typical German dispatch center in Cottbus (“Leitstelle Lausitz”). We identified the Pólya distribution as being superior to the Poisson distribution in describing the call arrival rate and the Weibull distribution to be more suitable than the exponential distribution for interarrival times and service times. However, the commonly used distributions offer acceptable approximations. This is important for estimating a sufficient staffing level in practice using, e.g., the Erlang-C model.

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Acknowledgements

The authors thank the three anonymous referees for their very helpful and constructive comments and suggestions.

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Authors and Affiliations

  1. Brandenburg University of Technology, 03046, Cottbus, Germany

    Ute Krueger

  2. University of Hohenheim, 70599, Stuttgart, Germany

    Katja Schimmelpfeng

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  1. Ute Krueger
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  2. Katja Schimmelpfeng
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Correspondence to Katja Schimmelpfeng.

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Krueger, U., Schimmelpfeng, K. Characteristics of service requests and service processes of fire and rescue service dispatch centers. Health Care Manag Sci 16, 1–13 (2013). https://doi.org/10.1007/s10729-012-9207-x

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