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Quantitative fairness for assessing perceived service quality in queues

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Abstract

Perceived service quality is eminent for service quality assessment from the customer perspective. As a major aspect of any service facility, customers expect a fair treatment. If human customers are involved in service operations, fairness significantly influences the perceived service quality and becomes crucial for customer satisfaction. Consequently, quantifying fairness in order to evaluate the degree of perceived fairness should be an integral part of service quality assessment. We consider quantitative fairness in the context of queueing systems and propose the discrimination frequency as an appropriate concept embedded in general service quality research. Proper formalization provides an extensible and flexible mathematical framework for assessing perceived service quality and customer satisfaction in queues with regard to the scheduling policy operated by the service provider.

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Notes

  1. See section 4.4 of Kleinrock (1976) entitled The Round-Robin Scheduling Algorithm.

  2. The notion of ergodicity is particularly well known for Markov chains. A Markov chain is ergodic iff it is positive recurrent, aperiodic and irreducible which can be obtained via properties of the states. However, for general stochastic processes, ergodicity is more complicated to define formally which we omit here. It suffices to know that ergodicity in our domain of interest is provided by stability of the queueing system.

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  1. Department of Applied Stochastics and Operations Research, Clausthal University of Technology, Erzstr. 1, 38678, Clausthal-Zellerfeld, Germany

    Werner Sandmann

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Sandmann, W. Quantitative fairness for assessing perceived service quality in queues. Oper Res Int J 13, 153–186 (2013). https://doi.org/10.1007/s12351-011-0111-9

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