The Effect of a Service Experience Cost on a Queueing System

Xuelu Zhang,Qing Ma

doi:10.1155/2021/6223808

Abstract

In this work, the authors consider the effect of a service experience cost (SE cost) on customer behaviour in the M/M/1 queueing system. Based on customer individual equilibrium strategy, social welfare is also analyzed in unobservable and observable cases. The SE cost decreases the equilibrium joining probability and social welfare in an unobservable case. However, there might exist multiple individual equilibrium thresholds in an observable case. Furthermore, numerical results show that the SE cost can be used as a feasible policy to make an incentive for customers and regulate the system for improved social welfare in some scenarios.

Highlights

Service experience is a term to describe the feeling of customers
(1) depressed consumers may feel open in a spacious fast-food restaurant, while lonely consumers may feel at home in a little fast-food restaurant
Lonely consumers might be more frustrated in the spacious environment, and unhappy consumers might be more agitated in the narrow environment

Summary

Introduction

Service experience is a term to describe the feeling of customers. the sense of each customer may be different, which depends on the service environment. Service experience should be considered in the study of customer behaviour and social welfare. The benefit function of individual customers generally includes the reward (or the degree of satisfaction) received after service and the sojourn cost in the system as. To reflect the effect of service experience on customer behaviour, the authors first establish a simple net benefit function as follows:. Is work considers an individual equilibrium strategy in unobservable and observable cases and analyzes social welfare. 2. Model Description is work considers the M/M/1 queueing system where customers arrive according to a Poisson process with rate λ, and service times are independent and exponentially distributed with mean μ− 1. Conditioning on the number of customers in the system is observed or not, there are two cases as follows:

The Unobservable Case

The Observable Case

Numerical Experiments

Conclusions