Abstract

This paper studies optimal information revelation policies in discrete-time \begin{document}$Geo/Geo/1$\end{document} queue. Revealing the queue length information to arriving customers plays an important role in their decision making, that is, whether to join the system or balk. We consider policies where a service provider discloses information to some customers and conceals it from others, depending upon the number of waiting customers. This partial information disclosure policy helps the service provider minimize the idle period of the system and maximize the revenue.

Highlights

  • In the recent years, there has been an emerging trend to study queueing systems related to economic analysis and strategic customer behavior

  • We find an optimal information policy, that is, the selective threshold information disclosure policy that maximizes the revenue

  • The decision of an arriving customer is considerably dependent on the information; he has acquired about the queue length at the instant of his arrival

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Summary

Introduction

There has been an emerging trend to study queueing systems related to economic analysis and strategic customer behavior. Edelson and Hilderbrand [5] complemented the above study by considering the corresponding unobservable M/M/1 queue, where the arriving customers make their decision without observing the number of customers in the queue In such studies, a certain cost-reward structure is levied on the queueing system. A customer acts strategically and enters the queue only when the expected waiting cost is less than the reward received upon being served This holds true in both the observable and unobservable cases. VEENA GOSWAMI AND GOPINATH PANDA system parameters like cost and expected waiting time Most of these systems assume that providing the queue-length information helps customers to optimize their expected payoffs. The purpose of this work is to ascertain the conditions in discrete-time queues where the service provider may optimize its revenue by employing both observable and unobservable cases. The service discipline is taken to be first-come first-served (FCFS)

We assume ρ
We assume this
Using the normalization condition
The average sojourn time of an uninformed arriving customer is
Conclusions

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