Investigating sensitivity and the impact of information on pricing decisions in an M/M/1/ ∞ queueing model

Larsen, Christian

doi:10.1016/s0925-5273(98)00072-3

Cited by 42 publications

(24 citation statements)

References 8 publications

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“…The long-run revenue rate at the server, denoted by R, is given by pµ(1 − π 0 ), e.g., see Larsen (1998). It follows that the long-run effective arrival rate at the system, denoted by λ ef f , is:…”

Section: Model Of Customer (Mis-)informationmentioning

confidence: 99%

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Cui

Veeraraghavan

2013

SSRN Journal

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In many service settings, customers have to join the queue without being fully aware of the parameters of the service provider (for e.g., customers at check-out counters may not know the true service rate prior to joining). In such "blind queues", customers make their joining/balking decisions based on the limited information about the service provider's operational parameters (from past service experiences, reviews, etc.), and queue lengths. We analyze a firm serving customers making decisions under arbitrary beliefs about the service parameters in an observable queue for a service with known price.We propose an ordering for the balking threshold distributions in customer population, which allows for comparing the effects of customer beliefs on the queue. We show that while revealing the service information to customers improves revenues under certain conditions, it may however destroy consumer welfare or social welfare. Given a market size, the consumer welfare can be significantly reduced when a fast server announces its true service parameter. When revenue is higher under some beliefs, one would expect the congestion to also be higher because more customers join, but we show the congestion may not necessarily increase.

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Section: Model Of Customer (Mis-)informationmentioning

confidence: 99%

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Cui

Veeraraghavan

2013

SSRN Journal

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“…Each node has a route buffer for providing users the queue space to wait for forwarding. Unlike the model in [13], the route buffer in our model is finite with a buffer length . Therefore, we formulate an / /1/ queuing game model for resource optimization of a single node.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Queuing Game Theory Based Optimal Routing Scheme for Heterogeneous Users over Space Information Networks

Guo

Gong

et al. 2017

Mathematical Problems in Engineering

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An optimal routing scheme in space information networks was presented to balance network loads for heterogeneous users. According to the competition among the nodes, the model was built based on queuing game theory. The virtual routing platform was in charge of resources allocation and route selection. It got user's gain to decide which node the user joined in. Owning to the existing of heterogeneous users, an optimal admission fee needed to be obtained to avoid congestion. In our model, firstly, the whole welfare of the system was formulated. Then the optimal admission fee was calculated through maximizing the whole welfare. Meanwhile, the average maximum queue length was generated to set the buffer space of the node. At last, a routing factor was introduced into the route algorithm in order that the optimal routing could be selected by heterogeneous users. As a result, the system welfare reaches the maximum.

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“…The authors show that in general, when waiting in the queue is costly, the equilibrium behavior is not of the threshold type. Other results on the value of information in queueing systems are discussed in [2,13,15,19]. Arnott, de Palma, and Lindsey [3,4] analyze effects of information on participation and time-of-use decisions in congestible systems, when capacity and demand fluctuate.…”

Section: Related Literaturementioning

confidence: 99%

Equilibrium customers’ choice between FCFS and random servers

Hassin

2009

Queueing Syst

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Consider two servers of equal service capacity, one serving in a first-come first-served order (FCFS), and the other serving its queue in random order. Customers arrive as a Poisson process and each arriving customer observes the length of the two queues and then chooses to join the queue that minimizes its expected queueing time. Assuming exponentially distributed service times, we numerically compute a Nash equilibrium in this system, and investigate the question of which server attracts the greater share of customers. If customers who arrive to find both queues empty independently choose to join each queue with probability 0.5, then we show that the server with FCFS discipline obtains a slightly greater share of the market. However, if such customers always join the same queue (say of the server with FCFS discipline) then that server attracts the greater share of customers.

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Investigating sensitivity and the impact of information on pricing decisions in an M/M/1/ ∞ queueing model

Cited by 42 publications

References 8 publications

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Queuing Game Theory Based Optimal Routing Scheme for Heterogeneous Users over Space Information Networks

Equilibrium customers’ choice between FCFS and random servers

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