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Signaling Quality Via Queues

Authors: Laurens G. Debo; Christine Parlour; Uday Rajan;

Signaling Quality Via Queues

Abstract

We consider an M/M/1 queueing system with impatient consumers who observe the length of the queue before deciding whether to buy the product. The product may have high or low quality, and consumers are heterogeneously informed. The firm chooses a slow or (at a cost) a fast service rate. In equilibrium, informed consumers join the queue if it is below a threshold. The threshold varies with the quality of the good, so an uninformed consumer updates her belief about quality on observing the length of the queue. The strategy of an uninformed consumer has a “hole”: she joins the queue at lengths both below and above the hole, but not at the hole itself. We show that if the prior probability the product has high quality and the proportion of informed consumers are both low, a high-quality firm may select a slower service rate than a low-quality firm. The queue can therefore be a valuable signaling device for a high-quality firm. Strikingly, in some scenarios, the high-quality firm may choose the slow service rate even if the technological cost of speeding up is zero. This paper was accepted by Assaf Zeevi, stochastic models and simulation.

Keywords

games-group decisions, stochastic, probability, stochastic model applications, queues, birth-death

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
110
Top 1%
Top 10%
Top 10%
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