Paper detail

Revenue Maximization in Service Systems with Heterogeneous Customers

In this paper, we consider revenue maximization problem for a two server system in the presence of heterogeneous customers. We assume that the customers differ in their cost for unit delay and this is modeled as a continuous random variable with a distribution $F.$ We also assume that each server charges an admission price to each customer that decide to join its queue. We first consider the monopoly problem where both the servers belong to a single operator. The heterogeneity of the customer makes the analysis of the problem difficult. The difficulty lies in the inability to characterize the equilibrium queue arrival rates as a function of the admission prices. We provide an equivalent formulation with the queue arrival rates as the optimization variable simplifying the analysis for revenue rate maximization for the monopoly. We then consider the duopoly problem where each server competes with the other server to maximize its revenue rate. For the duopoly problem, the interest is to obtain the set of admission prices satisfying the Nash equilibrium conditions. While the problem is in general difficult to analyze, we consider the special case when the two servers are identical. For such a duopoly system, we obtain the necessary condition for existence of symmetric Nash equilibrium of the admission prices. The knowledge of the distribution $F$ characterizing the heterogeneity of the customers is necessary to solve the monopoly and the duopoly problem. However, for most practical scenarios, the functional form of $F$ may not be known to the system operator and in such cases, the revenue maximizing prices cannot be determined. In the last part of the paper, we provide a simple method to estimate the distribution $F$ by suitably varying the admission prices. We illustrate the method with some numerical examples.

preprint2016arXivOpen access

Signal facts

What is known right now

Open access2 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.