Affiliation:
1. Microsoft Research, Cambridge, MA
2. Princeton University, Princeton, NJ
Abstract
We consider a monopolist seller with
n
heterogeneous items, facing a single buyer. The buyer has a value for each item drawn independently according to (non-identical) distributions, and her value for a set of items is additive. The seller aims to maximize his revenue.
We suggest using the
a priori better
of two simple pricing methods:
selling the items separately
, each at its optimal price, and
bundling together
, in which the entire set of items is sold as one bundle at its optimal price. We show that for any distribution, this mechanism achieves a constant-factor approximation to the optimal revenue. Beyond its simplicity, this is the first computationally tractable mechanism to obtain a constant-factor approximation for this multi-parameter problem. We additionally discuss extensions to multiple buyers and to valuations that are correlated across items.
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software
Cited by
17 articles.
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