Source:
Management Science, Volume 54, Issue 3, p.14 (2008)
Keywords:
information goods;
electronic commerce;
customized bundle;
pricing;
nonlinear programming
Abstract:
This paper proposes using nonlinear mixed-integer programming to solve the customized bundle-pricing
problem in which consumers are allowed to choose up to N goods out of a larger pool of J goods. Prior work
has suggested that this mechanism has attractive features for the pricing of information and other low-marginal
cost goods. Although closed-form solutions exist for this problem for certain cases of consumer preferences,
many interesting scenarios cannot be easily handled without a numerical solution procedure. In this paper,
we investigate the efficiency gains created by customized bundling over the alternatives of pure bundling or
individual sale under different assumptions about customer preferences and firm cost structure, as well as the
potential loss of efficiency caused by pricing with incomplete information about consumer reservation values.
Our analysis suggests that customized bundling enhances sellers’ profits and enhances welfare when consumers
do not place positive values on all goods, and that this consumer characteristic is much more important than
the shape of the valuation distribution in determining the optimal pricing scheme. We also find that customized
bundling outperforms both pure bundling and individual sale in the presence of incomplete information, and
that customized bundling still outperforms other simpler pricing schemes even when exact consumer valuations
are not known ex ante.
Notes:
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