Management Science
Randomized unbiased nonparametric estimates of nonestimable functionals
Proceedings of second world congress on Nonlinear analysts
Bundling Information Goods: Pricing, Profits, and Efficiency
Management Science
The Economics of Electronic Commerce
The Economics of Electronic Commerce
Bundling and Competition on the Internet
Marketing Science
Measuring Heterogeneous Reservation Prices for Product Bundles
Marketing Science
The Role of the Management Sciences in Research on Personalization
Management Science
The Optimal Number of Versions: Why Does Goldilocks Pricing Work for Information Goods?
Journal of Management Information Systems
For a Few Cents More: Why Supersize Unhealthy Food?
Marketing Science
Information Systems and e-Business Management
The Disruptive Effect of Open Platforms on Markets for Wireless Services
Journal of Management Information Systems
Pricing Digital Goods: Discontinuous Costs and Shared Infrastructure
Information Systems Research
Sell by bundle or unit?: Pure bundling versus mixed bundling of information goods
Decision Support Systems
The Disruptive Effect of Open Platforms on Markets for Wireless Services
Journal of Management Information Systems
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With declining costs of distributing digital products comes renewed interest in strategies for pricing goods with low marginal costs. In this paper, we evaluate customized bundling, a pricing strategy that gives consumers the right to choose up to a quantity M of goods drawn from a larger pool of N different goods for a fixed price. We show that the complex mixed-bundle problem can be reduced to the customized-bundle problem under some commonly used assumptions. We also show that, for a monopoly seller of low marginal cost goods, this strategy outperforms individual selling (M = 1) and pure bundling (M = N) when goods have a positive marginal cost or when customers have heterogeneous preferences over goods. Comparative statics results also show that the optimal bundle size for customized bundling decreases in both heterogeneity of consumer preferences over different goods and marginal costs of production. We further explore how the customized-bundle solution is affected by factors such as the nature of distribution functions in which valuations are drawn, the correlations of values across goods, and the complementarity or substitutability among products. Altogether, our results suggest that customized bundling has a number of advantages-both in theory and practice-over other bundling strategies in many relevant settings.