Commodity Bundling and the Burden of Monopoly

Adams, William James; Yellen, Janet L.

doi:10.2307/1886045

Cited by 1,201 publications

(739 citation statements)

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“…We focus on this last benefit of bundling, which was first discussed by Stigler (1963) in a paper showing how bundling could increase sellers' profits when consumer valuations for two goods were negatively correlated. Adams and Yellen (1976) introduced a two-dimensional graphical framework for analyzing bundling as a device for price discrimination. By introducing a setting with a multiproduct monopolist, two goods, no reselling, independent and additive consumer valuations, and linear "unit demands" (i.e., consumers buy either zero or one unit) for these two goods, they compare unbundled sales to pure bundling (offering only the complete bundle) and mixed bundling (offering both the complete bundle and subsets of the bundle).…”

Section: The Bundling Literaturementioning

confidence: 99%

Bundling Information Goods: Pricing, Profits, and Efficiency

1999

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W e study the strategy of bundling a large number of information goods, such as those increasingly available on the Internet, and selling them for a fixed price. We analyze the optimal bundling strategies for a multiproduct monopolist, and we find that bundling very large numbers of unrelated information goods can be surprisingly profitable. The reason is that the law of large numbers makes it much easier to predict consumers' valuations for a bundle of goods than their valuations for the individual goods when sold separately. As a result, this "predictive value of bundling" makes it possible to achieve greater sales, greater economic efficiency, and greater profits per good from a bundle of information goods than can be attained when the same goods are sold separately. Our main results do not extend to most physical goods, as the marginal costs of production for goods not used by the buyer typically negate any benefits from the predictive value of large-scale bundling.While determining optimal bundling strategies for more than two goods is a notoriously difficult problem, we use statistical techniques to provide strong asymptotic results and bounds on profits for bundles of any arbitrary size. We show how our model can be used to analyze the bundling of complements and substitutes, bundling in the presence of budget constraints, and bundling of goods with various types of correlations and how each of these conditions can lead to limits on optimal bundle size. In particular we find that when different market segments of consumers differ systematically in their valuations for goods, simple bundling will no longer be optimal. However, by offering a menu of different bundles aimed at each market segment, bundling makes traditional price discrimination strategies more powerful by reducing the role of unpredictable idiosyncratic components of valuations. The predictions of our analysis appear to be consistent with empirical observations of the markets for Internet and online content, cable television programming, and copyrighted music.

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Section: The Bundling Literaturementioning

confidence: 99%

Bundling Information Goods: Pricing, Profits, and Efficiency

1999

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“…It corresponds to the standard linear and additively separable utility function that is usually considered in the literature on bundling by a multi-product monopolist. In example 1 Our results depend only U A,k being strictly decreasing in x, not on its linearity.…”

Section: The Modelmentioning

confidence: 54%

“…A standard result of the monopoly pricing literature is that bundling multiple goods together can increase a monopolist's profits because buyer valuations of a bundle are more predictable than buyer valuations of individual goods (Stigler, 1963;Adams and Yellen, 1976;McAfee, McMillan, and Whinston, 1989). This same logic clearly applies to our model of multi-issue bargaining.…”

Section: Introductionmentioning

confidence: 73%

Cheap talk comparisons in multi-issue bargaining

Chakraborty

Harbaugh

2003

Economics Letters

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“…This is inessential for the argument. More formal analyses of this kind of problems are provided in Adams and Yellen (1976), McAfee, McMillan and Whinston (1989) and Armstrong (1996) for example.…”

Section: Motivations For Submitting a Package Bidmentioning

confidence: 99%