We 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

This paper investigates how the tying of complementary products can be used to both preserve and create monopoly positions, where our focus is on the use of tying to deter the entry of efficient producers. We first show how a firm that is a monopolist of a product in the current period can use tying to preserve its monopoly position in the future. We then show using related arguments how a monopolist in one market can employ tying to extend its monopoly position into a newly emerging market. The analysis focuses on the importance of entry costs and network externalities. The paper includes a Tying is a common practice in many markets, i.e., the seller of product A refuses to sell A to a consumer unless the consumer also purchases B (in this scenario product A is referred to as the tying product and B as the tied product). Examples are numerous such as IBM’s famous practice of requiring purchasers of IBM’s tabulating machines to also purchase tabulating cards from IBM, and Microsoft’s

Information goods have negligible marginal costs, and this will create possibilities for novel distribution and pricing methods. The main concern of this paper is with pricing of goods that are likely to be consumed in large quantities by individuals. For example, will software continue to be sold at a fixed price for each unit, or will it be paid for on the basis of usage? There is substantial evidence both from observing marketplace evolution and from surveys that customers overwhelmingly prefer subscription pricing. It turns out that even if we ignore this factor, peruse pricing is not a clear winner, and therefore when the preference effect is taken into account, subscription pricing is likely to dominate. We model competitive pricing between two companies that supply essentially equivalent services (such as movies or word processing software). One company charges a fixed fee per unit, while the other charges on a per-use basis. Each is interested in maximizing its revenue. We cons...

A seller with two objects faces a group of bidders who are subject to budget constraints. The objects have common values to all bidders, but need not be identical and may be either complements or substitutes. In a simple complete information setting we show: (1) if the objects are sold by means of a sequence of open ascending auctions, then it is always optimal to sell the more valuable object first; (2) the sequential auction yields more revenue than the simultaneous ascending auction used recently by the FCC if the discrepancy in the values is large, or if there are significant complementarities; (3) a hybrid simultaneous-sequential form is revenue superior to the sequential auction; and (4) budget constraints arise endogenously. 1

We analyze pricing strategies for digital information goods that are based on aggregation or disaggregation. Bundling, site licensing, and subscription pricing can be analyzed as strategies that aggregate consumer utility across different goods, different consumers, or different time periods, respectively. Using micropayments for rental of software “applets ” or other discrete units of information, can be thought of as disaggregation. We show that reductions in marginal costs made possible by low-cost digital processing and storage of information will favor aggregation, while reductions in transaction and distribution costs made possible by ubiquitous networking tend to make disaggregation of information goods more profitable. Furthermore, offering the goods simultaneously in the aggregated package and as separate components may dominate both strategies of pure aggregation and pure disaggregation. Our model demonstrates how the increasing availability of information goods over the Internet will lead to increased use of both disaggregation-based pricing strategies taking advantage of micropayment technologies, and aggregation strategies where information goods will be offered in bundles, site licenses, and subscriptions. Copyright © 1997 by Yannis Bakos and Erik Brynjolfsson

In broad terms, one can say that price discrimination exists when two “similar ” products which have the same marginal cost to produce are sold by a firm at different prices. 1 This practice is often highly controversial in terms of its impact on both consumers and rivals.

this paper.

A key trend in the world—especially in electronic commerce—is a demand for higher levels of expressiveness in the mechanisms that mediate interactions, such as the allocation of resources, matching of peers, and elicitation of opinions from large and diverse communities. Intuitively, one would think that this increase in expressiveness would lead to more efficient mechanisms (e.g., due to better matching of supply and demand). However, until now we have lacked a general way of characterizing the expressiveness of these mechanisms, analyzing how it impacts the actions taken by rational agents—and ultimately the outcome of the mechanism. In this technical report we introduce a general model of expressiveness for mechanisms. Our model is based on a new measure which we refer to as the maximum impact dimension. The measure captures the number of different ways that an agent can impact the outcome of a mechanism. We proceed to uncover a fundamental connection between this measure and the concept of shattering from computational learning theory. We also provide a way to determine an upper bound on the expected efficiency of any mechanism under its most efficient Nash equilibrium which, remarkably, depends only on the mechanism’s expressiveness. We show that for any setting and any prior over agent preferences, the

Consider an arbitrary Bayesian decision problem in which the preferences of each agent are private information. We prove that the utility costs associated with incentive constraints typically decrease when the decision problem is linked with independent copies of itself. This is established by first defining a mechanism in which agents must budget their representations of preferences so that the frequency of preferences across problems mirrors the underlying distribution of preferences, and then arguing that agents will satisfy their budget by being as truthful as possible. Examples illustrate the disappearance of incentive costs when problems are linked in a rich variety of problems, including public goods allocation, voting, and bargaining.

Information goods, such as journal articles, require substantial initial...