Information good

Abstract: 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 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.

Abstract: We analyze pricing strategies for digital information goods, such as those increasingly available via the Internet. Because perfect copies of such goods can be created and distributed almost costlessly, any single positive price for copies is likely to be socially inefficient. However, we show that, under certain conditions, a monopolist selling information goods in large bundles instead of individually may nearly eliminate this inefficiency. In addition, the bundling strategy can extract as profits an arbitrarily large fraction of the area under the demand curve for the individual goods while commensurately reducing consumers' surplus. The bundling strategy is particularly attractive when the marginal costs of the goods are very low, when the correlation in the demand for different goods is low, and when consumer valuations for the individual goods are of comparable magnitude. We also describe the optimal pricing strategies when these conditions do not hold; show how private incentives for bundling can diverge from social incentives; and describe a mechanism to recover information about the underlying demand for each individual good. The predictions of our analysis appear to be consistent with empirical observations of the markets for Internet and on- line content, cable television programming, and copyrighted music.

Abstract: The Internet has signi.cantly reduced the marginal cost of producing and distributing digital information goods. It also coincides with the emergence of new competitive strategies such as large-scale bundling. In this paper, we show that bundling can create "economies of aggregation" for information goods if their marginal costs are very low, even in the absence of network externalities or economies of scale or scope.We extend the Bakos-Brynjolfsson bundling model (1999) to settings with several different types of competition, including both upstream and downstream, as well as competition between a bundler and single good and competition between two bundlers. Our key results are based on the "predictive value of bundling," the fact that it is easier for a seller to predict how a consumer will value a collection of goods than it is to value any good individually. Using a model with fully rational and informed consumers, we use the Law of Large Numbers to show that this will be true as long as the goods are not perfectly correlated and do not affect each other's valuations significantly. As a result, a seller typically can extract more value from each information good when it is part of a bundle than when it is sold separately. Moreover, at the optimal price, more consumers will find the bundle worth buying than would have bought the same goods sold separately. Because of the predictive value of bundling, large aggregators will often be more pro.table than small aggregators, including sellers of single goods.We find that these economies of aggregation have several important competitive implications:1. When competing for upstream content, larger bundlers are able to outbid smaller ones, all else being equal. This is because the predictive value of bundling enables bundlers to extract more value from any given good.2. When competing for downstream consumers, the act of bundling information goods makes an incumbent seem "tougher" to single-product competitors selling similar goods. The resulting equilibrium is less profitable for potential entrants and can discourage entry in the bundler's markets, even when the entrants have a superior cost structure or quality.3. Conversely, by simply adding an information good to an existing bundle, a bundler may be able to profitably enter a new market and dislodge an incumbent who does not bundle, capturing most of the market share from the incumbent firm and even driving the incumbent out of business.4. Because a bundler can potentially capture a large share of profits in new markets, single-product firms may have lower incentives to innovate and create such markets. At the same time, bundlers may have higher incentives to innovate.For most physical goods, which have nontrivial marginal costs, the potential impact of large-scale aggregation is limited. However, we find that these effects can be decisive for the success or failure of information goods. Our results have particular empirical relevance to the markets for software and Internet content and suggest that aggregation strategies may take on particular relevance in these markets.