Network Effects, Nonlinear Pricing and Entry Deterrence
Last revised: July 2003
A number of products that display positive network effects are used in variable quantities by heterogeneous customers. Examples include corporate operating systems, infrastructure software, web services and networking equipment. In many of these contexts, the magnitude of network effects are influenced by gross consumption, rather than simply by user base. Moreover, the value an individual customer derives on account of these network effects may be related to the extent of their individual consumption, and therefore, the network effects may be heterogeneous across customers.
This paper presents a model of nonlinear pricing in the presence of such network effects, under incomplete information, and with the threat of competitive entry. Both homogeneous and heterogeneous network effects are modeled. Conditions under which a fulfilled-expectations contract exists and is unique are established. While network effects generally raise prices, it is shown that accompanying changes in consumption depend on the nature of the network effects -- in some cases, it is optimal for the monopolist to induce no changes in usage across customers, while in others cases, network effects raise the usage of all market participants. Optimal pricing is shown to include quantity discounts that increase with usage, and may also involve a nonlinear two-part tariff. These results highlight the impact of network effects on the standard trade-off between price discrimination and value creation, and have important implications for pricing policy
The threat of entry generally lowers profits for the monopolist, and increases customer surplus. When network effects are homogeneous across customers, the resulting entry-deterring monopoly contract is a fixed fee and results in the socially optimal outcome. However, when the magnitude of heterogeneous network effects is relatively high, there are no changes in total surplus induced by the entry threat, and the price changes merely cause a transfer of value from the seller to its customers. The presence of network effects, and of a credible entry threat, are also shown to increase distributional efficiency by reducing the disparity in relative value captured by different customer types. Regulatory and policy implications of these results are discussed.
JEL Codes: D42, L11, L12
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