A number of technology products display positive network effects, and are used invariable quantities by heterogeneous customers. Examples include operating systems, infrastructureand back-end software, web services and networking equipment. This paper studies optimalnonlinear pricing for such products, under incomplete information, and with the threat of competitiveentry. Both homogeneous and heterogeneous network effects are modeled. Conditions underwhich a fulfilled-expectations contract exists and is unique are established. While network effectsgenerally raise price, it is shown that accompanying changes in consumption depend on the natureof the network effects - in some cases, it is optimal for the monopolist to induce no changes in usageacross 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 involvea nonlinear two-part tariff. These results highlight the impact of network effects on trade-offsbetween price discrimination and value creation, and have important managerial implications forpricing policy in technology markets.The need to deter competitive entry generally lowers profits for the monopolist, and increasescustomer surplus. When network effects are homogeneous across customers, the resulting entry-deterringmonopoly 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 intotal surplus induced by the entry threat, and the price changes merely cause a transfer of valuefrom the seller to its customers. The presence of network effects, and of a credible entry threat, arealso shown to increase distributional efficiency by reducing the disparity in relative value capturedby different customer types. Regulatory and policy implications of these results are discussed.

A number of technology products display positive network effects, and are used in variable quantities by heterogeneous customers. Examples include operating systems, infrastructure and back-end software, web services and networking equipment. This paper studies optimal nonlinear pricing for such products, 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 trade-offs between price discrimination and value creation, and have important managerial implications for pricing policy in technology markets. The need to deter competitive 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.

This paper presents a model of second-degree price discrimination by a monopolistic seller who offers a menu of price-quantity pair contracts to consumers located in a social network. Network effects are local as consumers' private valuations are increasing in their friends' adoption decisions. When designing the optimal set of contracts, the seller takes into account how these local network effects are generated over the social network. Increased participation generates externalities through a ''market size effect'' (higher participation due to higher valuations) and a ''distribution effect'' (consumers upgrade to a higher quantity contract). Local network effects can induce the seller to offer contracts to some consumer segments at a loss (e.g., by offering a free-of-charge plan). Due to the combination of network effects and asymmetric information a complete market failure can occur, i.e., no output is produced despite some production is socially desirable.

The last chapter addresses a firm's motivation to join an informal network in the context of a standards war. I examine the importance of compatibility and network effects on technology adoption decisions of suppliers of Internet access as they upgrade to a new high speed modem standard. The results confirm the strong influence of network effects on adoption of new technologies.

Indirect network effects are of prime interest to marketers because they affect the growth and takeoff of software availability for, and hardware sales of, a new product. While prior work on indirect network effects in the economics and marketing literature is valuable, these literatures show two main shortcomings. First, empirical analysis of indirect network effects is rare. Second, in contrast to the importance the prior literature credits to the chicken-and-egg paradox in these markets, the temporal pattern - which leads which? - of indirect network effects remains unstudied. Based on empirical evidence of nine markets, this study shows, among others, that: (1) indirect network effects, as commonly operationalized by prior literature, are weaker than expected from prior literature; (2) in most markets we examined, hardware sales leads software availability, while the reverse almost never happens, contradicting existing beliefs. These findings are supported by multiple methods, such as takeoff and time series analyses, and fit with the histories of the markets we studied. The findings have important implications for academia, public policy and management practice. To academia, it identifies a need for new, and more relevant, conceptualizations of indirect network effects. To public policy, it questions the need for intervention in network markets. To management practice, it downplays the importance of the availability of a large library of software for hardware technology to be successful.