Based initially on studies of the telecommunications industry, spillovers and network effects were more broadly defined by Katz and Shapiro (1986). They extend the concept (consumer benefits of product use as an increasing function of other consumers’ use of compatible products) to industries without physical network characteristics. These include information technology and certain consumer goods, such as video cassettes and durable goods requiring specialized services.
Pepall (1992) developed a model of strategic product choice when consumer preferences combine both vertical and horizontal product differentiation. In such cases, the first mover advantage for producers is maximized when product differentiation is limited by preferences rather than technology (termed ‘niche markets’). As more consumers participate in the relevant market, follower firms offering a range of competing products increase consumer choices and lead to improved market benefits.
Godoe (2000) advanced a linkage between industries’ R&D intensity and their ability to create both incremental innovations and radical innovations. In this model institutional capacity for coordination, direction and leadership can anticipate and internalize the producer incentives offered by spillovers.
Spillover Effects and Network Models (II)
Analytic frameworks based on spillover effects and network characteristics focus on the returns to R&D and how specific firms react to these incentives. The emphasis is on groups of competing technologies within a particular market.
Network effects are important for consumers because their expectations about future product compatibility will influence their decisions about adopting current technologies.
Many models using this approach are concerned with strategic behavior and employ techniques from game theory, such as Cournot equilibrium, in order to specify market structure and strategic choices. Externalities arise when potential first mover firms lack the incentive to conduct R&D due to risks from follower firms. Public R&D investment can alter the incentives to private R&D investment.
R&D benefits estimated using this approach will focus on the effect of specific innovations on the full range of compatible products, including the chances for spillovers that improve the diffusion of compatible technologies. Such measures will be program-specific but are only useful when network characteristics apply.