Network Externalities, Mutuality, and Compatibility

Positive network externalities can arise when consumers benefit from the consumption of compatible products by other consumers (user-positive consumption externalities) or, alternatively, when they incur costs from the consumption of incompatible products by other consumers (nonuser-negative consumption externalities). But whereas user-positive externalities are typically mutually imposed and imply mutual benefit because they relate to interoperability, with nonuser-negative externalities the costs of incompatibility may be imposed unilaterally and borne asymmetrically. For example, increased risks of death and injury on the roads due to the co-existence of large and small vehicles are imposed exclusively by the owners of the large vehicles and borne exclusively by the occupants of the small vehicles. This paper compares the social optimality of incentives for compatibility under regimes involving user-positive and nonuser-negative externalities. Earlier work with respect to user-positive externalities (e.g., Katz and Shapiro, 1985) suggests that firms with relatively small networks or weak reputations tend to be biased in favor of compatibility, while individual firms’ incentives for compatibility are suboptimal when their networks are closely matched in size. Meanwhile, intuition suggests that with nonuser-negative externalities incentives for incompatibility should always be excessive, reflecting the notion that activities involving unilaterally imposed negative externalities will always be overprovided by the market (in the absence of regulation or Coaseian mitigation). Using a "location" model of differentiated products, we find that, under both regimes, incentives for compatibility tend to be suboptimal when firms' networks are close in size, and excessive for the small firm when the networks differ greatly in size. Surprising public policy implications with respect to externalities are discussed

Adverse Network Effects, Moral Hazard, and the Case of Sport-Utility Vehicles

The paper examines a class of phenomena that combine adverse network effects with moral hazard, using the motor vehicle market as an example to develop and illustrate the key concepts. It is hypothesized that consumers behave as if there is a network externality with respect to vehicle size: the more large vehicles there are on the roads, the greater a consumer’s propensity to seek protection from them by driving a large vehicle herself. One consequence of this is that motor vehicle manufacturers are discouraged from making large vehicles less hazardous to other motorists. The paper measures the network effect and consequent moral hazard using disaggregate data on choice of vehicle type and related household characteristics, combined with a state-level measure of the incidence of traffic fatalities. The results show that for each 1 million light trucks that replace cars, between 961 and 1,812 would-be car buyers decide to buy a light truck instead, in reaction to the increased risk of death posed by the incremental light trucks. This network effect, when run in reverse, creates egregious incentives for vehicle manufacturers: for every life saved due to safety innovations that make light trucks less deadly to other motorists, manufacturers can expect to sell about 31 fewer light trucks

Adverse Network Effects, Moral Hazard, and the Case of Sport-Utility Vehicles

The paper examines a class of phenomena that combine adverse network effects with moral hazard, using the motor vehicle market as an example to develop and illustrate the key concepts. It is hypothesized that consumers behave as if there is a network externality with respect to vehicle size: the more large vehicles there are on the roads, the greater a consumer’s propensity to seek protection from them by driving a large vehicle herself. One consequence of this is that motor vehicle manufacturers are discouraged from making large vehicles less hazardous to other motorists. The paper measures the network effect and consequent moral hazard using disaggregate data on choice of vehicle type and related household characteristics, combined with a state-level measure of the incidence of traffic fatalities. The results show that for each 1 million light trucks that replace cars, between 961 and 1,812 would-be car buyers decide to buy a light truck instead, in reaction to the increased risk of death posed by the incremental light trucks. This network effect, when run in reverse, creates egregious incentives for vehicle manufacturers: for every life saved due to safety innovations that make light trucks less deadly to other motorists, manufacturers can expect to sell about 31 fewer light trucks