The Evolution of R&D Networks

Abstract

We study the evolution of R&D networks in a Cournot model where firms may lower marginal costs due to bilateral R&D collaborations. Stochastically stable R&D networks exhibit the dominant group architecture, and, contrary to the existing literature, generically unique predictions about the size of the dominant group can be obtained. This size decreases monotonically with respect to the cost of link formation and there exists a lower bound on the size of the dominant group for non-empty networks. Stochastically stable networks are always inefficient and an increase in linking costs has a non-monotone effect on average industry profits.

The Effect of Entry on R&D Networks

“…They suggest that the optimal R&D policy should be such that it balances subsidies for entrants and subsidies to incumbents' link costs, as high subsidies to incumbent firms might deter entry, thus lowering welfare. In a similar vein, Westbrock (2010) and Dawid and Hellmann (2014) suggest that subsidization of R&D linking costs may improve welfare. in other markets from tax collection as well as potential operating costs of the subsidization process.…”

“…20 For a dynamic model of network formation with myopic agents, see Jackson and Watts (2002), which has been applied to R&D networks by Dawid and Hellmann (2014). Both articles focus on the notion of stochastic stability.…”

Third Party Beneficiaries and Contractual Networks

“…These effects are considered infra. Dawid & Hellmann (2014) and Hattori & Hsin (2014) analyze cooperate/compete networks.…”

Knowledge Transfer and Partial Equity Ownership

“…Finally, we discuss how our model differs from models that analyze endogenous network formation as a route to enjoy cost spillovers (see Goyal and Moraga-González, 2001;Greenlee, 2005;Dawid and Hellmann, 2016). In their three-stage games, firms form alliances and determine levels of cost-reducing Research and Development (R&D) investments in the first and the second stages, and then firms compete in the product market in the third stage (see also Joshi, 2003, andDawid andHellmann, 2014, for related models). In these models, knowledge automatically spills over within alliances.…”