  When multiple innovations compete for adoption, historical chance leading to
early advantage can generate lock-in effects that allow suboptimal innovations
to succeed at the expense of superior alternatives. Research on the diffusion
of innovafacetion has identified many possible sources of early advantage, but
these mechanisms can benefit both optimal and suboptimal innovations. This
paper moves beyond chance-as-explanation to identify structural principles that
systematically impact the likelihood that the optimal strategy will spread. A
formal model of innovation diffusion shows that the network structure of
organizational relationships can systematically impact the likelihood that
widely adopted innovations will be payoff optimal. Building on prior diffusion
research, this paper focuses on the role of central actors i.e. well-connected
people or firms. While contagion models of diffusion highlight the benefits of
central actors for spreading innovations further and faster, the present
analysis reveals a dark side to this influence: the mere presence of central
actors in a network increases rates of adoption but also increases the
likelihood of suboptimal outcomes. This effect, however, does not represent a
speed-optimality tradeoff, as dense networks are both fast and optimal. This
finding is consistent with related research showing that network centralization
undermines collective intelligence.
