Abstract
This paper models the processes of innovation and di usion on a network. Di usion is modelled as a process of broadcast | every agent has a xed (small) set of \neighbours to who he transmits his knowledge after he makes an innovation. In this regard, the model resembles \collective invention as de ned and documented by Allen (1983). The model places agents on a network, and broadcasts take place over (bi-directional) edges of length one. The communication network structure has a strong in uence on system performance in terms of knowledge production and growth. We examine the interaction between network structure and the nature of knowledge in determination of knowledge growth and distribution. In general a xed, static network structure dominates di usion through random mixing, and when absorptive capacities are low, the small world architecture dominates all others. JEL Classi cation: L00, O31, O38, R10.
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