Handbook on Complexity and Public Policy
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Handbook on Complexity and Public Policy

Edited by Robert Geyer and Paul Cairney

Though its roots in the natural sciences go back to the early 20th century, complexity theory as a scientific framework has developed most rapidly since the 1970s. Increasingly, complexity theory has been integrated into the social sciences, and this groundbreaking Handbook on Complexity and Public Policy has brought together top thinkers in complexity and policy from around the world. With contributions from Europe, North America, Brazil and China this comprehensive Handbook splits the topic into three cohesive parts: Theory and Tools, Methods and Modeling, and Application.
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Chapter 19: The emergence of intermediary organizations: a network-based approach to the design of innovation policies

Annalisa Caloffi, Federica Rossi and Margherita Russo


The importance of networking among heterogeneous organizations as a source of innovation is increasingly acknowledged within the scientific community. Some contributions (Nooteboom, 2000; Powell and Grodal, 2005) stress that the creative recombination of heterogeneous knowledge is an important source of innovation; others (Lane and Maxfield, 1997; Russo, 2000; Lane, 2009) focus on generative relationships characterized by heterogeneous competences, mutual and aligned directedness in contexts of joint action, as drivers of innovation processes; while yet others (Spence, 1984; Katz, 1986) suggest that networks foster innovation through the production and internalization of spillovers within the group of participants. In line with this growing consensus, policymakers increasingly implement interventions in support of networks among either small and large firms, or firms and universities, explicitly aimed at promoting innovation through joint R & D, knowledge transfer or technology diffusion. Nonetheless, our understanding of what network configurations most contribute to innovation, or indeed whether networks lead to innovation, and precisely how they do so, is still limited (Cunningham and Ramlogan, 2012). Greater understanding of what factors support the formation of innovation networks and their successful performance would help policymakers improve the design of policy interventions.

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