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This chapter discusses the impact of different types of learning on the success and failure of the transfer of the famous Silicon Valley Model (SVM) of innovation. Working with the idea of ‘adaptive learning’, it underlines the importance of understanding the learning process, and critically, the depth of learning that underpins policy transfer. Policy transfer is ‘a process in which knowledge about policies, administrative arrangements, institutions and ideas in one political setting (past or present) is used in the development of policies, administrative arrangements, institutions and ideas in another political setting’. Thus, knowledge exchange is highly dependent on the setting it occurs in as well as on the individuals involved in the process. There are different degrees of transfer: copying, emulation, combinations, and inspiration. These categories move from direct and complete transfer to searching for inspiration to create policy change. The chapter looks at four cases to demonstrate how different learning processes generated by actors at the meso-level, mainly networks of stakeholders and experts, mediate the extent to which policy transfer is a success or failure.
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