Seite - (000318) - in Knowledge and Networks

316 cratic laboratories (Shipan & Volden, 2012; Volden, 2006) and that they can learn important lessons from each other. Literature on urban policy mobilities (Jacobs, 2012; McCann, 2011) and policy diffusion (Krause, 2011; Lee & van de Meene, 2012) has begun to explore the mechanisms of policy transfer and diffusion between cities. Our research shares this interest in policy mobility and diffusion but approaches the issue from a different angle. Rather than asking why a policy moves from city A to city B, our research is interested in uncovering the relational princi- ples that constitute interurban networks in the first place. We approach the issue from this angle, in part, because of the character of our data, which does not enable us to track the mobility or diffusion of specific policies, but does give us an unusu- ally detailed look at the relationships of learning between Swedish municipalities. Our contribution is therefore not to explain mobility or diffusion per se, but rather to utilize social network analysis to uncover the structuring principles of national learning networks. Over the last decade or so, economic geographers and economic sociologists have been engaged in a similar exploration of the relational principles that guide learning in interfirm networks. Their research has shown that interfirm learning is often structured by geographical proximity, but that nonlocal networks may be criti- cal pipelines that move knowledge between local clusters of firms (e.g., Amin & Cohendet, 1999; Bathelt, Malmberg, & Maskell, 2004; Bell & Zaheer, 2007; Glückler, 2013; Owen- Smith & Powell, 2004). Although geographical proximity is understood to enhance interactional learning, nonlocal networks are increasingly understood to be important for preventing local learning networks from becoming too parochial (Boschma, 2005; Maskell, 2014). Although research is beginning to reveal variations on this theme, this literature valuably highlights the composite character of learning ecologies, which are produced through the interplay of geog- raphy and networks. Our research builds on this literature, but extends this discus- sion from firms to municipalities. Our research therefore offers a bridge between this literature on interfirm learning and the literature on policy mobility and diffu- sion. To our knowledge, there has been little cross-fertilization between these two important bodies of literature. Our exploration of intermunicipal learning networks is based on a unique survey of municipal civil servants conducted in 2010 as part of a wider study of municipal knowledge use in Sweden. In this survey, the senior civil servants in all Swedish municipalities were asked to name other Swedish municipalities from whom they had drawn lessons in a given period. When these choices are aggregated across all Swedish municipalities, the result is a unique glimpse into what an intermunicipal learning network looks like on a national scale. Swedish municipalities provide an interesting context in which to examine learning networks. Much of the fabled Swedish welfare state is actually administered by Sweden’s 290 municipalities varying in size from roughly 3000 inhabitants to 750,000 inhabitants.1 These munic- ipalities have responsibility for a wide range of policy areas, including social ser- 1 Prior research notes significant variation in welfare services across municipalities, leading some scholars to describe Sweden as a multitude of “welfare municipalities” (Trydegård & Thorslund, 2010). C. Ansell et al.