Martin Lundin

Learning Networks among Swedish Municipalities: Is Sweden a Small World?

Distributed, networked learning processes are widely touted as a basis for superior performance. Yet we know relatively little about how learning networks operate in the aggregate. We explore this issue by utilizing a unique data set on learning among Swedish municipalities. The data indicate that geographic proximity and county are the basic structuring properties of the global network. Municipalities learn from their near neighbors, especially from neighbors in the same county, and these two principles produce a high degree of local clustering in the municipal learning networks. At the same time, we also find evidence that Swedish municipalities are a small world linked together on a national basis. Two mechanisms knit the Swedish municipalities together. First, county seats serve as hubs that link local clusters together. Second, local clusters aggregate into regional clusters. Despite a high degree of local clustering, hubs and regions provide a structural basis for the national diffusion of policy ideas and practices among Swedish municipalities.

How learning aggregates: a social network analysis of learning between Swedish municipalities

ABSTRACT Using a unique data set of learning among all 290 Swedish municipalities, we use social network analysis to analyse how learning networks aggregate nationally. To facilitate this analysis, we describe five ideal-typical patterns of aggregation: core-periphery, small world, top-down regionalism, bottom-up regionalism and urban hierarchy. Each of these ideal-types has important implications for how ideas, information and innovation will circulate among municipalities. Social network analysis allows us to both isolate these patterns and to appreciate composite patterns. The analysis indicates that Swedish municipalities are a small-world network with regional and hierarchical elements. County seats serve an important role as network hubs.