Seite - (000327) - in Knowledge and Networks

325 support from the European Union. Lidström (2011) found that citizens in the municipal regions of Göteborg (13 municipalities) and Umeå (6 municipalities) adopted more of a city-regionalist attitude (emphasizing the importance of intermu- nicipal coordination on a regional basis), as opposed to a localist attitude (strong municipal autonomy). The findings of Gren (2002) and Lidström (2011) suggest explanations for the existence of this subregion in the learning network. A Small World? The previous analysis has shown that learning networks in Sweden are to a large extent structured by county. However, we want to know more about whether the municipalities are efficiently integrated on a national scale. The literature on small- world networks suggests that networks might be well connected despite highly localizing tendencies (Watts, 1999; Uzzi, Amaral, & Reed-Tsochas, 2007). Small- world networks are more cosmopolitan than expected because of the connections that occur among local clusters. If Swedish municipalities compose a small world, knowledge, ideas, and best practices might be diffused widely and rapidly despite the localism of learning networks. A small-world network is defined as a graph with high clustering but low path length.7 A random graph typically has low clustering but also short average path lengths. A highly clustered network, by contrast, generally has high path lengths. A small-world network is a network with higher clustering than a random graph but with similar path lengths. A key feature of a small-world network is that despite the high clustering, which is expected to impede communication across the network, links between clusters can greatly shorten the path lengths and hence facilitate more rapid and cosmopolitan communication. In small worlds, path lengths are often reduced through the influence of highly connected hubs that link different clusters together. Well-connected hubs are not a necessary feature of small worlds, but it is reasonable to expect them to be important in networks with high local clustering. A number of scholars have pointed to the potential for small-world networks to diffuse knowledge and enhance innovation. Cowan and Jonard (2004), for example, simu- lated knowledge diffusion in innovation networks and found that diffusion in small- world networks produces higher knowledge levels (in the network as a whole) than either a more local network or a random network. Two measures have been used to identify whether a network exhibits small- world properties: a clustering coefficient (as defined by Watts, 1999; labeled cc for 7 Clustering refers to the density of interconnections in each social network actor’s local neighbor- hood—the set of other actors with whom the focal actor is directly connected. The overall cluster- ing of a network is the mean clustering across all the actors in the network. Path length is the mean number of steps it takes each actor in the network to reach every other actor in the network when taking the shortest path. 15 Learning Networks Among Swedish Municipalities: Is Sweden a Small World?