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Measuring Network Structure
Authors:H Brinton Milward  & Keith G Provan
Institution:School of Public Administration and Policy at the University of Arizona, Tucson, USA.
Abstract:Networks have been a research issue in public administration for many years. Because of the difficulty of measuring networks, they have often been treated as a metaphor, a conceptual scheme, or a management technique (networking). The work on networks in public administration is almost all of the case study and rarely of the comparative case variety. This article presents the results of two studies of networks using social network analysis as a technique for studying structural relationships between organizations. This technique is utilized to show both the research and practical potential of network analysis as an evaluation methodology for organizations that jointly produce a service. In the first study, the network provides mental health services to seriously mentally ill adults. In the second study, the network attempts to prevent young people from abusing drugs and alcohol. The two studies were undertaken for different reasons. The first was an elaborate comparative study of four mental health networks and the relationship between network design and performance. The second was a much simpler consulting effort to help a local prevention partnership create linkages to other community organizations. However, in both of the studies the goal was to measure the structural ties in the network based on various types of relationships that exist in a given field of practice. These linkages are ties that bind the network together and become data that can be used to compare networks on their degree and type of integration. The article makes the argument that links in a network are one way that scholars can compare networks in similar or different policy domains. At the same time, the article argues that analysing linkages in an organization's network is an effective and practical means of determining how well integrated any given organization is in a network.
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