Th is article is a longitudinal examination of a publicly funded network of health and human services organizations that provide services to mentally ill adults. Data were collected at two points in time from a single network in a large U.S. metropolitan area: when the network was completely reorganized, and again when it had matured, four years later. Analysis focuses on changes in the patterns of interaction within and across fi ve resource-based subnetworks. Th e authors argue that the structure of network relationships depends on the type of resources involved-whether tangible or intangible, the stage of network evolution, and whether macro-or micro-level interactions are considered. Implications for theory and for network management, governance, and policy are discussed.

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This article reviews and discusses the empirical literature on interorganizational networks at the network level of analysis, or what is sometimes referred to as “whole” networks. An overview of the distinction between egocentric and network-level research is first introduced. Then, a review of the modest literature on whole networks is undertaken, along with a summary table outlining the main findings based on a thorough literature search. Finally, the authors offer a discussion concerning what future directions might be taken by researchers hoping to expand this important, but understudied, topic.

Although cooperative, interorganizational networks have become a common mechanism for delivery of public services, evaluating their effectiveness is extremely complex and has generally been neglected. To help resolve this problem, we discuss the evaluation of networks of community-based, mostly publicly funded health, human service, and public welfare organizations. Consistent with pressures to perform effectively from a broad range of key stakeholders, we argue that networks must be evaluated at three levels of analysis: community, network, and organization/participant levels. While the three levels are related, each has its own set of effectiveness criteria that must be considered. The article offers a general discussion of network effectiveness, followed by arguments explaining effectiveness criteria and stakeholders at each level of analysis. Finally, the article examines how effectiveness at one level of network analysis may or may not match effectiveness criteria at another level and the extent to which integration across levels may be possible.

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