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The rapid growth of knowledge in disease diagnosis and treatment requires health service provider organizations to continuously learn and update their practices. However, little is known about knowledge sharing in service implementation networks governed by a network administrative organization (NAO). The author suggests that strong ties enhance knowledge sharing and that there is a contingent effect of third‐party ties. Two provider agencies' common ties with the NAO may undermine knowledge sharing because of resource competition. In contrast, a dyad's common ties with a peer agency may boost knowledge sharing as a result of social cohesion. Finally, the author posits that third‐party ties moderate the relationship between strong ties and knowledge sharing. These hypotheses are examined in a mental health network. Quantitative network analysis confirms the strong tie and third‐party tie hypotheses and provides partial support for the moderating effect of third‐party ties. The implications for public management, including the implementation of HealthCare.gov, are discussed.

AbstractWhile information exchange is essential in the policy process, little is known about how divergent subgroups filter actors' technical and political information exchange, blocking learning processes. Guided by social identity, group entitativity, and self-categorisation theories, we introduce the concept and measurement of identity-based subgroups referring to informal clusters shaped by the self-referent perception of similarities among actors. The identity-based subgroup is recognised as a precursor for coalition building in a policy subsystem but received inadequate attention in the research on Advocacy Coalition Framework. We examine how divergent identity-based subgroups moderate the links between relational embeddedness and technical/political information exchanges in an adversarial fracking policy network in New York. Our quadratic assignment procedure multiple regression indicated that, despite trust, policy actors from different identity-based subgroups are less likely to share technical and political information in the network. When two actors' identity-based subgroups are different, competition is more likely associated with lower technical information exchange in the network. These findings extend research on information exchange in adversarial policy subsystems.

Given the background of financial disintermediation and interest rate marketization, the assets of China's commercial banks can be divided into traditional credit assets, whose rates of return are controlled by the supervision department, and financial assets, whose rates of return fluctuate according to market conditions. Direct financing enterprises are mainly state-owned enterprises with a good reputation, endorsed by the government, and they finance using the financial assets of commercial banks. Indirect financing enterprises are mainly private enterprises, which finance using credit assets. By introducing a financial intermediary sector with a balance sheet into dynamic stochastic general equilibrium (DSGE) model, our model endogenously determines the leverage ratio and the ratio of the two assets of the bank. Model results show that the impact from the volatility of financial markets and other exogenous shocks can affect the banks' asset proportions of the two asset types, asymmetrically affecting the production scale of enterprises with two types of financing. Further, the bank's leverage ratio changes will have a magnifying effect on economic fluctuations.

This 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 five resource‐based subnetworks. The 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.

This article examines a publicly funded mental health services network, focusing on the patterns of interaction in five resource-based subnetworks. We argue that the structure of network relationships can be explained by the nature of the resources that are at the source of the interaction. Depending on whether a particular resource is tangible or tacit, subnetwork structures will differ in predictable ways. We found that the pattern of interactions among network organizations in resource-based subnetworks appears to be dependent on the organizations controlling these resources (the Network Administrative Organization versus network members) as well as the nature of the resource (tangible versus knowledge based). Our research extends theory on network interactions as well as having implications for network practice. Adapted from the source document.

What predicts the formation and evolution of partnerships in unstable institutional contexts? We answer this question by examining the partnership field of environmental nonprofit organizations based in Lebanon. Employing descriptive and inferential network methods, we find organizational attributes such as scope, operations, and age to be significant predictors of partnership formation. In particular, organizations working in the same issue areas are more likely to partner with each other; age and scope complementarity also drives the partnership formation over time. Furthermore, the results reveal that organizations are more likely to form partnerships with their partners' partners, and consequently stable clusters or subgroups emerge over time. These findings are suggestive but are the first to provide a multilevel analysis of nonprofit partnership formation and evolution.