Policy network analysis

Policy network analysis is a field of research in political science focusing on the links and interdependence between government's sections and other societal actors, aiming to understand the policy-making process and public policy outcomes. Although the number of definitions is almost as large as the number of approaches of analysis, Rhodes aims to offer a minimally exclusive starting point: "Policy networks are sets of formal institutional and informal linkages between governmental and other actors structured around shared if endlessly negotiated beliefs and interests in public policy making and implementation." As Thatcher notes, policy network approaches initially aimed to model specific forms of state-interest group relations, without giving exhaustive typologies. The most widely used paradigm of the 1970s and 1980s only analyzed two specific types of policy networks: policy communities and issue networks. Justifications of the usage of these concepts were deduced from empirical case studies. Policy Communities in which you refer to relatively slowly changing networks defining the context of policy-making in specific policy segments. The network links are generally perceived as the relational ties between bureaucrats, politicians and interest groups. The main characteristic of policy communities – compared to issue networks – is that the boundaries of the networks are more stable and more clearly defined. This concept was studied in the context of policy-making in the United Kingdom. In contrast, issue networks – a concept established in literature about United States government - refer to a looser system, where a relatively large number of stakeholders are involved. Non-government actors in these networks usually include not only interest group representatives but also professional or academic experts. An important characteristic of issue network is that membership is constantly changing, interdependence is often asymmetric and – compared to policy communities – it is harder to identify dominant actors.