Confronta i metodi

	Network Governance Analysis	Policy Feedback Analysis
Campo	Public Administration	Public Administration
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	2008	1993
Ideatore	Keith G. Provan & Patrick Kenis	Paul Pierson
Tipo	Interorganizational network analysis framework	Theoretical-analytical framework for policy effects on politics
Fonte seminale	Provan, K. G., & Kenis, P. (2008). Modes of Network Governance: Structure, Management, and Effectiveness. Journal of Public Administration Research and Theory, 18(2), 229–252.	Pierson, P. (1993). When Effect Becomes Cause: Policy Feedback and Political Change. World Politics, 45(4), 595–628.
Alias	Governance Network Analysis, Public Network Governance Assessment, Collaborative Governance Network Analysis, Interorganizational Governance Network Analysis	Policy Feedback Theory Analysis, Feedback Effects Analysis, Policy-as-Cause Analysis, Self-Reinforcing Policy Analysis
Correlati	4	4
Sintesi	Network governance analysis studies how public problems are addressed not by single hierarchical agencies but by networks of interdependent organizations — government bodies, nonprofits, firms and community groups — coordinating to deliver services or make policy. It combines the relational tools of social network analysis with Keith Provan and Patrick Kenis's influential 2008 typology of network governance, which distinguishes shared (participant-governed) networks, lead-organization-governed networks, and network administrative organizations. By mapping the structure of ties, computing network metrics, classifying the governance mode and relating these to outcomes, the method explains how a collaborative network is held together and why it performs as it does.	Policy feedback analysis examines how policies, once enacted, reshape the politics that follow — turning yesterday's policy effects into today's political causes. Drawing on Paul Pierson's foundational 1993 article 'When Effect Becomes Cause,' it holds that policies are not just outputs of politics but powerful forces that create resources and incentives for groups, build administrative capacities, and shape how citizens understand their interests and their government. By tracing these resource and interpretive feedback effects over time, the method explains why some policies become self-reinforcing and politically durable, why others undermine their own support, and why policy change is often path-dependent and hard to reverse.