방법 비교

	Advocacy Coalition Framework	Policy Network Analysis
분야	Public Policy	Public Policy
계열	Process / pipeline	Process / pipeline
기원 연도	1993	1992
창시자	Paul Sabatier & Hank Jenkins-Smith	R. A. W. Rhodes & David Marsh (British school); broader governance-network tradition
유형	Theory of the policy process	Analysis of inter-organisational policy relationships
원전	Sabatier, P. A., & Jenkins-Smith, H. C. (Eds.) (1993). Policy Change and Learning: An Advocacy Coalition Approach. Boulder, CO: Westview Press. ISBN: 9780813316499	Marsh, D., & Rhodes, R. A. W. (Eds.) (1992). Policy Networks in British Government. Oxford: Clarendon Press. ISBN: 9780198278528
별칭	ACF, Sabatier-Jenkins-Smith Framework, Advocacy Coalition Approach	Policy Networks, Governance Network Analysis, Policy Network Approach
관련	4	4
요약	The Advocacy Coalition Framework (ACF) is a theory of the policy process developed by Paul Sabatier and Hank Jenkins-Smith from the late 1980s and consolidated in their 1993 volume Policy Change and Learning. It explains policy stability and change over long periods by analysing competing coalitions of actors within a policy subsystem who are bound together by shared beliefs. Policy change is understood as a function of the interaction among these belief-based coalitions, the policy-oriented learning that occurs over time, and external events and shocks that can shift the balance of power among them.	Policy network analysis examines policymaking as the product of relationships among interdependent actors — government agencies, interest groups, experts and others — who exchange resources such as information, money, legitimacy and authority. In the influential British tradition associated with R. A. W. Rhodes and David Marsh, policy networks range along a continuum from tightly knit, exclusive 'policy communities' to loose, open 'issue networks', and the type of network is held to shape policy outcomes. More broadly, the approach applies the concepts and tools of social-network analysis to governance, treating the structure of ties among actors as a key explanatory variable.