Synthesizing the Implementation Literature: The Ambiguity-Conflict Model of Policy Implementation
Richard E. Matland
Abstract
Richard E. Matland
Abstract
A review of the policy implementation literature finds the field split into two major schools, top-down and bottom-up. Previous attempts to reconcile these models are described, followed by an alternative model. This model reconciles these approaches by concentrating on the theoretical significance of ambiguity and conflict for policy implementation. A number of factors crucial to the implementation process are identified as varyingly dependent on a policy's ambiguity and conflict level. Four policy implementation paradigms are identified and the relevance of the existing literature to these conditions is discussed. The four paradigms are low conflict-low ambiguity (administrative implementation), high conflict-low ambiguity (political implementation), high conflict-high ambiguity (symbolic implementation), and low conflict-high ambiguity (experimental implementation).
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A review of the policy implementation literature finds the field split into two major schools, top-down and bottom-up. Previous attempts to reconcile these models are described, followed by an alternative model. This model reconciles these approaches by concentrating on the theoretical significance of ambiguity and conflict for policy implementation. A number of factors crucial to the implementation process are identified as varyingly dependent on a policy's ambiguity and conflict level. Four policy implementation paradigms are identified and the relevance of the existing literature to these conditions is discussed. The four paradigms are low conflict-low ambiguity (administrative implementation), high conflict-low ambiguity (political implementation), high conflict-high ambiguity (symbolic implementation), and low conflict-high ambiguity (experimental implementation).
Key concepts: Ambiguity, Relevance (law), Politics, Role conflict, Field (mathematics), Process (computing), Political science, Computer science