A Systems Thinking Approach to Comparative Public Policy

Mrs. Bianca Cavicchi
Language
English
Abstract

This study compares the evolution of the bioenergy policy feedback process and how it affects local, sustainable development in two regional bioenergy systems (BES), i.e., in Emilia Romagna (Italy) and Hedmark (Norway). The bioenergy policy is considered part of the wider bioeconomy and sustainability transitions policy framework. In this context, the bioenergy policy process is considered as a feedback loop that involves environmental and humans’ dimensions, such as cognitive processes (e.g. perceptions) and material processes (e.g. revenues), power dynamics and institutional features.
Thus, the main goal of the study is to contribute to comparative public policy analysis and policy-making with a better understanding of how the feedback dynamics in the policy process influence its evolution, thus impacting on local, sustainable development. Based on this, the study will give inputs on how to enable a change in mindset and policy-making processes. The second goal is to advance a methodology for studying the policy feedback process based on systems thinking and system dynamics. The main research questions of this paper are: How can we leverage the feedback policy process structure to better secure sustainable local development?
The main idea in the policy feedback framework is that changes to existing policies or the introduction of new policies can have effects on sub-systems, which in turn can alter the conditions for subsequent policies. Pierson (1993) distinguished between two types of effects: resource or incentive effects and interpretive (cognitive) effects. Empirical studies of policy feedbacks have shown how these effects contribute to positive and negative feedback effects. However, this framework presents some methodological weaknesses (e.g. lack of strong analytical framework to analyse feedback relations and weak boundary definition process) and empirical limitations (e.g. only applied to the study of welfare policies in the US. To fill these gaps, this presentation draws on the case of a multiple policy context, i.e. where different policies interrelate (i.e. agriculture policy, industrial policy and energy policy) and system dynamics methodology (i.e. causal loop diagramming) and system archetypes are used to study and compare the policy feedback process.