Systems-based methods for research & innovation policy

The study aims to provide evidence of system methods that can be used in the policy cycle to address complexity and support systemic transitions through transformative innovation policy. To do so, the study provides a review of system methods and an evaluation of their application and added value at the different stages of the policy cycle. It concludes with key recommendations on how to ensure the uptake of system methods in the R&I policy cycle. The study highlights the importance of systems-based methods in designing effective policies that address the root causes of challenges and promote transformative change. The methods discussed include causal loop diagramming, system dynamics modelling, agent-based modelling, and strategic foresight. The study also emphasizes the need for integrating these methods throughout the policy cycle to foster iterative learning, adaptive policy development, and long-term policy orientation.