Knowledge for policymaking: An evolutionary perspective to achieve policy resilience

This chapter discusses a cognitive-evolutionary model (Dotti 2018; Slembeck 1997) which pivots on the role of knowledge for policymaking. The goal is to highlight possibilities for cities and regions to foster policy resilience, broadly understood as the collective capacity to deal with emerging policy issues. The model draws on the seminal works of Schumpeter (1976) and Hall (1993) and emphasises the importance of adopting a territorial perspective to achieve policy resilience in cities and regions. The main argument at the basis of the model is that cities and regions can effectively mobilise and develop policy knowledge to achieve policy resilience only through gaining an understanding of the dynamics of policy learning (i.e. learning how to learn). The model is not based on a linear, mechanic and deterministic perspective and it does not aim to predict the outcome of policymaking processes. Rather, it presents four different scenarios, useful for policymakers and actors of learning, in which policy learning has different potentials to bring about policy change/ innovation. The aim is to highlight the nexus among the various elements and dimensions of each scenario and to consider their mutual interdependences and multifaceted implications for cities and regions planning to foster policy resilience.