Authors: Maxime Stauffer, Konrad Seifert, Isaak Mengesha, Igor Krawczuk, Jens Fischer, Giovanna Di Marzo Serugendo
Preprint submitted to Complexity.
While policy process theory has converged on the view that policymaking can be studied as a complex system, the literature has only minimally used the methodological complement to the theory - experiments performed with computational models. Implementations are rare, mainly pushed by computer scientists in trans-disciplinary work and often so detached from mainstream theory that they form a separate line of research instead of testing theories from the social sciences.
This paper builds on the theory of policy processes and computational sciences to advance the computational turn of policy process studies. We examine how and why complexity science lends itself to study policymaking, propose a workflow to guide the creation of computational policy process models, describe the contours of a computational approach to policy process modeling and define goals for future research that follow from this computational turn. Overall, we aim to promote a computational turn of policy process studies that is empirical and hypothesis-driven.