Compulsive policy-making—The evolution of the German feed-in tariff system for solar photovoltaic power

•We study how technology dynamics and uncertainty affect policy interventions in innovation systems.•We investigate the German feed-in tariff system for solar photovoltaic power.•We show that technological change was both a result and driver of policy changes.•We point to parallels in the process with Rosenberg's (1969) ‘compulsive sequences’.•Our research more closely integrates the literature on innovation systems and policy learning.

In recent years, policy approaches that build upon the notion of innovation systems have enjoyed increasing attention in science, technology and innovation policy. But while the usefulness of systemic thinking in policy-making has been demonstrated in a large number of empirical settings, we still lack a detailed understanding of the dynamics at play when policy makers address systemic problems. In this paper, we show how complex interdependencies and the uncertain nature of technological change shape the process of targeted policy interventions in socio-technical systems. Toward this end we analyzed the evolution of the German feed-in tariff (FIT) system for solar photovoltaic power, a highly effective and widely copied policy instrument targeted at fostering the diffusion and development of renewable energy technologies. We find that the policy has been subject to a considerable amount of changes, many of which are the result of policy makers addressing specific system issues and bottlenecks. Interestingly, however, often these issues themselves were driven by unforeseen technological developments induced by previous policy interventions. We argue that the pattern of policy serving as both a solution to and a driver of technological bottlenecks shows strong similarities with what Rosenberg (1969) called ‘compulsive sequences’ in the development of technical systems. By shedding more light on how the characteristics of socio-technical systems affect policy interventions, our framework represents a first step toward more closely integrating the literature on innovation systems with the work on policy learning.