Fostering sustainable technologies –a framework for analysing the governance of innovation systemsKarl Hillman, Post-doc researcher, Institute for Management of Innovation and Technology (IMIT) and University of Gothenburg,SwedenMåns Nilsson, Associate professor, Stockholm Environment Institute (SEI), SwedenAnnika Rickne*, Associate professor, University of Gothenburg and Institute for Management of Innovation and Technology (IMIT), SwedenThomas Magnusson, Assistantprofessor, Institute for Management of Innovation and Technology (IMIT) and Linköping University, SwedenAbstractThere is an ever-growing recognition among policy-makers, industries and analysts that the development and diffusion of technological innovations need governing in order to contribute to societal goals related to sustainability, such as climate change mitigation and resource efficiency. Yet, little is known about how different types of governance influence innovation processes, and what may be effective governance arrangements to pursue to influence the development and diffusion of sustainable technological innovations. This paper develops a framework for the analysis of governance arrangements aimed at fostering more sustainable technological innovations. The framework addresses important debates in governance and innovation research. First, it addresses a critical gap in the literature on technological innovation systems (TISs) which is the connection between governance arrangements and the functionality of the TIS. Second, it contextualizes this connection in relation to the multi-level perspective (MLP) to transitions, assuming that governance arrangements influence in different ways the functionality of the TIS depending on the structure, stability and positioning of the TIS in relation to the regime. Third, it develops a comprehensive heuristic to examine the prevalence, role and effectiveness of various modes of governance, departing from a simple typology of "who governs", "how do they govern", and "what isgoverned".The framework prompts a temporal causal analysis of predominantly qualitative nature.