This book discusses the feasibility of empirical research on technological development and changes in industry structure using an analytical framework which has roots in the work of Schumpeter and Marx.

In order for the innovation process to be successful, not only do innovations need to be developed and reached the market, but, once they are available for users, they have to spread on a large scale. In the innovation literature, a complete explanation is lacking of why some innovations reach a phase of large-scale diffusion faster than others, including both actor- and system-level components. For instance, what drives and hinders adopters to decide to adopt the innovation on the actor and system levels, and how adopters who participate in the largescale diffusion handle the adoption process and the implementation of the innovation, are questions still unanswered. As a consequence, it remains unclear how the large-scale diffusion process can be facilitated and speeded up. This thesis addresses these issues by studying the case of renewable electricity (RE) innovations. After decades of technology development and improvements, RE innovations are now mature enough to be bought off-the-shelf by individuals and organizations. Yet, the pace of their large-scale diffusion is still too slow for countries to reach their RE generation targets and to limit global warming. Through qualitative and quantitative methods including 59 semi-structured interviews with adopters, project developers and experts in Sweden, France and Germany as well as a survey sent to the whole population of RE adopters in Sweden, an adopter perspective is taken in order to explore the adoption dynamics shaping large-scale diffusion of innovation. More specifically, the thesis identifies the drivers and challenges of adoption during large-scale diffusion and their impact on adoption decisions and strategies. The outcome of this work is presented in a compiling synthesis and six appended papers. Findings show that adopters are heterogeneous with regard to their characteristics, as well as to the drivers, challenges and strategies that affect their adoption processes. Depending on their perceptions, some adopters are more influenced by drivers and challenges than others and, as a consequence, adopters base their adoption decisions on different motives and follow different strategies to implement the innovation. Moreover, the results suggest that the dynamics that occur during the large-scale diffusion process does not only come from the actor level and the level of the system where the largescale diffusion takes place, but also from parallel systems, which are related to adopters and their contexts, including both the social networks and the industries they primarily belong. This makes adopters the central drivers of the innovation diffusion process and this distinguishes the dynamics of large-scale diffusion from the dynamics of innovation development and early diffusion, in which the innovation is the central component. Based on the findings about the adoption dynamics shaping large-scale diffusion, the thesis raises the need to consider large-scale diffusion as part of a new system, different from the innovation system and that acknowledges the specificities of this process. A tentative model accounting for the central role of adopters and for the interactions between adopters, the diffusion system and parallel systems is introduced. Finally, the implications of these findings for policy makers and managers are put forward. In particular, there is a need for policies acknowledging adopters’ heterogeneity as well as the new challenges of large-scale diffusion. Strategies developed by adopters can be a source of inspiration for policy-makers, who can for instance promote the use of intermediaries, of adopters’ task environment and networks, as well as the formation of coalitions among adopters.

Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.

Policy Diffusion Dynamics in America integrates research from agenda setting and epidemiology to model factors that shape the speed and scope of public policy diffusion. Drawing on a data set of more than 130 policy innovations, the research demonstrates that the 'laboratories of democracy' metaphor for incremental policy evaluation and emulation is insufficient to capture the dynamic process of policy diffusion in America. A significant subset of innovations trigger outbreaks - the extremely rapid adoption of innovation across states. The book demonstrates how variation in the characteristics of policies, the political and institutional traits of states, and differences among interest group carriers interact to produce distinct patterns of policy diffusion.