The impact of new technologies within and across industries is only felt through their widespread diffusion, yet studies of technology diffusion are scarce compared to other aspects of the innovation process. The electric power industry is one industry that is currently undergoing substantial change as a result of both technological and institutional innovations. In this dissertation I examine the economic rationale for the adoption of smart meters by electric power utilities and the relationship between smart meters and the evolving electric power industry. I contribute to empirical research on technology diffusion by studying the early diffusion of smart meters in the US electric power industry. Using a panel dataset and econometric models, I analyze the determinants of both the interfirm and intrafirm diffusion of smart meters in the United States. The empirical findings suggest multiple drivers of smart meter diffusion. Policy and regulatory support have had a significant, positive impact on adoption but have not been the only relevant determinants. The findings also suggest that utility characteristics and some combination of learning, cost reductions, and technology standards have been important determinants affecting smart meter diffusion. I also explore the policy implications resulting from this analysis for enhancing the diffusion of smart meters. The costs and benefits of adopting smart meters have been more uncertain than initially thought, suggesting that some policy support for adoption was premature. The coordination of policies is also necessary to achieve the full benefits of using smart meters
