Smart Grid Adoption Likeliness Framework: Comparing Idaho and National Residential Consumers' Perceptions

New energy technologies that provide real-time visibility of the electricity grid's performance, along with the ability to address unusual events in the grid and allow consumers to manage their energy use, are being developed in the United States. Primary drivers for the new technologies include the growing energy demand, tightening environmental regulations, aging electricity infrastructure, and rising consumer demand to become more involved in managing individual energy usage. In the literature and in practice, it is unclear if, and to what extent, residential consumers will adopt smart grid technologies. The purpose of this quantitative study was to examine the relationships between demographic characteristics, perceptions, and the likelihood of adopting smart grid technologies among residential energy consumers. The results of a 31-item survey were analyzed for differences within the Idaho consumers and compared against national consumers. Analysis of variance was used to examine possible differences between the dependent variable of likeliness to adopt smart grid technologies and the independent variables of age, gender, residential ownership, and residential location. No differences were found among Idaho consumers in their likeliness to adopt smart grid technologies. An independent sample t-test was used to examine possible differences between the two groups of Idaho consumers and national consumers in their level of interest in receiving detailed feedback information on energy usage, the added convenience of the smart grid, renewable energy, the willingness to pay for infrastructure costs, and the likeliness to adopt smart grid technologies. The level of interest in receiving detailed feedback information on energy usage was significantly different between the two groups (t = 3.11, p = .0023), while the other variables were similar. The study contributes to technology adoption research regarding specific consumer perceptions and provides a framework that estimates the likeliness of adopting smart grid technologies by residential consumers. The study findings could assist public utility managers and technology adoption researchers as they develop strategies to enable wide-scale adoption of smart grid technologies as a solution to the energy problem. Future research should be conducted among commercial and industrial energy consumers to further validate the findings and conclusions of this research.