Our research includes linear regression, principal component regression, and spatial error models to provide empirical evidence for the relationship between the adoption rates and socio-economic, geographical, and technical factors while identifying characteristics of adopter groups. The results suggest that the relative advantage factors – electricity prices and solar irradiation – play the most significant role across all regions and market segmentations. Statewide policy indicators are the second most significant factor, followed by socio-economic variables on employment status, remote working, car ownership, and property value. Our results indicate that homeowners do not only differ in their circumstances but also in their motivations.