Understanding smart thermostat adoption: Housing, HVAC, and socio-economic traits in the U.S.

In transition to smart and connected communities, smart thermostats support real-time occupancy-based setpoint adjustments and serve as enablers of demand response strategies, given their integrations with heating, ventilation, and air-conditioning (HVAC) systems in buildings. To date, prior research has not systematically examined how smart thermostat adopters’ socio-economic and housing characteristics have evolved over time – particularly during a period when rebate programs have been available in the United States. This study aims to address this gap by analyzing socio-economic and housing characteristics of U.S. smart thermostat adopters through the lens of the diffusion of innovation (DoI) theory. We utilized the rebate program data, ecobee Donate Your Data metadata, and the 2015 and 2020 Residential Energy Consumption Survey data to group, analyze, and compare adopters and non-adopters, and innovators and early adopters. We also applied a feature selection process to identify key variables contributing to adoption and assess how they changed across adoption stages. Results indicated an upward trend in rebate program availability, although this trend did not always correlate with adoption at the state level. Also, adopters did not actively use remote sensors that play a key role in fully leveraging smart thermostat capabilities. Notably, income and homeownership remained the strongest predictors of adoption. These findings indicate that despite broader diffusion from innovators to early adopters, smart thermostat adoption remains concentrated among higher-income homeowners, with renters and lower-income households increasingly underrepresented. This study contributes to our understanding of how smart thermostat adoption has diffused across diverse household types and socio-economic groups, and highlights the value of connecting and analyzing various large-scale, national-level data sources using the lens of DoI theory to inform equity-aware energy policy and technology development. • Smart thermostat adopters and non-adopters were compared. • Using diffusion of innovation theory, innovators and early adopters were found. • Their socio-demographic and housing characteristics were compared. • Rebate program availability did not consistently correlate with adoption rates. • Income and homeownership have been the key factor in smart thermostat adoption.