Defining the relationship between housing characteristics, household demographics, and time-of-use demand response participation

As major energy consumers connected to the electric grid, the participation of residential buildings in demand-side management (DSM) programs, including time of use (TOU) rates, can help utilities with load management and support decarbonization goals. However, participation in these programs is influenced by a combination of household demographic and housing characteristics, which are often examined separately despite their potential interactions. To address this gap, this study develops and analyzes a linked dataset that combines demographic and housing characteristics at the household level, together with respondents' interest in adopting smart technologies (ST) and willingness to adjust thermostat settings. Separate and combined predictive models were developed to evaluate the influence of these factors on DSM related behaviors. Results revealed that combined demographic and housing models outperformed separate models (χ 2 = 14.48–24.99, p < 0.001), indicating that jointly considering these factors better captures the complex drivers of DSM participation. Age, education level, tenure and dwelling type emerged as important predictors for ST technology adoption, while home size, dwelling type, and tenure status more effectively explained respondents' willingness to adjust thermostat setpoints throughout the day. Although 81.7% of respondents reported willingness to adjust setpoints at least sometimes during the day, only 11% were willing to do so during evening peak periods. Household income also seems to predict interest and willingness, indicating that financial resources may influence households’ ability to adopt and participate in DSM/TOU programs. These findings can help utilities tailor DSM and TOU programs to different household contexts, for example, by aligning incentives and outreach with housing types and tenure patterns, to improve participation and load-shifting outcomes. They can also guide policymakers in developing more equitable energy policies that expand access to ST across diverse income and housing groups.