Modeling the adoption dynamics of community integrated energy systems: Behavioral drivers and policy implications for renewable energy deployment

Community integrated energy systems (CIES) are a promising option for integrating distributed renewable energy in residential communities, yet the factors shaping residents' willingness to participate remain underexamined. This study develops an extended Technology Acceptance Model that incorporates psychological, social, institutional, and economic factors and tests the proposed framework using survey data from 589 respondents via structural equation modeling. The results show that attitude toward use is the strongest predictor of residents' behavioral intention, followed by government involvement and perceived cost. Technology trust, resident innovativeness, perceived ease of use, and subjective norm also significantly influence intention, whereas attitude toward renewable energy, perceived usefulness, and environmental concern play comparatively weaker roles. By identifying the main behavioral drivers of CIES participation, this study links household-level adoption behavior to community energy planning and provides evidence to inform policies that can accelerate distributed low-carbon transitions and the development of sustainable community energy systems.