Adopting generative AI for house design: a multi-stage model of user perception and environmental attitudes

Purpose This study aims to explore the factors influencing consumer adoption and purchase intention of generative artificial intelligence (GAI) tools in the context of residential design. It aims to understand how technological, emotional and environmental factors shape user behavior toward emerging artificial intelligence (AI) design technologies. Design/methodology/approach A stage-based structural model was developed by integrating the artificially intelligent device use acceptance and task-oriented artificial intelligence acceptance frameworks. The model includes technological, psychological and social drivers, with perceived well-being as an emotional outcome and environmental awareness as a moderating variable. Data were collected via an online survey from 304 participants and analyzed using partial least squares structural equation modeling. Findings Perceived competence, performance expectancy and interaction convenience significantly influence user adoption. Perceived well-being plays a critical role in enhancing purchase intention, while higher effort expectancy is associated with greater inclination to revert to traditional design methods. Environmental awareness moderates several key relationships, reinforcing the role of sustainability in consumer decision-making. Originality/value This research extends traditional AI adoption models by incorporating emotional outcomes and environmental consciousness. It offers new insights into how consumers evaluate GAI tools for home design and provides practical implications for developers and marketers targeting the sustainable housing sector.