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Purpose Despite the widespread adoption of generative artificial intelligence (Gen AI) across various sectors, there is a limited understanding of the factors driving its use for environmental sustainability and green purchase behavior. The present study fills this gap by identifying the key factors influencing the use of Gen AI to access environmental information and the willingness to practice green purchasing behavior. Design/methodology/approach Through integrating the Unified Theory of Acceptance and Use of Technology 2 and the Value-Belief-Norm theory, with psychological ownership and warm glow as context-relevant extensions, we analyzed data from 514 respondents using Partial Least Squares Structural Equation Modeling and Artificial Neural Network methodologies. Findings The results highlight the importance of performance expectancy, effort expectancy, green value, learning value, psychological ownership, and environmental concern in driving the adoption of Gen AI for environmental information as well as green purchasing intentions. The study also underscores the role of emotional satisfaction (warm glow) in shaping behavioral intentions, highlighting a complex emotional-behavioral dynamic. Practical implications Insights from this study can guide technology developers in designing more user-centric AI tools, help marketers tailor eco-conscious messaging, and support policymakers in crafting strategies that promote sustainable consumer choices through digital innovation. Originality/value This study is among the first to explore the intersection of Gen AI and green consumerism using a bounded theoretical framework and a dual-method approach. The findings contribute to the growing literature on sustainable technology adoption and provide a foundation for future research on the environmental applications of AI technologies.
Foroughi et al. (Wed,) studied this question.