## 7 Conclusions  
In summary, this study explored the motivations of university students to use LLMs to assist with online green product consumption and analyzed the technology acceptance and continue using intention of university students towards LLMs in the context of assisting online sustainable consumption. The empirical results show that key technological and psychological factors significantly influence users' acceptance of shopping assistants driven by LLMs. Notably, when consumers consider LLMs to be practical, trustworthy, and in line with their own needs, they are more inclined to adopt them. This adoption is also related to the strong green experience brought by LLMs, indicating that integrating tools driven by LLMs into online retail can encourage more environmentally friendly consumer behavior. These findings enrich our understanding of digital interventions for sustainable development and pave the way for further research on how to utilize advanced artificial intelligence to support consumer choices of sustainable products. Theoretically, this study broadens the explanatory boundaries of the technology acceptance framework. More significantly, it furnishes a more nuanced theoretical perspective for comprehending the evaluation mechanism of emerging artificial intelligence services and the factors influencing their continued use. This research situates green self-identity value (GSV) as an extension of perceived value in a specific domain, providing a reference for subsequent research to explore the longitudinal changes of GSV in this context. Practically, the research findings offer actionable insights for e-commerce platforms and policymakers. Specifically, enhancing the perceived practicality and credibility of services based on LLMs can increase user utilization rates and effectively guide consumers to make shopping choices that better suit their personalized needs. Developers could consider embedding verifiable ecological impact data in the conversational output, adopting adaptive conversations focused on users' sustainability goals, and leveraging feedback in real time to reinforce sustainable decisions. These implications highlight the strategic value of LLM innovation in promoting sustainable consumption and improving the online shopping experience. Despite the contributions of this study, several limitations should be acknowledged. One limitation lies in the fact that the research was carried out within a specific context and with a particular sample, which may impede the generalizability of the findings to other settings. Another concern is the rapid evolution of LLM technology. This implies that users' perceptions and behaviors might change over time, necessitating continuous research to capture such dynamics. Moreover, this study centered on intended behavior rather than actual behavior. Consequently, future research ought to investigate the actual usage patterns of LLMs and their long-term impact on sustainable development outcomes. To tackle these issues, future research could adopt a longitudinal design, explore diverse contexts, and integrate emerging LLM features to validate and extend the current research findings. This would enhance our understanding of how to optimally utilize LLM technology for sustainable online consumption on a broader scale. Conceptualization, J.Y., W.Y. and W.C.; methodology, J.Y. ; software, J.Y. and S.W. ; validation, J.Y., W.Y. and J.G. ; formal analysis, J.Y. ; investigation, J.Y. and J.G. ; resources, J.Y. and K.N. ; data curation, J.Y. ; writing--original draft preparation, J.Y. ; writing--review and editing, J.Y. and S.W. ; visualization, J.Y., W.Y. and W.C.; supervision, S.W. and K.N. ; project administration, S.W. and K.N. ; funding acquisition, J.G. and W.C. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This study was conducted in accordance with the Declaration of Helsinki.