This study investigates how the quality of AI-Chatbot conversations during online-shopping encourages consumer to choose eco-friendly products in an emerging market. Using the Stimulus-Organism-Response (S-O-R) framework, it measures whether perceived usefulness, trust, satisfaction, and perceived risk explain this relationship. The data were collected from 547 active chatbot users in Nepal, which was then analysed using SmartPLS V4. The results highlight that high-quality chatbot interactions enhance users’ perception of usefulness, satisfaction and trust, while simultaneously lowering risk. The model explains 58.4% of the variance in green purchase intention. Among them, organismic-factors, perceived risk emerges as strongest inhibitor of sustainable purchasing, while trust and usefulness positively support green purchase intention; however, satisfaction directly doesn’t influence it. The results indicate that humanizing AI-Chatbots is mainly about making them more reliable and transparent, so that it reduces uncertainty, supports decision making, and builds confidence in green choices, allowing users to feel assured when following their suggestions and become more willing to choose sustainable-products. The study provides evidence from Nepal and offers a careful understanding of how chatbot quality shapes sustainable purchase intention in an emerging-market setting.
Neupane et al. (Wed,) studied this question.