Background - Despite significant investment, fashion e-commerce platforms face underutilization of AI chatbots, which hold potential for transforming shopping experiences. Amidst the competition by fast fashion giants and sustainability trends, brands strive to engage the environmentally conscious Gen Z demographic. However, this potential is challenged by an adoption gap among this cohort, necessitating deeper insights of the factors influencing chatbot use in sustainable fashion shopping.

Purpose - Driven by Venkatesh et al.’s (2003) Unified Theory of Acceptance and Use of Technology (UTAUT) and Katz et al.’s (1973) Uses and Gratification Theory (UGT), this study aims to test and develop a comprehensive framework to examine Gen Z consumers' acceptance of AI chatbots for sustainable fashion shopping. This research seeks to integrate both functional and hedonic motivations, alongside social influences, to better understand and address the adoption gap.

Method - This study uses a mixed-methods approach, combining quantitative data from 185 respondents across 15 countries via Qualtrics and qualitative insights from interviews of a treatment group and a control group, categorized by 10 participants’ experience in sustainable fashion shopping to minimize bias. The data was analyzed using regression analysis in IBM SPSS and thematic coding.

Findings - The quantitative results show that performance expectancy, social influence, enjoyment have a positive and significant effect on behavioral intention. Conversely, effort expectancy, facilitating conditions, and personal innovativeness do not exhibit a significant influence. Moreover, the qualitative insights particularly indicate the importance of practical benefits (performance expectancy) and facilitating conditions. Additionally, social influence is more like an enabler rather than a determinant, while personal innovativeness can be a double-edge sword. Skepticism and technological adaptability were revealed to disrupt other factors like social influence and enjoyment.

Originality/ value - By synthesizing UTAUT and UGT frameworks, this study enriches the existing literature by providing a robust model built on both functional and hedonic motivations with the inclusion of previously unconsidered disruptive factors in the adoption of AI chatbots for sustainable fashion. Furthermore, this study’s knowledge offers implications for e-commerce platforms and authorities in designing strategies that align with Gen Z's digital habits and environmental mindset. These contributions aim to foster sustainable shopping practices and facilitate an effective use of AI technologies in retail sectors gradually adapted to the preferences of the next generation of consumers.