These patterns motivate our inquiry into which factors drive intention to use and how trust and user satisfaction condition adoption in both settings. Therefore,this study examines bankers in Vietnam and China through the extended Unified Theory of Acceptance and Use of Technology (UTAUT) Model, showing how performance, support, and digital trust translate intention into use.

To address these questions, the study follows a qualitative design grounded in an extended UTAUT that adds Trust and User Satisfaction. Semi-structured online interviews were held with 8 banking employees in Vietnam and China. Thematic analysis combined model-based deductive codes with inductive codes for emerging issues in ATLAS.ti, with Excel and ChatGPT supporting organization and early theme surfacing. Finally, patterns were compared across the two countries to identify convergences and differences.

The analysis reveals that performance expectancy is the main engine of adoption, which includes speed, accuracy, and richer functions. Effort expectancy lowers learning costs but rarely drives expansion on its own. Social influence and facilitating conditions enable early and wider use through peer help, supervisor support, clear policies, professional training, and stable systems. Trust acts as a regulator: reliable output and privacy protections maintain confidence, while language barriers and erroneous outputs prompt verification and double-checking. Satisfaction rises when tools fit tasks. Cross-country patterns show stronger expansion intent in Vietnam backed by strategy, and a Chinese focus on operational reliability and privacy discipline. Together, these results indicate that credible performance plus visible support and transparent governance convert trial into sustained use and create conditions for scale.