Understanding the impacts of intelligence and anthropomorphism on user stickiness in AI-driven mobile banking applications: the moderator of technology readiness
研究了AI移动银行应用中感知智能和拟人化对用户粘性的正向影响，以及技术准备度中乐观和创新特质的增强调节作用，对金融科技产品设计有参考价值。
Purpose Artificial intelligence (AI) has enhanced mobile banking by improving user value and user experience. Success depends on user stickiness, but few studies have explored how AI-specific features (perceived intelligence and anthropomorphism) affect user stickiness or how technology readiness (optimism, innovativeness, discomfort, and insecurity) moderates these effects in the context of AI-enabled mobile banking. Design/methodology/approach This study develops a research model to examine the impacts of perceived intelligence and anthropomorphism on user stickiness, as well as the moderating role of technology readiness. Data were collected from a sample of 428 users with prior experience using AI-enabled mobile banking applications and were analyzed using the partial least squares (PLS) method. Findings The results reveal that both intelligence and anthropomorphism positively influence user stickiness in AI-enabled mobile banking applications, highlighting their essential role in encouraging more frequent usage of and extended usage time on these applications. In addition, optimism and innovativeness significantly strengthen the positive effects of both perceived intelligence and perceived anthropomorphism on user stickiness. In contrast, discomfort and insecurity do not significantly moderate the relationships between perceived intelligence or perceived anthropomorphism and user stickiness. Originality/value This study introduces user stickiness as a behaviorally grounded outcome to better explain user adoption behavior in AI-enabled mobile banking. The findings show that perceived anthropomorphism outweighs intelligence in driving user stickiness, and only optimism and innovativeness moderate these effects. Moreover, optimism proves more influential than innovativeness does, thereby refining the TRI framework and advancing the understanding of AI adoption in intelligent financial services.