論文作者

Kuo-Tai Lu.

卷號/期號:

摘要:

The rise of robo-advisors-automated, algorithm-driven investment services—has transformed the financial service landscape by offering low-cost, data-driven solutions tailored to individual users. While prior research has examined factors influencing the adoption of FinTech tools, limited attention has been paid to how users’ experiential value and involvement interact with perceived innovation attributes to shape behavioral intention. This study integrates Innovation Diffusion Theory, Experiential Value Theory, and Involvement Theory to propose a comprehensive research model. Using data from 565 valid responses collected in Taiwan, the model is tested via partial least squares structural equation modeling (PLS-SEM). The results indicate that innovation attributes-particularly usability, relative advantage, and observability-positively influence multiple dimensions of experiential value, including investment return, hedonic value, aesthetics, and playfulness. In turn, experiential value significantly predicts users’ behavioral intention to adopt robo-advisory services, with investment return and hedonic value emerging as the strongest predictors. Interestingly, user involvement negatively moderates the relationship between playfulness and behavioral intention, suggesting that highly involved users prioritize functionality over entertainment. This study contributes to the FinTech adoption literature by identifying experiential value as a critical mediating mechanism and reframing the role of user involvement. The findings provide theoretical insights and practical guidance for designing personalized, user-centric robo-advisory platforms.

Keywords :

Robo-advisors, Experiential value, Innovation attributes, Involvement, FinTech adoption

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